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Telnyx Email - curl · team-telnyx | DecimalAI

Marketingby team-telnyx

Telnyx Email - curl

Send transactional email, batch sends, scheduled delivery, templates, email validation, and track delivery events.

Never made a case worseMaintained

SkillScore

SkillScore100/100

Test results 100

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

29%100%of test cases passed +71 pts

Without skill7 of 24

With skill24 of 24

17 fixed7 passed either way0 still failing0 broke

Measured on gemini-3.6-flash9/3/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWrite a curl command to fetch overall recipient-level email statistics (counts and rates) for our Telnyx account for July 2026.

Without the skillMissed

With the skillPassed

Same model, same task. Answers are capped and redacted.

Use this skill

Your agent runs on

Adds every file the skill has, pinned so you can update it. No account needed.

pip install "decimalai>=0.15"
decimalai skills add team-telnyx-telnyx-email-curl
claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

The same install from Python, for a notebook or a setup script.

Install

pip install "decimalai>=0.15"

Add the skill

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

print("Added. Start Claude Code with the command below.")

Start Claude Code with it

claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

Type these in a Claude Code session. No account or API key. It writes the skill and any files it bundles, and asks first when its safety rating isn't Passed.

Add the DecimalAI plugin, once

/plugin marketplace add decimal-labs/decimalai-claude-plugins
/plugin install decimalai@decimalai

Install this skill

/decimalai:install team-telnyx-telnyx-email-curl

The plugin needs python3 and curl on your machine.

No Python or account. Claude Code picks it up in its next session.

Save it into your project

curl -fsSL --create-dirs -o .claude/skills/team-telnyx-telnyx-email-curl/SKILL.md https://app.decimal.ai/s/team-telnyx-telnyx-email-curl/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/team-telnyx-telnyx-email-curl/SKILL.md

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Claude Code docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

async def main():
    async for message in query(prompt="Hello!", options=options):
        print(message)

# In a notebook or async code: await main()
asyncio.run(main())

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Claude Agent SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai-agents]"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

Install

pip install "decimalai[openai-agents]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

OpenAI Agents docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai]"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

Install

pip install "decimalai[openai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

OpenAI SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[anthropic]"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

Install

pip install "decimalai[anthropic]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Anthropic docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[google-genai]"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

Install

pip install "decimalai[google-genai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from google import genai
from google.genai import types

client = genai.Client()
skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Gemini API docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

Install

pip install "decimalai[langchain]" langchain-openai

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

LangChain docs

CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

The same install from Python, for a notebook or a setup script. CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

No DecimalAI package. CrewAI's own loader reads the folder, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                         # your own CrewAI LLM
    skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

CrewAI docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[adk]"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

Install

pip install "decimalai[adk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from google.adk.agents import LlmAgent

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Google ADK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

Install

pip install "decimalai[pydantic-ai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Pydantic AI docs

Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

The same install from Python, for a notebook or a setup script. Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Deep Agents docs

Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

The same install from Python, for a notebook or a setup script. Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Microsoft Agent Framework docs

Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add team-telnyx-telnyx-email-curl

Add it to your agent

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

The same install from Python, for a notebook or a setup script. Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("team-telnyx-telnyx-email-curl")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/team-telnyx-telnyx-email-curl/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Strands docs

Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.

pip install "decimalai>=0.15"
decimalai skills add team-telnyx-telnyx-email-curl

No Python or account. Cursor, Copilot, Cline and Warp read this folder by themselves.

Save it into your project

curl -fsSL --create-dirs -o .agents/skills/team-telnyx-telnyx-email-curl/SKILL.md https://app.decimal.ai/s/team-telnyx-telnyx-email-curl/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/team-telnyx-telnyx-email-curl/SKILL.md

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Cursor and other editors docs

Fetch the file and give its text to your model as instructions. No account or package needed.

Get the file

curl -fsSL https://app.decimal.ai/s/team-telnyx-telnyx-email-curl/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/team-telnyx-telnyx-email-curl.json

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 9/3/2026
Source: team-telnyx/ai ↗
License: MIT

Manage it in DecimalAI

Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.

Claude Code reads files from your project, so DecimalAI config does not apply there.

On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.

On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.

On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

Editors read files from your project, so DecimalAI config does not apply there.

Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.

Use this skill

SKILL.md

Telnyx Email - curl

Installation

# curl is pre-installed on macOS, Linux, and Windows 10+
# jq is required for examples that capture IDs from responses:
#   macOS: brew install jq
#   Debian/Ubuntu: sudo apt-get install jq

Setup

export TELNYX_API_KEY="YOUR_API_KEY_HERE"

All examples below use $TELNYX_API_KEY for authentication.

Error Handling

All API calls can fail with network errors, rate limits (429), validation errors (400 or 422), or authentication errors (401). Preserve the response body so the Telnyx error code and detail remain available:

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "from": {"email": "[email protected]", "name": "Example"},
    "to": ["[email protected]"],
    "subject": "Hello from Telnyx",
    "text_body": "Your notification is ready."
  }' \
  "https://api.telnyx.com/v2/email_messages"

Common errors: 401 invalid credentials, 403 sender-domain eligibility or verification failure, 404 resource not found, 413 body larger than 8,000,000 bytes, and 422 semantic validation or template-rendering failure. A 429 is not necessarily a transient throughput limit: it can indicate a reputation suspension or a daily policy limit. Inspect .errors[0].code and .errors[0].detail before deciding whether to retry. See the full taxonomy in references/api-details.md.

Important Notes

Base URL: All paths in this skill are relative to https://api.telnyx.com/v2.
Sender domain: The domain in from.email must be authorized and ready for sending. A successful create response means accepted, queued, scheduled, or sandbox-created—not delivered.
Address input: from, reply_to, and each to/cc/bcc item accept either a string address or { "email": "...", "name": "..." }. Recipients must be unique across to, cc, and bcc after case-insensitive normalization.
Body or template: subject is required unless template_id is supplied. With template_id, do not also send subject, html_body, or text_body; pass Liquid values in template_variables.
Pagination: Core Email endpoints use page_size (default 25, maximum 100) and the opaque page_cursor returned in .meta.page_cursor. Do not translate these names to page[size] or page[cursor].
Message listing: GET /email_messages currently implements cursor pagination only; no message filters are exposed. Event and recipient list endpoints have their own filters.

Operational Caveats

Scheduling is fail-open: scheduled_at is the preferred field. If it is invalid or in the past, the API silently sends immediately. Validate the timestamp before sending and confirm the response status is scheduled when future delivery is required. The legacy send_at alias remains accepted; if both are present, scheduled_at wins.
Batch status: POST /email_messages/batch always returns 207 Multi-Status, including when every item succeeds. It does not return 202.
Batch limit: A batch contains 1–50 messages. Split larger jobs and give each request its own idempotency key.
Idempotency is endpoint-specific: Idempotency-Key is supported only on POST /email_messages, POST /email_messages/batch, POST /email_templates, POST /email_validations, and POST /email_validations/batch. Do not send it universally.
Sandbox behavior: sandbox_mode: true skips Kafka/MTA delivery, but still persists the message, emits a sandbox event, and creates a non-billable Email Detail Record (EDR). Batch-level sandbox_mode overrides every per-message value.
429 requires classification: It can mean reputation suspension or a daily policy limit. Read the error code/detail; do not blindly back off and retry an account-policy failure.
Attachments are in-band JSON: Put attachment content in the request as a Base64 string. disposition: "inline" plus content_id supports CID references. The whole request body is limited to 8,000,000 bytes (approximately 8 MB), including Base64 overhead.
Tags are not labels: Outbound tags are immutable billing/reporting attribution propagated to EDRs and Mission Control. Mailbox labels are mutable workflow state and are a different concept.
Threading is single-send only: in_reply_to_message_id, reply_to_all, and forward_of_message_id are accepted by single send but not by batch send. in_reply_to_message_id and forward_of_message_id are mutually exclusive.

Reference Use Rules

Do not invent Telnyx parameters, enums, response fields, or webhook fields.

If a parameter, enum, or response field is not shown inline, read references/api-details.md before writing the request or handler.
Before using an operation in ## Additional Operations, read the parameter reference and the response schemas.
Before matching webhook fields or event names, read the webhook payload reference. Pollable and subscribable event enums are intentionally different.
Treat the two delete-message routes marked not yet available as unreachable even though they appear in the OpenAPI contract.

Core Tasks

Send an email

Primary outbound transactional-email flow.

POST /v2/email_messages

Parameter	Type	Required	Description
`from`	string or email-address object	Yes	Sender address; object form supports `email` and optional `name`.
`to`	array[string or email-address object]	Yes	At least one recipient. Must be unique across all recipient lists.
`from_name`	string	No	Display name for string `from`; overrides `from.name`.
`cc`	array[string or object]	No	Carbon-copy recipients.
`bcc`	array[string or object]	No	Blind-copy recipients.
`reply_to`	string or object	No	Reply-to address; an object name is ignored when stored.
`subject`	string	Conditional	Required without `template_id`. Do not use with a template.
`html_body`	string	No	HTML body. Returned only by the message detail endpoint.
`text_body`	string	No	Plain-text body. Returned only by the message detail endpoint.
`headers`	object[string,string]	No	Custom headers; write-only.
`attachments`	array[attachment]	No	Embedded Base64 attachment objects.
`tags`	array[string]	No	Immutable EDR/reporting attribution; not returned by the API.
`group_id`	UUID or null	No	Unsubscribe group for suppression checks.
`ignore_suppression`	boolean	No	Default false; requires `email:override` scope and cannot override hard-bounce, complaint, or invalid-address suppressions.
`metadata`	object	No	Custom write-only metadata.
`tracking_settings`	object	No	`open_tracking` and/or `click_tracking`; omitted values inherit domain settings.
`template_id`	UUID	No	Liquid template ID. Makes `subject`/body fields mutually exclusive.
`template_variables`	object	No	Liquid values; defaults to `{}`.
`scheduled_at`	date-time or null	No	Preferred future send time; invalid/past values send immediately.
`send_at`	date-time	No	Deprecated alias for `scheduled_at`.
`inline_css`	boolean	No	Inline CSS before sending; default false.
`sandbox_mode`	boolean	No	Persist and emit sandbox records without MTA delivery; default false.
`in_reply_to_message_id`	UUID or null	No	Parent Telnyx message; adds RFC 5322 threading headers.
`reply_to_all`	boolean or null	No	Reply-all intent; meaningful only with `in_reply_to_message_id`.
`forward_of_message_id`	UUID or null	No	Forward provenance; mutually exclusive with `in_reply_to_message_id`.
`Idempotency-Key`	header string	No	1–255 letters, digits, `_`, or `-`; reuse only for the identical retry.

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: 8e03978e-40d5-43e8-bc93-6894a57f9326" \
  -d '{
    "from": {"email": "[email protected]", "name": "Example Orders"},
    "to": [{"email": "[email protected]", "name": "Customer"}],
    "subject": "Order received",
    "html_body": "<p>Thanks for your order.</p>",
    "text_body": "Thanks for your order.",
    "tags": ["order-confirmation"],
    "tracking_settings": {"open_tracking": true, "click_tracking": true}
  }' \
  "https://api.telnyx.com/v2/email_messages"

Primary response fields:

.data.id, .data.status, .data.from, .data.to, .data.cc, .data.bcc
.data.subject, .data.template_id, .data.attachments, .data.events
.data.created_at, optional .data.scheduled_at, .data.sandbox, and .data.recipient_statuses
optional top-level .suppressed[] when some recipients were removed but at least one remains

Send a batch

Send 1–50 independent messages. Always parse both success and error arrays from the 207 response.

POST /v2/email_messages/batch

Parameter	Type	Required	Description
`messages`	array[message]	Yes	1–50 items; each has the single-send shape except the three threading fields.
`sandbox_mode`	boolean	No	Applies to every item and overrides item-level `sandbox_mode`.
`Idempotency-Key`	header string	No	Idempotency for the whole batch request.

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: d6aa99f9-df20-4caf-99aa-e4c8b67e80ef" \
  -d '{
    "messages": [
      {
        "from": "[email protected]",
        "to": ["[email protected]"],
        "subject": "Alert one",
        "text_body": "First alert"
      },
      {
        "from": "[email protected]",
        "to": ["[email protected]"],
        "subject": "Alert two",
        "text_body": "Second alert"
      }
    ]
  }' \
  "https://api.telnyx.com/v2/email_messages/batch"

Primary response fields:

.data[] — successful EmailMessage objects
.errors[] — failed items with zero-based index, code, and message
.meta.total, .meta.succeeded, .meta.failed

Schedule and cancel an email

Scheduling uses the normal create endpoint. Confirm .data.status == "scheduled"; an invalid or past timestamp is silently treated as an immediate send.

# Schedule for a future time (compute dynamically so the value is always in the future)
SCHEDULED_AT=$(date -u -v+1H '+%Y-%m-%dT%H:%M:%SZ' 2>/dev/null || date -u -d '+1 hour' '+%Y-%m-%dT%H:%M:%SZ')

# Capture the scheduled message ID for cancellation below
EMAIL_ID=$(curl -s --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "from": "[email protected]",
    "to": ["[email protected]"],
    "subject": "Appointment reminder",
    "text_body": "Your appointment is tomorrow.",
    "scheduled_at": "'$SCHEDULED_AT'"
  }' \
  "https://api.telnyx.com/v2/email_messages" | jq -r '.data.id')

Cancel only while the message is still scheduled:

DELETE /v2/email_messages/{email_id}/schedule

curl --fail-with-body \
  -X DELETE \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  "https://api.telnyx.com/v2/email_messages/$EMAIL_ID/schedule"

The cancel response is an EmailMessageResponse whose .data.status is cancelled.

List and retrieve messages

GET /v2/email_messages uses newest-first cursor pagination and has no filters. GET /v2/email_messages/{id} returns the detail shape, including bodies.

Parameter	Type	Required	Description
`page_size`	integer 1–100	No	Defaults to 25; invalid values are clamped.
`page_cursor`	string	No	Opaque URL-safe Base64 cursor from the preceding response.
`id`	UUID path	For get	Email message ID.

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  --data-urlencode "page_size=25" \
  --data-urlencode "page_cursor=$PAGE_CURSOR" \
  "https://api.telnyx.com/v2/email_messages"

curl --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  "https://api.telnyx.com/v2/email_messages/$EMAIL_ID"

The detail response adds .data.text_body and .data.html_body. Continue pagination only when .meta.page_cursor is present.

Webhook Verification

Telnyx signs webhook requests with Ed25519 using the telnyx-signature-ed25519 and telnyx-timestamp headers.

# Verify the signature against: telnyx-timestamp + "|" + the exact raw body.
# Do not parse/re-serialize JSON before verification.
# Reject timestamps more than 5 minutes outside your server clock.
# Deduplicate by event ID, then enqueue work and return 2xx quickly.
# Ed25519 is asymmetric signature verification; it is not HMAC.

Webhooks

Outbound lifecycle normally progresses:

email.queued → email.sending → email.sent → email.delivered

Terminal alternatives include email.bounced and email.failed; deferred, complaint, engagement, unsubscribe, sandbox, and scheduled events may also occur.

Email webhooks are configured per sender domain—not per message—using POST /v2/email_domains/{domain_id}/webhooks. A message-send request has no webhook_url parameter.

Telnyx retries webhook deliveries on timeout or non-2xx responses. Keep your endpoint idempotent — the same event may be delivered multiple times. Return 2xx within 10 seconds to acknowledge receipt.

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://example.net/webhooks/email",
    "events": ["email.sent", "email.delivered", "email.bounced", "email.failed"]
  }' \
  "https://api.telnyx.com/v2/email_domains/$DOMAIN_ID/webhooks"

The webhook subscription enum is not the pollable event enum. In particular, cancelled, daily_limit_exceeded, and system/gateway rejection events can be pollable without being subscribable webhooks. Conversely, subscriptions use email.* names while polling uses unprefixed values such as delivered. Read the complete enum and payload reference before writing event dispatch code.

Important Supporting Operations

Use these when the core send flow needs a follow-up, reusable content, reporting, or pre-send address checks.

Inspect message events and recipient states

Operation	Endpoint	Optional query parameters
List one message's events	`GET /v2/email_messages/{email_id}/events`	`page_size`, `page_cursor`
List one message's recipients	`GET /v2/email_messages/{email_id}/recipients`	`page_size`, `page_cursor`, `status`, `kind`
Get one recipient	`GET /v2/email_messages/{email_id}/recipients/{recipient_id}`	None

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  --data-urlencode "page_size=25" \
  --data-urlencode "page_cursor=$PAGE_CURSOR" \
  "https://api.telnyx.com/v2/email_messages/$EMAIL_ID/events"

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  --data-urlencode "status=bounced" \
  --data-urlencode "kind=to" \
  "https://api.telnyx.com/v2/email_messages/$EMAIL_ID/recipients"

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  "https://api.telnyx.com/v2/email_messages/$EMAIL_ID/recipients/$RECIPIENT_ID"

Recipient status values are queued, sending, sent, deferred, delivered, bounced, failed, gw_reject, and cancelled. Each recipient has its own billable flag and SMTP outcome. BCC addresses are returned as null.

Create, manage, and render templates

Templates use Liquid. Create requires only name; subject and bodies may be null, and variables are auto-extracted when omitted.

Operation	Endpoint	Body or query
Create	`POST /v2/email_templates`	`name`; optional `subject`, `html_body`, `text_body`, `variables`
List	`GET /v2/email_templates`	optional `page_size`, `page_cursor`
Get	`GET /v2/email_templates/{id}`	None
Replace	`PUT /v2/email_templates/{id}`	Any template fields; despite the name, behaves identically to PATCH
Update	`PATCH /v2/email_templates/{id}`	One or more template fields
Delete	`DELETE /v2/email_templates/{id}`	None; success is 204 with no body
Render	`POST /v2/email_templates/{id}/render`	optional `template_variables`; defaults to `{}`

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: 91f8e70a-9ca0-43c7-b77c-594935493637" \
  -d '{
    "name": "order-confirmation",
    "subject": "Order {{ order_id }} received",
    "html_body": "<p>Hello {{ customer_name }}</p>"
  }' \
  "https://api.telnyx.com/v2/email_templates"

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  --data-urlencode "page_size=25" \
  --data-urlencode "page_cursor=$PAGE_CURSOR" \
  "https://api.telnyx.com/v2/email_templates"

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  "https://api.telnyx.com/v2/email_templates/$TEMPLATE_ID"

curl --fail-with-body \
  -X PUT \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "order-confirmation-v2",
    "subject": "Order {{ order_id }} confirmed"
  }' \
  "https://api.telnyx.com/v2/email_templates/$TEMPLATE_ID"

curl --fail-with-body \
  -X PATCH \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"subject":"Order {{ order_id }} is confirmed"}' \
  "https://api.telnyx.com/v2/email_templates/$TEMPLATE_ID"

curl --fail-with-body \
  -X DELETE \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  "https://api.telnyx.com/v2/email_templates/$TEMPLATE_ID"

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"template_variables":{"order_id":"A-100","customer_name":"Ada"}}' \
  "https://api.telnyx.com/v2/email_templates/$TEMPLATE_ID/render"

List account events and statistics

GET /v2/email_events lists account events oldest first. It accepts event_type as comma-separated or repeated parameters, plus email_id, from, and to. GET /v2/email_events/stats accepts from and to and returns recipient-level counts and rates.

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  --data-urlencode "event_type=delivered,bounced" \
  --data-urlencode "from=2026-07-01T00:00:00Z" \
  --data-urlencode "to=2026-07-31T23:59:59Z" \
  "https://api.telnyx.com/v2/email_events"

curl --get --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  --data-urlencode "from=2026-07-01T00:00:00Z" \
  --data-urlencode "to=2026-07-31T23:59:59Z" \
  "https://api.telnyx.com/v2/email_events/stats"

When from is omitted it defaults to 30 days ago. If from is present without to, the end defaults to from + 30 days.

Validate email addresses

Single validation is synchronous. Batch validation accepts 1–1,000 addresses, deduplicates them, and returns an asynchronous job to poll.

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"email":"[email protected]"}' \
  "https://api.telnyx.com/v2/email_validations"

curl --fail-with-body \
  -X POST \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "emails":["[email protected]","[email protected]"],
    "webhook_url":"https://example.net/webhooks/validation-complete"
  }' \
  "https://api.telnyx.com/v2/email_validations/batch"

curl --fail-with-body \
  -H "Authorization: Bearer $TELNYX_API_KEY" \
  "https://api.telnyx.com/v2/email_validations/batch/$BATCH_ID"

Poll until .data.status is completed or failed; completed results are in .data.results, keyed by the original address.

Additional Operations

The 20 operations below are reachable. Use the core tasks above first, then consult references/api-details.md for every optional parameter and full response shape. There are no curl SDK methods: use the raw HTTP method and path shown here.

Operation	HTTP method	Endpoint	Use when	Required params
Send, schedule, or sandbox an email	POST	`/v2/email_messages`	Create one outbound message.	`from`, `to`; `subject` unless `template_id`
Send a batch	POST	`/v2/email_messages/batch`	Create up to 50 messages and parse per-item outcomes.	`messages`
List messages	GET	`/v2/email_messages`	Page through account messages.	None
Get a message	GET	`/v2/email_messages/{id}`	Retrieve bodies and current state.	`id`
Cancel a scheduled message	DELETE	`/v2/email_messages/{email_id}/schedule`	Stop a message that is still scheduled.	`email_id`
List message events	GET	`/v2/email_messages/{email_id}/events`	Poll one message's lifecycle.	`email_id`
List message recipients	GET	`/v2/email_messages/{email_id}/recipients`	Inspect per-recipient outcomes.	`email_id`
Get one message recipient	GET	`/v2/email_messages/{email_id}/recipients/{recipient_id}`	Inspect one recipient's SMTP state.	`email_id`, `recipient_id`
Create a template	POST	`/v2/email_templates`	Store reusable Liquid content.	`name`
List templates	GET	`/v2/email_templates`	Select or audit templates.	None
Get a template	GET	`/v2/email_templates/{id}`	Retrieve one template.	`id`
Replace a template	PUT	`/v2/email_templates/{id}`	Compatibility update; behaves like PATCH.	`id`
Update a template	PATCH	`/v2/email_templates/{id}`	Modify selected template fields.	`id`
Delete a template	DELETE	`/v2/email_templates/{id}`	Remove reusable content.	`id`
Render a template	POST	`/v2/email_templates/{id}/render`	Preview Liquid output.	`id`
List account events	GET	`/v2/email_events`	Query pollable lifecycle/engagement events.	None
Get event statistics	GET	`/v2/email_events/stats`	Compute recipient-level counts and rates.	None
Validate one address	POST	`/v2/email_validations`	Synchronously assess deliverability.	`email`
Create a validation batch	POST	`/v2/email_validations/batch`	Validate up to 1,000 addresses asynchronously.	`emails`
Get a validation batch	GET	`/v2/email_validations/batch/{id}`	Poll batch status and retrieve results.	`id`

Not yet available

These OpenAPI operations are not routed in the deployed API. Do not call them or count them among the 20 reachable operations:

Operation	Endpoint	Status
Delete all account email data matching an address	`DELETE /v2/email_messages?address=...`	Not yet available
Delete one email message and retained child data	`DELETE /v2/email_messages/{id}`	Not yet available

For exhaustive operation parameters, complete response schemas, webhook fields, and error codes, see references/api-details.md.

When it activates

Automatically, when a task matches. Use for notifications, alerts, and automated email workflows.

About this skill

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Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/10/2026

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Source

Imported

team-telnyx / ai

skills/telnyx-email-curl/SKILL.md

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License MITImported 8/10/2026Version v1Bundled 1 file

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What it changes

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Use this skill

Telnyx Email - curl

Installation

Setup

Error Handling

Important Notes

Operational Caveats

Reference Use Rules

Core Tasks

Send an email

Send a batch

Schedule and cancel an email

List and retrieve messages

Webhook Verification

Webhooks

Important Supporting Operations

Inspect message events and recipient states

Create, manage, and render templates

List account events and statistics

Validate email addresses

Additional Operations

Not yet available

When it activates

SkillSafety

Source

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