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starknet.js v9.x SDK · internet-court | DecimalAI

Codingby internet-court

starknet.js v9.x SDK

Reference for building Starknet applications using starknet.js v9.x SDK, including contract interaction, account management, transaction handling, fee estimation, wallet integration, and paymaster flows.

Never made a case worse

SkillScore

SkillScore91/100

Test results 91

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

27%91%of test cases passed +64 pts

Without skill6 of 22

With skill20 of 22

14 fixed6 passed either way2 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 taskWhen polling transaction receipts after calling waitForTransaction, what methods on the receipt object check whether a transaction succeeded, reverted, or was rejected?

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-js
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-js")
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-js

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

Copy SKILL.md

Save it in your project, as

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

This gets SKILL.md only. The skill's 5 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-js

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-js")
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-js/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-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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-js")
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-js/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-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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-js")
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-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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-js")
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-js/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-js/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 5 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-js

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-js")
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-js/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/internet-court-starknet-js/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 5 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-js

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

Copy SKILL.md

Save it in your project, as

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

This gets SKILL.md only. The skill's 5 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-js/SKILL.md

Read the summary as JSON

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

This gets SKILL.md only. The skill's 5 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.js v9.x SDK

Related modules: skills catalog.

When to Use

Building Starknet apps with provider, account, contract, wallet, or paymaster flows.

When NOT to Use

Cairo contract authoring, deployment-only runbooks, or security audits.

Quick Start

npm install starknet

Minimal setup to read from Starknet:

import { RpcProvider, Contract } from 'starknet';

const provider = await RpcProvider.create({ nodeUrl: 'https://rpc.starknet.lava.build' });
const contract = new Contract(abi, contractAddress, provider);
const result = await contract.get_balance();

Core Architecture

Provider -> Account -> Contract
   |          |          |
Network   Identity   Interaction

Provider: Read-only network connection (RpcProvider)
Account: Extends Provider with signing and transaction capabilities
Contract: Type-safe interface to deployed contracts

Use Provider for read operations, Account for write operations.

Provider Setup

import { RpcProvider } from 'starknet';

// Recommended: Auto-detect RPC spec version
const provider = await RpcProvider.create({
  nodeUrl: 'https://rpc.starknet.lava.build'
});

Networks:

Mainnet: https://rpc.starknet.lava.build
Sepolia: https://rpc.starknet-testnet.lava.build

Key Methods:

const chainId = await provider.getChainId();
const block = await provider.getBlock('latest');
const nonce = await provider.getNonceForAddress(accountAddress);
await provider.waitForTransaction(txHash);

// Read storage directly
const value = await provider.getStorageAt(contractAddress, storageKey);

Account Management

Account Creation (4 Steps)

Step 1: Compute address

import { hash, ec, encode, CallData } from 'starknet';

// IMPORTANT: `stark.randomAddress()` returns an address-like random felt and is NOT a private key.
// Use a real stark curve private key generator.
const privateKey = '0x' + encode.buf2hex(ec.starkCurve.utils.randomPrivateKey());
const publicKey = ec.starkCurve.getStarkKey(privateKey);

// NOTE: account class hashes are network/account-type dependent.
// Treat this as an example only (verify the correct class hash for your setup).
const classHash = '0x540d7f5ec7ecf317e68d48564934cb99259781b1ee3cedbbc37ec5337f8e688'; // example

const constructorCalldata = CallData.compile({ publicKey });
const address = hash.calculateContractAddressFromHash(publicKey, classHash, constructorCalldata, 0);

Step 2: Fund the address with STRK before deployment.

Step 3: Deploy

import { Account } from 'starknet';

// NOTE: Account constructor signature varies across starknet.js versions.
// If this doesn't typecheck for your version, refer to the official docs.
const account = new Account({ provider, address, signer: privateKey, cairoVersion: '1' });
const { transaction_hash } = await account.deployAccount({
  classHash,
  constructorCalldata,
  addressSalt: publicKey
});
await provider.waitForTransaction(transaction_hash);

Step 4: Use the account for transactions.

Connect to Existing Account

const account = new Account({
  provider,
  address: '0x123...',
  signer: privateKey,
  cairoVersion: '1'  // Optional, auto-detected if omitted
});

Contract Interaction

Connect to Contract

import { Contract } from 'starknet';

const contract = new Contract(abi, contractAddress, provider);  // Read-only
const writeContract = new Contract(abi, contractAddress, account);   // Read-write

Typed Contract (Type-Safe)

// Get full TypeScript autocomplete and type checking from ABI
const typedContract = contract.typedv2(abi);
const balance = await typedContract.balanceOf(userAddress);

Read State

const balance = await contract.get_balance();
const userBalance = await contract.balanceOf(userAddress);

Write (Execute)

const tx = await contract.increase_balance(100);
await provider.waitForTransaction(tx.transaction_hash);

Multicall (Batch Transactions)

import { CallData, cairo } from 'starknet';

const calls = [
  {
    contractAddress: tokenAddress,
    entrypoint: 'approve',
    calldata: CallData.compile({ spender: bridgeAddress, amount: cairo.uint256(1000n) })
  },
  {
    contractAddress: bridgeAddress,
    entrypoint: 'deposit',
    calldata: CallData.compile({ amount: cairo.uint256(1000n) })
  }
];

const tx = await account.execute(calls);

Using populate() for type-safety:

const approveCall = tokenContract.populate('approve', {
  spender: bridgeAddress,
  amount: cairo.uint256(1000n)
});
const depositCall = bridgeContract.populate('deposit', { amount: cairo.uint256(1000n) });
const tx = await account.execute([approveCall, depositCall]);

Parse Events

const receipt = await provider.getTransactionReceipt(txHash);
const events = contract.parseEvents(receipt);
const transferEvents = contract.parseEvents(receipt, 'Transfer');

Transaction Simulation

Simulate before executing to catch reverts and inspect state changes:

const simResult = await account.simulateTransaction(
  [{ type: 'INVOKE', payload: calls }],
  { skipValidate: false }
);

console.log('Fee estimate:', simResult[0].fee_estimation);
console.log('Trace:', simResult[0].transaction_trace);

// Check state changes before execution
const trace = simResult[0].transaction_trace;
if (trace?.state_diff) {
  console.log('Storage changes:', trace.state_diff.storage_diffs);
}

Fee Estimation

const fee = await account.estimateInvokeFee(calls);
console.log({
  overallFee: fee.overall_fee,
  resourceBounds: fee.resourceBounds  // V3: l1_gas, l2_gas, l1_data_gas
});

Execute with custom bounds:

const tx = await account.execute(calls, {
  resourceBounds: {
    l1_gas: { amount: '0x2000', price: '0x1000000000' },
    l2_gas: { amount: '0x0', price: '0x0' },
    l1_data_gas: { amount: '0x1000', price: '0x1000000000' }
  }
});

With priority tip:

const tipStats = await provider.getEstimateTip();
const tx = await account.execute(calls, { tip: tipStats.percentile_75 });

Transaction Receipt Handling

const receipt = await provider.waitForTransaction(txHash);

// Status check helpers
if (receipt.isSuccess()) {
  console.log('Transaction succeeded');
} else if (receipt.isReverted()) {
  console.log('Reverted:', receipt.revert_reason);
} else if (receipt.isRejected()) {
  console.log('Rejected');
} else if (receipt.isError()) {
  console.log('Error');
}

Wallet Integration

Connect to browser wallets (ArgentX, Braavos):

import { connect } from '@starknet-io/get-starknet';
import { WalletAccount } from 'starknet';

const selectedWallet = await connect({ modalMode: 'alwaysAsk' });
const walletAccount = await WalletAccount.connect(
  { nodeUrl: 'https://rpc.starknet.lava.build' },
  selectedWallet
);

// Use like regular Account
const tx = await walletAccount.execute(calls);

// Event handlers
walletAccount.onAccountChange((accounts) => console.log('New account:', accounts[0]));
walletAccount.onNetworkChanged((chainId) => console.log('Network changed:', chainId));

Paymaster (Gas Sponsorship)

Setup paymaster for sponsored or alternative gas token transactions:

import { PaymasterRpc, Account } from 'starknet';

const paymaster = new PaymasterRpc({ nodeUrl: 'https://sepolia.paymaster.avnu.fi' });
const account = new Account({ provider, address, signer: privateKey, paymaster });

Sponsored (dApp pays gas):

const tx = await account.executePaymasterTransaction(calls, { feeMode: { mode: 'sponsored' } });

Alternative token (e.g., USDC):

const tokens = await account.paymaster.getSupportedTokens();
const feeDetails = { feeMode: { mode: 'default', gasToken: USDC_ADDRESS } };
const estimate = await account.estimatePaymasterTransactionFee(calls, feeDetails);
const tx = await account.executePaymasterTransaction(calls, feeDetails, estimate.suggested_max_fee_in_gas_token);

Message Signing (SNIP-12)

const typedData = {
  types: {
    StarknetDomain: [
      { name: 'name', type: 'shortstring' },
      { name: 'version', type: 'shortstring' },
      { name: 'chainId', type: 'shortstring' },
      { name: 'revision', type: 'shortstring' }
    ],
    Message: [{ name: 'content', type: 'shortstring' }]
  },
  primaryType: 'Message',
  domain: { name: 'MyDapp', version: '1', chainId: 'SN_SEPOLIA', revision: '1' },
  message: { content: 'Hello Starknet' }
};

const signature = await account.signMessage(typedData);
const msgHash = await account.hashMessage(typedData);
const isValid = ec.starkCurve.verify(signature, msgHash, publicKey);

CallData & Cairo Types

import { CallData, cairo, CairoCustomEnum, CairoOption, CairoOptionVariant } from 'starknet';

// Compile with ABI
const calldata = new CallData(abi);
const compiled = calldata.compile('transfer', { recipient: '0x...', amount: cairo.uint256(1000n) });

// Cairo type helpers - always use BigInt (n suffix) for token amounts
cairo.uint256(1000n)          // { low, high } - ALWAYS use BigInt for precision
cairo.felt252(1000)           // BigInt
cairo.felt('0x123')           // hex to felt
cairo.bool(true)              // Cairo bool
cairo.byteArray('Hello')      // ByteArray for long strings

// Short strings (<= 31 chars)
import { shortString } from 'starknet';
shortString.encodeShortString('hello')  // felt252
shortString.decodeShortString('0x...')  // 'hello'

// Enums and Options
const myEnum = new CairoCustomEnum({ Variant1: { value: 123 } });
const some = new CairoOption(CairoOptionVariant.Some, value);

Important: Always use BigInt (e.g., 1000n) for token amounts and balances. Never use Number() or parseFloat() on wei values -- JavaScript numbers lose precision above 2^53.

ERC-20 Token Operations

const erc20 = new Contract(erc20Abi, tokenAddress, account);

// Read balance (returns BigInt - do NOT convert with Number())
const balance = await erc20.balanceOf(account.address);
console.log('Balance (wei):', balance.toString());

// Transfer (use BigInt for amount)
const amount = cairo.uint256(1000000000000000000n); // 1 token (18 decimals)
const tx = await erc20.transfer(recipientAddress, amount);
await provider.waitForTransaction(tx.transaction_hash);

// Approve + transferFrom pattern
await erc20.approve(spenderAddress, cairo.uint256(amount));

Utility Functions

import { stark, ec, encode, num, hash } from 'starknet';

// Key generation
const privateKey = '0x' + encode.buf2hex(ec.starkCurve.utils.randomPrivateKey());
const publicKey = ec.starkCurve.getStarkKey(privateKey);

// Number conversions
num.toHex(123);           // '0x7b'
num.toBigInt('0x7b');     // 123n

// Hashing
hash.getSelectorFromName('transfer');
hash.calculateContractAddressFromHash(salt, classHash, calldata, deployer);

Contract Deployment

// Deploy via UDC
const { transaction_hash, contract_address } = await account.deploy({
  classHash: '0x...',
  constructorCalldata: CallData.compile({ owner: account.address }),
  salt: stark.randomAddress(), // random felt252 salt (not a private key)
  unique: true
});

// Declare first, then deploy
const declareResponse = await account.declare({
  contract: compiledSierra,
  casm: compiledCasm
});
await provider.waitForTransaction(declareResponse.transaction_hash);

const deployResponse = await account.deploy({
  classHash: declareResponse.class_hash,
  constructorCalldata: CallData.compile({ owner: account.address })
});

// Or combined
const result = await account.declareAndDeploy({
  contract: compiledContract,
  casm: compiledCasm,
  constructorCalldata: CallData.compile({ owner: account.address })
});

Outside Execution (SNIP-9)

Execute transactions on behalf of another account (gasless/delegated):

const version = await account.getSnip9Version();  // 'V1' | 'V2' | 'UNSUPPORTED'

const outsideTransaction = await account.getOutsideTransaction(
  { caller: executorAddress, execute_after: now, execute_before: now + 3600 },
  calls,
  'V2'
);

// Executor submits the pre-signed transaction
const result = await executorAccount.executeFromOutside(outsideTransaction);

Error Handling

import { LibraryError, RpcError } from 'starknet';

try {
  const tx = await account.execute(calls);
} catch (error) {
  if (error instanceof RpcError) {
    console.error('RPC error:', error.code, error.message);
  } else if (error instanceof LibraryError) {
    console.error('Library error:', error.message);
  }
}

Logging & Configuration

import { config, setLogLevel } from 'starknet';

// Global config
config.set('transactionVersion', '0x3');
config.get('transactionVersion');

// Logging
setLogLevel('DEBUG');  // ERROR | WARN | INFO | DEBUG

About this skill

Automatic

Coding pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

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

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

internet-court / internet-court-skill

vendored/starknet/starknet-js/SKILL.md

View on GitHub ↗

License Apache-2.0Imported 8/3/2026Version v1Bundled 5 files · scripts

Illustrative Want to see what internet-court/starknet-js would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

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SkillScore

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What it changes

Track record

Use this skill

starknet.js v9.x SDK

When to Use

When NOT to Use

Quick Start

Core Architecture

Provider Setup

Account Management

Account Creation (4 Steps)

Connect to Existing Account

Contract Interaction

Connect to Contract

Typed Contract (Type-Safe)

Read State

Write (Execute)

Multicall (Batch Transactions)

Parse Events

Transaction Simulation

Fee Estimation

Transaction Receipt Handling

Wallet Integration

Paymaster (Gas Sponsorship)

Message Signing (SNIP-12)

CallData & Cairo Types

ERC-20 Token Operations

Utility Functions

Contract Deployment

Outside Execution (SNIP-9)

Error Handling

Logging & Configuration

SkillSafety

Source

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