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Error Handling Patterns · valec3 | DecimalAI

Codingby valec3

Error Handling Patterns

Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications.

SkillScore

SkillScore94/100

Test results 91 · Live runs 98

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

82%91%of test cases passed +9 pts

Without skill18 of 22

With skill20 of 22

3 fixed17 passed either way1 still failing1 broke

Measured on gemini-3.6-flash8/3/2026v1

Track record

Agent runs: 67; All time
Forks: 1

See one task, with and without the skill

One test taskWrite a Rust function that looks up a user by ID returning Option<User>, and convert that lookup into a Result<u32, AppError> extracting the user's age or returning a NotFound error.

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 valec3-error-handling-patterns
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("valec3-error-handling-patterns")
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 valec3-error-handling-patterns

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/valec3-error-handling-patterns/SKILL.md https://app.decimal.ai/s/valec3-error-handling-patterns/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/valec3-error-handling-patterns/SKILL.md

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

Other ways to add it

Claude Code docs

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

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

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

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

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

Other ways to add it

Claude Agent SDK docs

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

Install

pip install "decimalai[openai-agents]"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

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

Other ways to add it

OpenAI Agents docs

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

Install

pip install "decimalai[openai]"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

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

Other ways to add it

OpenAI SDK docs

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

Install

pip install "decimalai[anthropic]"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

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

Other ways to add it

Anthropic docs

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

Install

pip install "decimalai[google-genai]"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/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/valec3-error-handling-patterns/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

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

Other ways to add it

Gemini API docs

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

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

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

Other ways to add it

LangChain docs

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

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

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

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

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

Other ways to add it

CrewAI docs

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

Install

pip install "decimalai[adk]"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

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

Other ways to add it

Google ADK docs

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

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

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

Other ways to add it

Pydantic AI docs

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

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

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

Other ways to add it

Deep Agents docs

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

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

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

Other ways to add it

Microsoft Agent Framework docs

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

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add valec3-error-handling-patterns

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("valec3-error-handling-patterns")
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/valec3-error-handling-patterns/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/valec3-error-handling-patterns/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

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

Other ways to add it

Strands docs

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

pip install "decimalai>=0.15"
decimalai skills add valec3-error-handling-patterns

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/valec3-error-handling-patterns/SKILL.md https://app.decimal.ai/s/valec3-error-handling-patterns/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/valec3-error-handling-patterns/SKILL.md

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

Other ways to add it

Cursor and other editors docs

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

Get the file

curl -fsSL https://app.decimal.ai/s/valec3-error-handling-patterns/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/valec3-error-handling-patterns.json

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

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/3/2026
Source: valec3/agents.skills.md ↗
License: Not recorded

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

Error Handling Patterns

Build resilient applications with robust error handling strategies that gracefully handle failures and provide excellent debugging experiences.

When to Use This Skill

Implementing error handling in new features
Designing error-resilient APIs
Debugging production issues
Improving application reliability
Creating better error messages for users and developers
Implementing retry and circuit breaker patterns
Handling async/concurrent errors
Building fault-tolerant distributed systems

Core Concepts

1. Error Handling Philosophies

Exceptions vs Result Types:

Exceptions: Traditional try-catch, disrupts control flow
Result Types: Explicit success/failure, functional approach
Error Codes: C-style, requires discipline
Option/Maybe Types: For nullable values

When to Use Each:

Exceptions: Unexpected errors, exceptional conditions
Result Types: Expected errors, validation failures
Panics/Crashes: Unrecoverable errors, programming bugs

2. Error Categories

Recoverable Errors:

Network timeouts
Missing files
Invalid user input
API rate limits

Unrecoverable Errors:

Out of memory
Stack overflow
Programming bugs (null pointer, etc.)

Language-Specific Patterns

Python Error Handling

Custom Exception Hierarchy:

class ApplicationError(Exception):
    """Base exception for all application errors."""
    def __init__(self, message: str, code: str = None, details: dict = None):
        super().__init__(message)
        self.code = code
        self.details = details or {}
        self.timestamp = datetime.utcnow()

class ValidationError(ApplicationError):
    """Raised when validation fails."""
    pass

class NotFoundError(ApplicationError):
    """Raised when resource not found."""
    pass

class ExternalServiceError(ApplicationError):
    """Raised when external service fails."""
    def __init__(self, message: str, service: str, **kwargs):
        super().__init__(message, **kwargs)
        self.service = service

# Usage
def get_user(user_id: str) -> User:
    user = db.query(User).filter_by(id=user_id).first()
    if not user:
        raise NotFoundError(
            f"User not found",
            code="USER_NOT_FOUND",
            details={"user_id": user_id}
        )
    return user

Context Managers for Cleanup:

from contextlib import contextmanager

@contextmanager
def database_transaction(session):
    """Ensure transaction is committed or rolled back."""
    try:
        yield session
        session.commit()
    except Exception as e:
        session.rollback()
        raise
    finally:
        session.close()

# Usage
with database_transaction(db.session) as session:
    user = User(name="Alice")
    session.add(user)
    # Automatic commit or rollback

Retry with Exponential Backoff:

import time
from functools import wraps
from typing import TypeVar, Callable

T = TypeVar('T')

def retry(
    max_attempts: int = 3,
    backoff_factor: float = 2.0,
    exceptions: tuple = (Exception,)
):
    """Retry decorator with exponential backoff."""
    def decorator(func: Callable[..., T]) -> Callable[..., T]:
        @wraps(func)
        def wrapper(*args, **kwargs) -> T:
            last_exception = None
            for attempt in range(max_attempts):
                try:
                    return func(*args, **kwargs)
                except exceptions as e:
                    last_exception = e
                    if attempt < max_attempts - 1:
                        sleep_time = backoff_factor ** attempt
                        time.sleep(sleep_time)
                        continue
                    raise
            raise last_exception
        return wrapper
    return decorator

# Usage
@retry(max_attempts=3, exceptions=(NetworkError,))
def fetch_data(url: str) -> dict:
    response = requests.get(url, timeout=5)
    response.raise_for_status()
    return response.json()

TypeScript/JavaScript Error Handling

Custom Error Classes:

// Custom error classes
class ApplicationError extends Error {
  constructor(
    message: string,
    public code: string,
    public statusCode: number = 500,
    public details?: Record<string, any>,
  ) {
    super(message);
    this.name = this.constructor.name;
    Error.captureStackTrace(this, this.constructor);
  }
}

class ValidationError extends ApplicationError {
  constructor(message: string, details?: Record<string, any>) {
    super(message, "VALIDATION_ERROR", 400, details);
  }
}

class NotFoundError extends ApplicationError {
  constructor(resource: string, id: string) {
    super(`${resource} not found`, "NOT_FOUND", 404, { resource, id });
  }
}

// Usage
function getUser(id: string): User {
  const user = users.find((u) => u.id === id);
  if (!user) {
    throw new NotFoundError("User", id);
  }
  return user;
}

Result Type Pattern:

// Result type for explicit error handling
type Result<T, E = Error> = { ok: true; value: T } | { ok: false; error: E };

// Helper functions
function Ok<T>(value: T): Result<T, never> {
  return { ok: true, value };
}

function Err<E>(error: E): Result<never, E> {
  return { ok: false, error };
}

// Usage
function parseJSON<T>(json: string): Result<T, SyntaxError> {
  try {
    const value = JSON.parse(json) as T;
    return Ok(value);
  } catch (error) {
    return Err(error as SyntaxError);
  }
}

// Consuming Result
const result = parseJSON<User>(userJson);
if (result.ok) {
  console.log(result.value.name);
} else {
  console.error("Parse failed:", result.error.message);
}

// Chaining Results
function chain<T, U, E>(
  result: Result<T, E>,
  fn: (value: T) => Result<U, E>,
): Result<U, E> {
  return result.ok ? fn(result.value) : result;
}

Async Error Handling:

// Async/await with proper error handling
async function fetchUserOrders(userId: string): Promise<Order[]> {
  try {
    const user = await getUser(userId);
    const orders = await getOrders(user.id);
    return orders;
  } catch (error) {
    if (error instanceof NotFoundError) {
      return []; // Return empty array for not found
    }
    if (error instanceof NetworkError) {
      // Retry logic
      return retryFetchOrders(userId);
    }
    // Re-throw unexpected errors
    throw error;
  }
}

// Promise error handling
function fetchData(url: string): Promise<Data> {
  return fetch(url)
    .then((response) => {
      if (!response.ok) {
        throw new NetworkError(`HTTP ${response.status}`);
      }
      return response.json();
    })
    .catch((error) => {
      console.error("Fetch failed:", error);
      throw error;
    });
}

Rust Error Handling

Result and Option Types:

use std::fs::File;
use std::io::{self, Read};

// Result type for operations that can fail
fn read_file(path: &str) -> Result<String, io::Error> {
    let mut file = File::open(path)?;  // ? operator propagates errors
    let mut contents = String::new();
    file.read_to_string(&mut contents)?;
    Ok(contents)
}

// Custom error types
#[derive(Debug)]
enum AppError {
    Io(io::Error),
    Parse(std::num::ParseIntError),
    NotFound(String),
    Validation(String),
}

impl From<io::Error> for AppError {
    fn from(error: io::Error) -> Self {
        AppError::Io(error)
    }
}

// Using custom error type
fn read_number_from_file(path: &str) -> Result<i32, AppError> {
    let contents = read_file(path)?;  // Auto-converts io::Error
    let number = contents.trim().parse()
        .map_err(AppError::Parse)?;   // Explicitly convert ParseIntError
    Ok(number)
}

// Option for nullable values
fn find_user(id: &str) -> Option<User> {
    users.iter().find(|u| u.id == id).cloned()
}

// Combining Option and Result
fn get_user_age(id: &str) -> Result<u32, AppError> {
    find_user(id)
        .ok_or_else(|| AppError::NotFound(id.to_string()))
        .map(|user| user.age)
}

Go Error Handling

Explicit Error Returns:

// Basic error handling
func getUser(id string) (*User, error) {
    user, err := db.QueryUser(id)
    if err != nil {
        return nil, fmt.Errorf("failed to query user: %w", err)
    }
    if user == nil {
        return nil, errors.New("user not found")
    }
    return user, nil
}

// Custom error types
type ValidationError struct {
    Field   string
    Message string
}

func (e *ValidationError) Error() string {
    return fmt.Sprintf("validation failed for %s: %s", e.Field, e.Message)
}

// Sentinel errors for comparison
var (
    ErrNotFound     = errors.New("not found")
    ErrUnauthorized = errors.New("unauthorized")
    ErrInvalidInput = errors.New("invalid input")
)

// Error checking
user, err := getUser("123")
if err != nil {
    if errors.Is(err, ErrNotFound) {
        // Handle not found
    } else {
        // Handle other errors
    }
}

// Error wrapping and unwrapping
func processUser(id string) error {
    user, err := getUser(id)
    if err != nil {
        return fmt.Errorf("process user failed: %w", err)
    }
    // Process user
    return nil
}

// Unwrap errors
err := processUser("123")
if err != nil {
    var valErr *ValidationError
    if errors.As(err, &valErr) {
        fmt.Printf("Validation error: %s\n", valErr.Field)
    }
}

Universal Patterns

Pattern 1: Circuit Breaker

Prevent cascading failures in distributed systems.

from enum import Enum
from datetime import datetime, timedelta
from typing import Callable, TypeVar

T = TypeVar('T')

class CircuitState(Enum):
    CLOSED = "closed"       # Normal operation
    OPEN = "open"          # Failing, reject requests
    HALF_OPEN = "half_open"  # Testing if recovered

class CircuitBreaker:
    def __init__(
        self,
        failure_threshold: int = 5,
        timeout: timedelta = timedelta(seconds=60),
        success_threshold: int = 2
    ):
        self.failure_threshold = failure_threshold
        self.timeout = timeout
        self.success_threshold = success_threshold
        self.failure_count = 0
        self.success_count = 0
        self.state = CircuitState.CLOSED
        self.last_failure_time = None

    def call(self, func: Callable[[], T]) -> T:
        if self.state == CircuitState.OPEN:
            if datetime.now() - self.last_failure_time > self.timeout:
                self.state = CircuitState.HALF_OPEN
                self.success_count = 0
            else:
                raise Exception("Circuit breaker is OPEN")

        try:
            result = func()
            self.on_success()
            return result
        except Exception as e:
            self.on_failure()
            raise

    def on_success(self):
        self.failure_count = 0
        if self.state == CircuitState.HALF_OPEN:
            self.success_count += 1
            if self.success_count >= self.success_threshold:
                self.state = CircuitState.CLOSED
                self.success_count = 0

    def on_failure(self):
        self.failure_count += 1
        self.last_failure_time = datetime.now()
        if self.failure_count >= self.failure_threshold:
            self.state = CircuitState.OPEN

# Usage
circuit_breaker = CircuitBreaker()

def fetch_data():
    return circuit_breaker.call(lambda: external_api.get_data())

Pattern 2: Error Aggregation

Collect multiple errors instead of failing on first error.

class ErrorCollector {
  private errors: Error[] = [];

  add(error: Error): void {
    this.errors.push(error);
  }

  hasErrors(): boolean {
    return this.errors.length > 0;
  }

  getErrors(): Error[] {
    return [...this.errors];
  }

  throw(): never {
    if (this.errors.length === 1) {
      throw this.errors[0];
    }
    throw new AggregateError(
      this.errors,
      `${this.errors.length} errors occurred`,
    );
  }
}

// Usage: Validate multiple fields
function validateUser(data: any): User {
  const errors = new ErrorCollector();

  if (!data.email) {
    errors.add(new ValidationError("Email is required"));
  } else if (!isValidEmail(data.email)) {
    errors.add(new ValidationError("Email is invalid"));
  }

  if (!data.name || data.name.length < 2) {
    errors.add(new ValidationError("Name must be at least 2 characters"));
  }

  if (!data.age || data.age < 18) {
    errors.add(new ValidationError("Age must be 18 or older"));
  }

  if (errors.hasErrors()) {
    errors.throw();
  }

  return data as User;
}

Pattern 3: Graceful Degradation

Provide fallback functionality when errors occur.

from typing import Optional, Callable, TypeVar

T = TypeVar('T')

def with_fallback(
    primary: Callable[[], T],
    fallback: Callable[[], T],
    log_error: bool = True
) -> T:
    """Try primary function, fall back to fallback on error."""
    try:
        return primary()
    except Exception as e:
        if log_error:
            logger.error(f"Primary function failed: {e}")
        return fallback()

# Usage
def get_user_profile(user_id: str) -> UserProfile:
    return with_fallback(
        primary=lambda: fetch_from_cache(user_id),
        fallback=lambda: fetch_from_database(user_id)
    )

# Multiple fallbacks
def get_exchange_rate(currency: str) -> float:
    return (
        try_function(lambda: api_provider_1.get_rate(currency))
        or try_function(lambda: api_provider_2.get_rate(currency))
        or try_function(lambda: cache.get_rate(currency))
        or DEFAULT_RATE
    )

def try_function(func: Callable[[], Optional[T]]) -> Optional[T]:
    try:
        return func()
    except Exception:
        return None

Best Practices

Fail Fast: Validate input early, fail quickly
Preserve Context: Include stack traces, metadata, timestamps
Meaningful Messages: Explain what happened and how to fix it
Log Appropriately: Error = log, expected failure = don't spam logs
Handle at Right Level: Catch where you can meaningfully handle
Clean Up Resources: Use try-finally, context managers, defer
Don't Swallow Errors: Log or re-throw, don't silently ignore
Type-Safe Errors: Use typed errors when possible

# Good error handling example
def process_order(order_id: str) -> Order:
    """Process order with comprehensive error handling."""
    try:
        # Validate input
        if not order_id:
            raise ValidationError("Order ID is required")

        # Fetch order
        order = db.get_order(order_id)
        if not order:
            raise NotFoundError("Order", order_id)

        # Process payment
        try:
            payment_result = payment_service.charge(order.total)
        except PaymentServiceError as e:
            # Log and wrap external service error
            logger.error(f"Payment failed for order {order_id}: {e}")
            raise ExternalServiceError(
                f"Payment processing failed",
                service="payment_service",
                details={"order_id": order_id, "amount": order.total}
            ) from e

        # Update order
        order.status = "completed"
        order.payment_id = payment_result.id
        db.save(order)

        return order

    except ApplicationError:
        # Re-raise known application errors
        raise
    except Exception as e:
        # Log unexpected errors
        logger.exception(f"Unexpected error processing order {order_id}")
        raise ApplicationError(
            "Order processing failed",
            code="INTERNAL_ERROR"
        ) from e

Common Pitfalls

Catching Too Broadly: except Exception hides bugs
Empty Catch Blocks: Silently swallowing errors
Logging and Re-throwing: Creates duplicate log entries
Not Cleaning Up: Forgetting to close files, connections
Poor Error Messages: "Error occurred" is not helpful
Returning Error Codes: Use exceptions or Result types
Ignoring Async Errors: Unhandled promise rejections

Resources

resources/exception-hierarchy-design.md: Designing error class hierarchies
resources/error-recovery-strategies.md: Recovery patterns for different scenarios
resources/async-error-handling.md: Handling errors in concurrent code
resources/error-handling-checklist.md: Review checklist for error handling
resources/error-message-guide.md: Writing helpful error messages
scripts/error-analyzer.py: Analyze error patterns in logs

When it activates

Automatically, when a task matches. Use when implementing error handling, designing APIs, or improving application reliability.

About this skill

Automatic

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SkillSafety

✓ 3 of 3 passed

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LLM judge · does the skill do what it claims

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LLM judge · policy & harmful-content review

Source

Imported

valec3 / agents.skills.md

.agent/skills/error-handling-patterns/SKILL.md

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Imported 8/1/2026Version v1Bundled 1 file · scripts

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SkillScore

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What it changes

Track record

Use this skill

Error Handling Patterns

When to Use This Skill

Core Concepts

1. Error Handling Philosophies

2. Error Categories

Language-Specific Patterns

Python Error Handling

TypeScript/JavaScript Error Handling

Rust Error Handling

Go Error Handling

Universal Patterns

Pattern 1: Circuit Breaker

Pattern 2: Error Aggregation

Pattern 3: Graceful Degradation

Best Practices

Common Pitfalls

Resources

When it activates

SkillSafety

Source

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