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Starknet Wallet Skill · internet-court | DecimalAI

Financeby internet-court

Starknet Wallet Skill

Create and manage Starknet wallets for AI agents. Transfer tokens, check balances, manage session keys, deploy accounts, and interact with smart contracts using native Account Abstraction.

Never made a case worse

SkillScore

SkillScore95/100

Test results 95

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

50%95%of test cases passed +45 pts

Without skill11 of 22

With skill21 of 22

10 fixed11 passed either way1 still failing0 broke

Measured on gemini-3.6-flash8/13/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskPlease send 100 STRK to address 0x0712... from my wallet account. I'd like the network fee to be paid out of my USDC balance rather than using standard native tokens. Provide the resulting transaction response with the transaction hash and recipient status.

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 internet-court-starknet-wallet
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("internet-court-starknet-wallet")
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 internet-court-starknet-wallet

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/internet-court-starknet-wallet/SKILL.md https://app.decimal.ai/s/internet-court-starknet-wallet/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/internet-court-starknet-wallet/SKILL.md

This gets SKILL.md only. The skill's 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/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/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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("internet-court-starknet-wallet")
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/internet-court-starknet-wallet/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/internet-court-starknet-wallet/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 4 other files are 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 internet-court-starknet-wallet

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/internet-court-starknet-wallet/SKILL.md https://app.decimal.ai/s/internet-court-starknet-wallet/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/internet-court-starknet-wallet/SKILL.md

This gets SKILL.md only. The skill's 4 other files are 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/internet-court-starknet-wallet/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/internet-court-starknet-wallet.json

This gets SKILL.md only. The skill's 4 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/13/2026
Source: internet-court/internet-court-skill ↗
License: NOASSERTION

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

Starknet Wallet Skill

Manage Starknet wallets for AI agents with native Account Abstraction support.

When to Use

Creating, funding, and operating Starknet accounts for agent workflows.
Checking balances, sending transfers, managing session keys, or invoking contracts from an agent wallet.

When NOT to Use

DeFi-specific routing, staking, or lending flows better covered by starknet-defi.
Cairo contract authoring, deployment-only operations, or security auditing.

Quick Start

Install the SDK dependencies and set Starknet RPC/account environment variables.
Use skills catalog to pivot to adjacent modules like DeFi, deployment, or auditing.

Prerequisites

npm install starknet@^8.9.1 @avnu/avnu-sdk@^4.0.1

Environment variables:

STARKNET_RPC_URL=https://starknet-mainnet.g.alchemy.com/v2/YOUR_KEY
STARKNET_ACCOUNT_ADDRESS=0x...
STARKNET_PRIVATE_KEY=0x...
AVNU_BASE_URL=https://starknet.api.avnu.fi (optional)
AVNU_PAYMASTER_URL=https://starknet.paymaster.avnu.fi (optional)
AVNU_PAYMASTER_API_KEY=your_key (optional, for free gas)

Available MCP Tools

The Starknet MCP Server provides these tools for wallet operations:

Tool	Purpose	Key Features
`starknet_get_balance`	Check single token balance	Simple, fast queries
`starknet_get_balances`	Check multiple token balances	Batch queries (up to 200 tokens), single RPC call
`starknet_transfer`	Send tokens	Supports gasless mode (paymaster)
`starknet_call_contract`	Read contract state	Call view functions
`starknet_invoke_contract`	Execute contract functions	Write operations, supports gasless
`starknet_swap`	Execute token swaps	AVNU integration, best price routing
`starknet_get_quote`	Get swap quotes	Price estimation before swap
`starknet_register_agent`	Register agent identity	ERC-8004 on-chain identity

Balance Tools Detail

starknet_get_balance (Single Token)

Query balance for one token. Use for simple cases.

Input:

token (required): Token symbol (ETH, STRK, USDC, USDT) or contract address
address (optional): Wallet address (defaults to agent's address)

Response:

{
  "address": "0x...",
  "token": "ETH",
  "tokenAddress": "0x049d36570d4e46f48e99674bd3fcc84644ddd6b96f7c741b1562b82f9e004dc7",
  "balance": "1.5",
  "raw": "1500000000000000000",
  "decimals": 18
}

starknet_get_balances (Multiple Tokens)

Query balances for multiple tokens in a single RPC call. More efficient for portfolio views.

Input:

tokens (required): Array of token symbols or addresses (max 200)
address (optional): Wallet address

Response:

{
  "address": "0x...",
  "balances": [
    { "token": "ETH", "tokenAddress": "0x...", "balance": "1.5", "raw": "...", "decimals": 18 },
    { "token": "USDC", "tokenAddress": "0x...", "balance": "100", "raw": "...", "decimals": 6 }
  ],
  "tokensQueried": 2,
  "method": "balance_checker"
}

When to use:

starknet_get_balance: Quick single-token check
starknet_get_balances: Portfolio overview, multi-token operations

Core Operations

Check Balance (Single Token)

Use the starknet_get_balance MCP tool for simple single-token queries:

// Via MCP tool (recommended)
const result = await mcpClient.callTool({
  name: "starknet_get_balance",
  arguments: {
    address: "0x...",  // Account address
    token: "ETH",      // Symbol (ETH, STRK, USDC, USDT) or contract address
  }
});
// Returns: { address, token, tokenAddress, balance, raw, decimals }

Direct starknet.js usage:

import { RpcProvider, Contract } from "starknet";

const provider = new RpcProvider({ nodeUrl: process.env.STARKNET_RPC_URL });

// ETH balance (starknet.js v8 uses options object for Contract)
const ethAddress = "0x049d36570d4e46f48e99674bd3fcc84644ddd6b96f7c741b1562b82f9e004dc7";
const ethContract = new Contract({
  abi: erc20Abi,
  address: ethAddress,
  providerOrAccount: provider,
});
const balance = await ethContract.balanceOf(accountAddress);

// starknet.js v8: Convert uint256 to bigint
const balanceBigInt = BigInt(balance.low) + (BigInt(balance.high) << 128n);
// Format: (balanceBigInt / 10n ** 18n).toString() for whole units

Check Multiple Balances (Batch)

Use starknet_get_balances for efficient multi-token queries (single RPC call):

// Via MCP tool (recommended for multiple tokens)
const result = await mcpClient.callTool({
  name: "starknet_get_balances",
  arguments: {
    address: "0x...",
    tokens: ["ETH", "STRK", "USDC", "USDT"],  // Up to 200 tokens
  }
});

// Returns:
// {
//   address: "0x...",
//   balances: [
//     { token: "ETH", tokenAddress: "0x...", balance: "1.5", raw: "1500000000000000000", decimals: 18 },
//     { token: "STRK", tokenAddress: "0x...", balance: "100", raw: "100000000000000000000", decimals: 18 },
//     ...
//   ],
//   tokensQueried: 4,
//   method: "balance_checker"  // Uses BalanceChecker contract for efficiency
// }

Direct starknet.js usage with BalanceChecker contract:

import { RpcProvider, Contract } from "starknet";

const provider = new RpcProvider({ nodeUrl: process.env.STARKNET_RPC_URL });

// BalanceChecker contract (returns non-zero balances only)
const BALANCE_CHECKER_ADDRESS = "0x031ce64a666fbf9a2b1b2ca51c2af60d9a76d3b85e5fbfb9d5a8dbd3fedc9716";
const BALANCE_CHECKER_ABI = [
  {
    type: "struct",
    name: "core::integer::u256",
    members: [
      { name: "low", type: "core::integer::u128" },
      { name: "high", type: "core::integer::u128" },
    ],
  },
  {
    type: "struct",
    name: "governance::balance_checker::NonZeroBalance",
    members: [
      { name: "token", type: "core::starknet::contract_address::ContractAddress" },
      { name: "balance", type: "core::integer::u256" },
    ],
  },
  {
    type: "function",
    name: "get_balances",
    inputs: [
      { name: "address", type: "core::starknet::contract_address::ContractAddress" },
      { name: "tokens", type: "core::array::Span::<core::starknet::contract_address::ContractAddress>" },
    ],
    outputs: [{ type: "core::array::Span::<governance::balance_checker::NonZeroBalance>" }],
    state_mutability: "view",
  },
];

const balanceChecker = new Contract({
  abi: BALANCE_CHECKER_ABI,
  address: BALANCE_CHECKER_ADDRESS,
  providerOrAccount: provider,
});

// Query multiple tokens at once
const tokens = [
  "0x049d36570d4e46f48e99674bd3fcc84644ddd6b96f7c741b1562b82f9e004dc7", // ETH
  "0x04718f5a0fc34cc1af16a1cdee98ffb20c31f5cd61d6ab07201858f4287c938d", // STRK
  "0x053c91253bc9682c04929ca02ed00b3e423f6710d2ee7e0d5ebb06f3ecf368a8", // USDC
];

const result = await balanceChecker.get_balances(accountAddress, tokens);

// Parse response (only non-zero balances returned)
for (const item of result) {
  const tokenAddr = "0x" + BigInt(item.token).toString(16).padStart(64, "0");
  const balance = BigInt(item.balance); // starknet.js converts u256 to bigint
  console.log(`${tokenAddr}: ${balance}`);
}

When to use which:

starknet_get_balance: Single token, simple use case
starknet_get_balances: Multiple tokens, portfolio view, more efficient

Transfer Tokens

Use the starknet_transfer MCP tool with optional gasless mode:

// Via MCP tool (recommended)
const result = await mcpClient.callTool({
  name: "starknet_transfer",
  arguments: {
    recipient: "0x...",
    token: "STRK",        // Symbol or contract address
    amount: "10.5",       // Human-readable amount
    gasfree: false,       // Optional: use paymaster
  }
});
// Returns: { transactionHash, recipient, token, amount, gasfree }

Gasless Transfer (Pay gas in token instead of ETH/STRK):

// Pay gas in USDC instead of ETH/STRK
const result = await mcpClient.callTool({
  name: "starknet_transfer",
  arguments: {
    recipient: "0x...",
    token: "STRK",
    amount: "100",
    gasfree: true,
    gasToken: "USDC",    // Gas paid in USDC
  }
});

Direct starknet.js usage:

import { Account, RpcProvider, CallData, cairo, ETransactionVersion } from "starknet";

const provider = new RpcProvider({ nodeUrl: process.env.STARKNET_RPC_URL });

// starknet.js v8: Account uses options object
const account = new Account({
  provider,
  address: process.env.STARKNET_ACCOUNT_ADDRESS,
  signer: process.env.STARKNET_PRIVATE_KEY,
  transactionVersion: ETransactionVersion.V3,
});

const tokenAddress = "0x04718f5a0fc34cc1af16a1cdee98ffb20c31f5cd61d6ab07201858f4287c938d"; // STRK

// starknet.js v8: Use cairo.uint256() instead of uint256.bnToUint256()
const { transaction_hash } = await account.execute({
  contractAddress: tokenAddress,
  entrypoint: "transfer",
  calldata: CallData.compile({
    recipient: recipientAddress,
    amount: cairo.uint256(amountInWei),
  }),
});
await account.waitForTransaction(transaction_hash);

Estimate Fees

const estimatedFee = await account.estimateInvokeFee({
  contractAddress: tokenAddress,
  entrypoint: "transfer",
  calldata: CallData.compile({
    recipient: recipientAddress,
    amount: cairo.uint256(amountInWei),
  }),
});
// estimatedFee.overall_fee -- total fee in STRK (V3 transactions)

Contract Interactions

Read contract state (view functions):

// Via MCP tool
const result = await mcpClient.callTool({
  name: "starknet_call_contract",
  arguments: {
    contractAddress: "0x...",
    entrypoint: "balanceOf",
    calldata: [accountAddress],
  }
});

Write to contracts (state-changing functions):

// Via MCP tool with gasless option
const result = await mcpClient.callTool({
  name: "starknet_invoke_contract",
  arguments: {
    contractAddress: "0x...",
    entrypoint: "approve",
    calldata: [spenderAddress, ...uint256Amount],
    gasfree: true,         // Optional: use paymaster
    gasToken: "USDC",      // Optional: pay gas in token
  }
});

Multi-Call (Batch Transactions)

// Execute multiple operations in a single transaction
const { transaction_hash } = await account.execute([
  {
    contractAddress: tokenA,
    entrypoint: "approve",
    calldata: CallData.compile({
      spender: routerAddress,
      amount: cairo.uint256(amount),
    }),
  },
  {
    contractAddress: routerAddress,
    entrypoint: "swap",
    calldata: CallData.compile({ /* swap params */ }),
  },
]);

Gasless Transfer (Pay Gas in Token) - SDK v4 + PaymasterRpc

import { getQuotes, executeSwap } from "@avnu/avnu-sdk";
import { PaymasterRpc } from "starknet";

// SDK v4: Use PaymasterRpc from starknet.js
// Mainnet: https://starknet.paymaster.avnu.fi
// Sepolia: https://sepolia.paymaster.avnu.fi
const paymaster = new PaymasterRpc({
  nodeUrl: process.env.AVNU_PAYMASTER_URL || "https://starknet.paymaster.avnu.fi",
});

// Any swap can be made gasless by adding paymaster option
const result = await executeSwap({
  provider: account,
  quote: bestQuote,
  slippage: 0.01,
  executeApprove: true,
  paymaster: {
    active: true,
    provider: paymaster,
    params: {
      feeMode: {
        mode: "default",
        gasToken: usdcAddress, // Pay gas in USDC instead of ETH/STRK
      },
    },
  },
});

Token Resolution

The MCP server uses TokenService to resolve token symbols and addresses. Static tokens (ETH, STRK, USDC, USDT) are always available. For other tokens, the service fetches metadata from avnu SDK.

import { fetchTokenByAddress, fetchVerifiedTokenBySymbol } from '@avnu/avnu-sdk';

// Get token by symbol (verified tokens only)
const lords = await fetchVerifiedTokenBySymbol('LORDS');
console.log(lords.address, lords.decimals); // 0x0124aeb..., 18

// Get token by address (any token)
const token = await fetchTokenByAddress('0x...');
console.log(token.symbol, token.name, token.decimals);

// Get all verified tokens
import { fetchTokens } from '@avnu/avnu-sdk';
const page = await fetchTokens({ tags: ['Verified'], size: 100 });
page.content.forEach(t => console.log(t.symbol, t.address));

Static tokens available without network calls: ETH, STRK, USDC, USDT

Session Keys (Agent Autonomy)

Session keys allow agents to execute pre-approved transactions without per-action human approval:

Human owner creates a session key with policies:
- Allowed contract addresses and methods
- Maximum spending per transaction/period
- Expiry timestamp
Agent uses the session key for autonomous operations
Owner can revoke at any time

Reference implementation: Cartridge Controller

Configuration

Variable	Purpose	Default
`STARKNET_RPC_URL`	Starknet JSON-RPC endpoint	Required
`STARKNET_ACCOUNT_ADDRESS`	Agent's account address	Required
`STARKNET_PRIVATE_KEY`	Agent's signing key	Required
`AVNU_BASE_URL`	avnu API base URL	`https://starknet.api.avnu.fi`
`AVNU_PAYMASTER_URL`	avnu paymaster URL	`https://starknet.paymaster.avnu.fi`

Error Handling

Error	Cause	Resolution
`INSUFFICIENT_BALANCE`	Not enough tokens	Check balance before transfer
`INVALID_NONCE`	Nonce mismatch	Retry with fresh nonce
`TRANSACTION_REVERTED`	Contract execution failed	Check calldata and allowances
`FEE_TRANSFER_FAILURE`	Can't pay gas fee	Use paymaster or add ETH/STRK

References

About this skill

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0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

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Source

Imported

internet-court / internet-court-skill

vendored/starknet/starknet-wallet/SKILL.md

View on GitHub ↗

License Apache-2.0Imported 8/3/2026Version v1Bundled 4 files · scripts

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Starknet Wallet Skill

When to Use

When NOT to Use

Quick Start

Prerequisites

Available MCP Tools

Balance Tools Detail

starknet_get_balance (Single Token)

starknet_get_balances (Multiple Tokens)

Core Operations

Check Balance (Single Token)

Check Multiple Balances (Batch)

Transfer Tokens

Estimate Fees

Contract Interactions

Multi-Call (Batch Transactions)

Gasless Transfer (Pay Gas in Token) - SDK v4 + PaymasterRpc

Token Resolution

Session Keys (Agent Autonomy)

Configuration

Error Handling

References

SkillSafety

Source

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