Official agent skill

Sentry Python SDK

by getsentry in getsentry/sentry-for-ai

Full Sentry SDK setup for Python. An agent skill from getsentry/sentry-for-ai.

OfficialApache-2.0Auto-check passedBackend & APIs

Install Sentry Python SDK

skills CLI
$ npx skills add getsentry/sentry-for-ai --skill sentry-python-sdk -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install getsentry/sentry-for-ai sentry-python-sdk --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/getsentry/sentry-for-ai.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills-legacy/sentry-python-sdk .claude/skills/sentry-python-sdk && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
sentry-python-sdk
GitHub stars
268
Token cost
~4.1k tokens
SKILL.md length
1,290 words
Files
8 (incl. references)
Skills in repo
32
Repo updated
First seen
Licence
Apache-2.0

At a glance

Full Sentry SDK setup for Python. An agent skill from getsentry/sentry-for-ai.

  • Works in 4 steps: Detect → Recommend → Guide → …
  • Asked to add Sentry to Python
  • SKILL.md covers Invoke This Skill When, Phase 1: Detect, Phase 2: Recommend and Phase 3: Guide, plus 4 more sections
  • Calls pip and fastapi

What it does

Sentry Python SDK is an agent skill from getsentry/sentry-for-ai, published by the product's own GitHub organization. Full Sentry SDK setup for Python. Use when asked to "add Sentry to Python", "install sentry-sdk", "setup Sentry in Python", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for Python applications. Supports Django, Flask, FastAPI, Celery, Starlette, AIOHTTP, Tornado, and more.

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `references/ai-monitoring.md`, `references/crons.md` and `references/error-monitoring.md`).

It sits in Backend & APIs, covering Backend development, Background jobs and Scheduled and recurring tasks. It works with Sentry, Python, Django and FastAPI. The repository describes itself as: Teach your AI coding assistant how to use Sentry - setup, debugging, alerts, and more. The licence is Apache-2.0.

When your agent uses it

  • Asked to add Sentry to Python
  • Install sentry-sdk
  • Setup Sentry in Python
  • Configure error monitoring

Example prompts

  • “add Sentry to Python”
  • “install sentry-sdk”
  • “setup Sentry in Python”
  • “/sentry-python-sdk”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Detect
  2. Recommend
  3. Guide
  4. Cross-Link

What it can do on your machine

Read from SKILL.md and the folder at commit d8fd106. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip
    • fastapi

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.sentry.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sentry Python SDK loads about 4.1k tokens when it runs, and up to ~18k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 1,290 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~18k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from getsentry/sentry-for-ai at commit d8fd106, republished under its Apache-2.0 licence (© getsentry). 1,290 words, ~4,064 tokens.

Download SKILL.mdSave it as .claude/skills/sentry-python-sdk/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
sentry-python-sdk
description
Full Sentry SDK setup for Python. Use when asked to "add Sentry to Python", "install sentry-sdk", "setup Sentry in Python", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for Python applications. Supports Django, Flask, FastAPI, Celery, Starlette, AIOHTTP, Tornado, and more.
license
Apache-2.0
category
sdk-setup
parent
sentry-sdk-setup
disable-model-invocation
true

All Skills > SDK Setup > Python SDK

Sentry Python SDK

Opinionated wizard that scans your Python project and guides you through complete Sentry setup.

Invoke This Skill When

  • User asks to "add Sentry to Python" or "setup Sentry" in a Python app
  • User wants error monitoring, tracing, profiling, logging, metrics, or crons in Python
  • User mentions sentry-sdk, sentry_sdk, or Sentry + any Python framework
  • User wants to monitor Django views, Flask routes, FastAPI endpoints, Celery tasks, or scheduled jobs

Note: SDK versions and APIs below reflect Sentry docs at time of writing (sentry-sdk 2.x). Always verify against docs.sentry.io/platforms/python/ before implementing.


Phase 1: Detect

Run these commands to understand the project before making recommendations:

bash
# Check existing Sentry
grep -i sentry requirements.txt pyproject.toml setup.cfg setup.py 2>/dev/null

# Detect web framework
grep -rE "django|flask|fastapi|starlette|aiohttp|tornado|quart|falcon|sanic|bottle|pyramid" \
  requirements.txt pyproject.toml 2>/dev/null

# Detect task queues
grep -rE "celery|rq|huey|arq|dramatiq" requirements.txt pyproject.toml 2>/dev/null

# Detect logging libraries
grep -E "loguru" requirements.txt pyproject.toml 2>/dev/null

# Detect AI libraries
grep -rE "openai|anthropic|langchain|huggingface|google-genai|pydantic-ai|litellm" \
  requirements.txt pyproject.toml 2>/dev/null

# Detect schedulers / crons
grep -rE "celery|apscheduler|schedule|crontab" requirements.txt pyproject.toml 2>/dev/null

# OpenTelemetry tracing — check for SDK + instrumentations
grep -rE "opentelemetry-sdk|opentelemetry-instrumentation|opentelemetry-distro" \
  requirements.txt pyproject.toml 2>/dev/null
grep -rn "TracerProvider\|trace\.get_tracer\|start_as_current_span" \
  --include="*.py" 2>/dev/null | head -5

# Check for companion frontend
ls frontend/ web/ client/ ui/ static/ templates/ 2>/dev/null

What to note:

  • Is sentry-sdk already in requirements? If yes, check if sentry_sdk.init() is present — may just need feature config.
  • Which framework? (Determines where to place sentry_sdk.init().)
  • Which task queue? (Celery needs dual-process init; RQ needs a settings file.)
  • AI libraries? (OpenAI, Anthropic, LangChain are auto-instrumented.)
  • OpenTelemetry tracing? (Use OTLP path instead of native tracing.)
  • Companion frontend? (Triggers Phase 4 cross-link.)

Phase 2: Recommend

Based on what you found, present a concrete proposal. Don't ask open-ended questions — lead with a recommendation:

Route from OTel detection:

  • OTel tracing detected (opentelemetry-sdk / opentelemetry-distro in requirements, or TracerProvider in source) → use OTLP path: OTLPIntegration(); do not set traces_sample_rate; Sentry links errors to OTel traces automatically

Always recommended (core coverage):

  • ✅ Error Monitoring — captures unhandled exceptions, supports ExceptionGroup (Python 3.11+)
  • ✅ Logging — Python logging stdlib auto-captured; enhanced if Loguru detected

Recommend when detected:

  • ✅ Tracing — HTTP framework detected (Django/Flask/FastAPI/etc.)
  • ✅ AI Monitoring — OpenAI/Anthropic/LangChain/etc. detected (auto-instrumented, zero config)
  • ⚡ Profiling — production apps where performance matters; not available with OTLP path
  • ⚡ Crons — Celery Beat, APScheduler, or cron patterns detected
  • ⚡ Metrics — business KPIs, SLO tracking

Recommendation matrix:

FeatureRecommend when...Reference
Error MonitoringAlways — non-negotiable baseline${SKILL_ROOT}/references/error-monitoring.md
OTLP IntegrationOTel tracing detected — replaces native Tracing${SKILL_ROOT}/references/tracing.md
TracingDjango/Flask/FastAPI/AIOHTTP/etc. detected; skip if OTel tracing detected${SKILL_ROOT}/references/tracing.md
ProfilingProduction + performance-sensitive workload; skip if OTel tracing detected (requires traces_sample_rate, incompatible with OTLP)${SKILL_ROOT}/references/profiling.md
LoggingAlways (stdlib); enhanced for Loguru${SKILL_ROOT}/references/logging.md
MetricsBusiness events or SLO tracking needed${SKILL_ROOT}/references/metrics.md
CronsCelery Beat, APScheduler, or cron patterns${SKILL_ROOT}/references/crons.md
AI MonitoringOpenAI/Anthropic/LangChain/etc. detected${SKILL_ROOT}/references/ai-monitoring.md

OTel tracing detected: "I see OpenTelemetry tracing in the project. I recommend Sentry's OTLP integration for tracing (via your existing OTel setup) + Error Monitoring + Sentry Logging [+ Metrics/Crons/AI Monitoring if applicable]. Shall I proceed?"

No OTel: "I recommend Error Monitoring + Tracing [+ Logging if applicable]. Want Profiling, Crons, or AI Monitoring too?"


Phase 3: Guide

Install
bash
# Core SDK (always required)
pip install sentry-sdk

# Optional extras (install only what matches detected framework):
pip install "sentry-sdk[django]"
pip install "sentry-sdk[flask]"
pip install "sentry-sdk[fastapi]"
pip install "sentry-sdk[celery]"
pip install "sentry-sdk[aiohttp]"
pip install "sentry-sdk[tornado]"

# Multiple extras:
pip install "sentry-sdk[django,celery]"

Extras are optional — plain sentry-sdk works for all frameworks. Extras install complementary packages.

Full init enabling the most features with sensible defaults. Place before any app/framework code:

python
import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    environment=os.environ.get("SENTRY_ENVIRONMENT", "production"),
    release=os.environ.get("SENTRY_RELEASE"),   # e.g. "myapp@1.0.0"
    send_default_pii=True,

    # Tracing (lower to 0.1–0.2 in high-traffic production)
    traces_sample_rate=1.0,

    # Profiling — continuous, tied to active spans
    profile_session_sample_rate=1.0,
    profile_lifecycle="trace",

    # Structured logs (SDK ≥ 2.35.0)
    enable_logs=True,
)
Where to Initialize Per Framework
FrameworkWhere to call sentry_sdk.init()Notes
DjangoTop of settings.py, before any importsNo middleware needed — Sentry patches Django internally
FlaskBefore app = Flask(__name__)Must precede app creation
FastAPIBefore app = FastAPI()StarletteIntegration + FastApiIntegration auto-enabled together
StarletteBefore app = Starlette(...)Same auto-integration as FastAPI
AIOHTTPModule level, before web.Application()
TornadoModule level, before app setupNo integration class needed
QuartBefore app = Quart(__name__)
FalconModule level, before app = falcon.App()
PyramidModule level, before config = Configurator()WSGI framework
SanicInside @app.listener("before_server_start")Sanic's lifecycle requires async init
Celery@signals.celeryd_init.connect in worker AND in calling processDual-process init required
RQmysettings.py loaded by worker via rq worker -c mysettings
ARQBoth worker module and enqueuing process

Django example (settings.py):

python
import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    send_default_pii=True,
    traces_sample_rate=1.0,
    profile_session_sample_rate=1.0,
    profile_lifecycle="trace",
    enable_logs=True,
)

# rest of Django settings...
INSTALLED_APPS = [...]

FastAPI example (main.py):

python
import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    send_default_pii=True,
    traces_sample_rate=1.0,
    profile_session_sample_rate=1.0,
    profile_lifecycle="trace",
    enable_logs=True,
)

from fastapi import FastAPI
app = FastAPI()
Auto-Enabled vs Explicit Integrations

Most integrations activate automatically when their package is installed — no integrations=[...] needed:

Auto-enabledExplicit required
Django, Flask, FastAPI, Starlette, AIOHTTP, Tornado, Quart, Falcon, Pyramid, Sanic, BottleDramatiqIntegration
Celery, RQ, Huey, ARQGRPCIntegration
SQLAlchemy, Redis, asyncpg, pymongoStrawberryIntegration
Requests, HTTPX, httpx2, aiohttp-clientAsyncioIntegration
OpenAI, Anthropic, LangChain, Pydantic AI, MCPOpenTelemetryIntegration
Python logging, LoguruWSGIIntegration / ASGIIntegration
For Each Agreed Feature

Walk through features one at a time. Load the reference, follow its steps, verify before moving on:

FeatureReference fileLoad when...
Error Monitoring${SKILL_ROOT}/references/error-monitoring.mdAlways (baseline)
Tracing${SKILL_ROOT}/references/tracing.mdHTTP handlers / distributed tracing
Profiling${SKILL_ROOT}/references/profiling.mdPerformance-sensitive production
Logging${SKILL_ROOT}/references/logging.mdAlways; enhanced for Loguru
Metrics${SKILL_ROOT}/references/metrics.mdBusiness KPIs / SLO tracking
Crons${SKILL_ROOT}/references/crons.mdScheduler / cron patterns detected
AI Monitoring${SKILL_ROOT}/references/ai-monitoring.mdAI library detected

For each feature: Read ${SKILL_ROOT}/references/<feature>.md, follow steps exactly, verify it works.


Configuration Reference

Show full SKILL.md (589 more words)Show less
Key sentry_sdk.init() Options
OptionTypeDefaultPurpose
dsnstrNoneSDK disabled if empty; env: SENTRY_DSN
environmentstr"production"e.g., "staging"; env: SENTRY_ENVIRONMENT
releasestrNonee.g., "myapp@1.0.0"; env: SENTRY_RELEASE
send_default_piiboolFalseInclude IP, headers, cookies, auth user, query strings (ASGI frameworks)
traces_sample_ratefloatNoneTransaction sample rate; None disables tracing
traces_samplerCallableNoneCustom per-transaction sampling (overrides rate)
profile_session_sample_ratefloatNoneContinuous profiling session rate
profile_lifecyclestr"manual""trace" = auto-start profiler with spans
profiles_sample_ratefloatNoneTransaction-based profiling rate
enable_logsboolFalseSend logs to Sentry (SDK ≥ 2.35.0)
sample_ratefloat1.0Error event sample rate
attach_stacktraceboolFalseStack traces on capture_message()
max_breadcrumbsint100Max breadcrumbs per event
debugboolFalseVerbose SDK debug output
before_sendCallableNoneHook to mutate/drop error events
before_send_transactionCallableNoneHook to mutate/drop transaction events
ignore_errorslist[]Exception types or regex patterns to suppress
auto_enabling_integrationsboolTrueSet False to disable all auto-detection
OTLPIntegration Options (pass to constructor)
OptionTypeDefaultPurpose
setup_otlp_traces_exporterboolTrueAuto-configure OTLP exporter; set False if you send to your own Collector
collector_urlstrNoneOTLP HTTP endpoint of an OTel Collector (e.g., http://localhost:4318/v1/traces); when set, spans are sent to the collector instead of directly to Sentry
setup_propagatorboolTrueAuto-configure Sentry propagator for distributed tracing
capture_exceptionsboolFalseIntercept exceptions recorded via OTel Span.record_exception
Environment Variables
VariableMaps toNotes
SENTRY_DSNdsn
SENTRY_RELEASEreleaseAlso auto-detected from git SHA, Heroku, CircleCI, CodeBuild, GAE
SENTRY_ENVIRONMENTenvironment
SENTRY_DEBUGdebug

Verification

Test that Sentry is receiving events:

python
# Trigger a real error event — check dashboard within seconds
division_by_zero = 1 / 0

Or for a non-crashing check:

python
sentry_sdk.capture_message("Sentry Python SDK test")

If nothing appears:

  1. Set debug=True in sentry_sdk.init() — prints SDK internals to stdout
  2. Verify the DSN is correct
  3. Check SENTRY_DSN env var is set in the running process
  4. For Celery/RQ: ensure init runs in the worker process, not just the calling process

After completing Python setup, check for a companion frontend missing Sentry:

bash
ls frontend/ web/ client/ ui/ 2>/dev/null
cat frontend/package.json web/package.json client/package.json 2>/dev/null \
  | grep -E '"react"|"svelte"|"vue"|"next"|"nuxt"'

If a frontend exists without Sentry, suggest the matching skill:

Frontend detectedSuggest skill
React / Next.jssentry-react-sdk
Svelte / SvelteKitsentry-svelte-sdk
Vue / NuxtUse @sentry/vue — see docs.sentry.io/platforms/javascript/guides/vue/
Other JS/TSsentry-react-sdk (covers generic browser JS patterns)

Troubleshooting

IssueSolution
Events not appearingSet debug=True, verify DSN, check env vars in the running process
Malformed DSN errorFormat: https://<key>@o<org>.ingest.sentry.io/<project>
Django exceptions not capturedEnsure sentry_sdk.init() is at the top of settings.py before other imports
Flask exceptions not capturedInit must happen before app = Flask(__name__)
FastAPI exceptions not capturedInit before app = FastAPI(); both StarletteIntegration and FastApiIntegration auto-enabled
ASGI chained exceptions suppressedBy default, Sentry's ASGI middleware strips exception chains (raise exc from None). To preserve chained exceptions, set _experiments={"suppress_asgi_chained_exceptions": False} in sentry_sdk.init()
Celery task errors not capturedMust call sentry_sdk.init() in the worker process via celeryd_init signal
Sanic init not workingInit must be inside @app.listener("before_server_start"), not module level
uWSGI not capturingAdd --enable-threads --py-call-uwsgi-fork-hooks to uWSGI command
No traces appearing (native)Verify traces_sample_rate is set (not None); check that the integration is auto-enabled
No traces appearing (OTLP)Verify sentry-sdk[opentelemetry-otlp] is installed; do not set traces_sample_rate when using OTLPIntegration
Profiling not startingRequires traces_sample_rate > 0 + either profile_session_sample_rate or profiles_sample_rate; not compatible with OTLP path
enable_logs not workingRequires SDK ≥ 2.35.0; for direct structured logs use sentry_sdk.logger; for stdlib bridging use LoggingIntegration(sentry_logs_level=...)
Too many transactionsLower traces_sample_rate or use traces_sampler to drop health checks
Cross-request data leakingDon't use get_global_scope() for per-request data — use get_isolation_scope()
Query strings not captured (ASGI)Query strings and client IP in ASGI frameworks (FastAPI, Starlette, etc.) require send_default_pii=True
RQ worker not reportingPass --sentry-dsn="" to disable RQ's own Sentry shortcut; init via settings file instead

© getsentry, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in skills-legacy/sentry-python-sdk of getsentry/sentry-for-ai.

  • SKILL.md
  • references/ai-monitoring.md
  • references/crons.md
  • references/error-monitoring.md
  • references/logging.md
  • references/metrics.md
  • references/profiling.md
  • references/tracing.md

Open the folder on GitHubat commit d8fd106

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Framework Migration AssistantArabelaTso/Skills-4-SE253—~1.9kAutomated safety check: PassApache-2.0
Python Appservice Deploymicrosoft/GitHub-Copilot-for-Azure2551 repos~688Automated safety check: PassMIT
Python Devdoccker/cc-use-exp1.1k—~790Automated safety check: PassCustom licence

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Categories

Questions about Sentry Python SDK

What does Sentry Python SDK do?

Full Sentry SDK setup for Python. An agent skill from getsentry/sentry-for-ai. Sentry Python SDK is an agent skill from getsentry/sentry-for-ai, published by the product's own GitHub organization. Full Sentry SDK setup for Python.

When should I use Sentry Python SDK?

Sentry Python SDK fits situations like: asked to add Sentry to Python; install sentry-sdk; setup Sentry in Python; configure error monitoring.

How do I install Sentry Python SDK in Claude Code?

Run `npx skills add getsentry/sentry-for-ai --skill sentry-python-sdk -a claude-code`. Or copy the skill folder (skills-legacy/sentry-python-sdk in getsentry/sentry-for-ai) into .claude/skills/sentry-python-sdk in your project. Claude Code loads it when a task matches its description.

How do I install Sentry Python SDK in Codex?

Run `npx skills add getsentry/sentry-for-ai --skill sentry-python-sdk -a codex`. Or copy the skill folder (skills-legacy/sentry-python-sdk in getsentry/sentry-for-ai) into .agents/skills/sentry-python-sdk in your project. Codex loads it when a task matches its description.

Can I use Sentry Python SDK in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add getsentry/sentry-for-ai --skill sentry-python-sdk -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sentry-python-sdk, .gemini/skills/sentry-python-sdk, .github/skills/sentry-python-sdk and .opencode/skills/sentry-python-sdk in your project.

What does Sentry Python SDK need to run?

Going by SKILL.md and its folder, Sentry Python SDK needs the command-line tools its instructions call (pip and fastapi). Our summary lists: Python 3.

Does Sentry Python SDK access the network?

SKILL.md names 1 domain. As links in the text: docs.sentry.io. This is read from the text; nothing was executed.

Is Sentry Python SDK safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Sentry Python SDK use?

Sentry Python SDK is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sentry Python SDK use?

About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 14k tokens, read only when the agent opens those files.

What are the alternatives to Sentry Python SDK?

Skills that share tags, products or a category with Sentry Python SDK: Otel Python (ollygarden/opentelemetry-agent-skills, 106 stars), Fix Slow Endpoint (vpcarlos/profyle, 123 stars), Framework Migration Assistant (ArabelaTso/Skills-4-SE, 253 stars) and Python Appservice Deploy (microsoft/GitHub-Copilot-for-Azure, 255 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sentry Python SDK?

getsentry (a GitHub organization, an official publisher) maintains it in getsentry/sentry-for-ai, which has 268 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on October 7, 2026.

Source: getsentry/sentry-for-ai on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.