Agent skill

Sentry Performance Tracing

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Set up performance monitoring and distributed tracing with Sentry.

MITAuto-check passedDevOps & Cloud

Install Sentry Performance Tracing

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill sentry-performance-tracing -a claude-code

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace sentry-performance-tracing --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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/sentry-performance-tracing .claude/skills/sentry-performance-tracing && 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-performance-tracing
GitHub stars
2.8k
Token cost
~4.1k tokens
SKILL.md length
779 words
Files
5 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Set up performance monitoring and distributed tracing with Sentry.

  • Works in 3 steps: Configure Tracing and Profiling in SDK… → Create Custom Spans for Business Logic → Enable Auto-Instrumentation and…
  • Implementing performance tracking
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Sentry Performance Tracing is an agent skill from jeremylongshore/tons-of-skills-marketplace. Set up performance monitoring and distributed tracing with Sentry. Use when implementing performance tracking, tracing requests, or monitoring application performance. Trigger with phrases like "sentry performance", "sentry tracing", "sentry APM", "monitor performance sentry".

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/best-practices.md`, `references/errors.md` and `references/examples.md`). Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Observability and Monitoring and alerting. It works with Sentry. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Implementing performance tracking
  • Tracing requests
  • Monitoring application performance
  • With phrases like sentry performance

Example prompts

  • “sentry performance”
  • “sentry tracing”
  • “sentry APM”
  • “/sentry-performance-tracing”

Requirements

  • Python 3
  • Node.js
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Bash(node:*)

Workflow steps

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

  1. Configure Tracing and Profiling in SDK Init
  2. Create Custom Spans for Business Logic
  3. Enable Auto-Instrumentation and Distributed Tracing

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep
    • Bash(node:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript and python).

    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.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Sentry Performance Tracing loads about 4.1k tokens when it runs, and up to ~5.3k if it reads all its reference files. Until then it costs about 76 tokens; SKILL.md has 779 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~76
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
~5.3k

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 jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 779 words, ~4,093 tokens.

Download SKILL.mdSave it as .claude/skills/sentry-performance-tracing/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
sentry-performance-tracing
description
Set up performance monitoring and distributed tracing with Sentry. Use when implementing performance tracking, tracing requests, or monitoring application performance. Trigger with phrases like "sentry performance", "sentry tracing", "sentry APM", "monitor performance sentry".
allowed-tools
Read, Write, Edit, Grep, Bash(node:*)
compatibility
Designed for Claude Code
version
1.51.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, sentry, monitoring, performance, tracing, spans

Sentry Performance Tracing

Overview

Sentry performance monitoring captures distributed traces across your application stack, measuring latency, identifying bottlenecks, and tracking Web Vitals. The v8 SDK uses a span-based API where Sentry.startSpan() replaces the deprecated startTransaction(). Auto-instrumentation covers HTTP, database queries, and framework routes out of the box. Manual spans let you measure business-critical operations. Combined with profiling (profilesSampleRate), you get function-level flamegraphs attached to traces.

Prerequisites

  • Sentry SDK v8+ installed (@sentry/node >= 8.0.0 or sentry-sdk >= 2.0.0)
  • tracesSampleRate > 0 set in Sentry.init() — performance data is not collected at zero
  • Performance monitoring enabled in your Sentry project settings (Settings > Performance)
  • For distributed tracing: all participating services must have Sentry SDK initialized

Instructions

Step 1 — Configure Tracing and Profiling in SDK Init

Set tracesSampleRate to control what percentage of requests generate traces. Use tracesSampler for dynamic, per-endpoint sampling. Add profilesSampleRate to attach function-level flamegraphs to sampled transactions.

TypeScript (@sentry/node):

typescript
import * as Sentry from '@sentry/node';

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  tracesSampleRate: 0.2, // 20% of transactions in production

  // Profiling — profiles 10% of sampled transactions
  profilesSampleRate: 0.1,

  // Dynamic sampling overrides tracesSampleRate when defined
  tracesSampler: (samplingContext) => {
    const { name, attributes } = samplingContext;

    // Drop health checks entirely — no trace data
    if (name === 'GET /health') return 0;

    // Always trace payment flows
    if (name?.includes('/api/payment')) return 1.0;

    // Higher sampling for API routes
    if (name?.startsWith('GET /api/') || name?.startsWith('POST /api/')) return 0.2;

    // Default: 5% for everything else
    return 0.05;
  },
});

Python (sentry-sdk):

python
import os
import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    traces_sample_rate=0.2,       # 20% of transactions
    profiles_sample_rate=0.1,     # 10% of sampled transactions get profiled

    # Dynamic sampling via traces_sampler (overrides traces_sample_rate)
    traces_sampler=lambda ctx: (
        0.0 if ctx.get("transaction_context", {}).get("name") == "GET /health"
        else 1.0 if "/api/payment" in ctx.get("transaction_context", {}).get("name", "")
        else 0.2
    ),
)

Key decisions:

  • Start at tracesSampleRate: 0.2 and adjust based on volume and budget
  • tracesSampler takes priority when defined — tracesSampleRate becomes the fallback
  • profilesSampleRate is relative to sampled transactions (0.1 means 10% of the 20% that are sampled)
  • Return 0 from tracesSampler to explicitly drop a transaction, not false
Step 2 — Create Custom Spans for Business Logic

Auto-instrumentation covers HTTP and database calls, but business-critical operations need manual spans. The v8 API provides three span creation methods for different use cases.

Sentry.startSpan() — auto-ending spans (most common):

typescript
import * as Sentry from '@sentry/node';

const result = await Sentry.startSpan(
  {
    name: 'order.process',
    op: 'task',
    attributes: {
      'order.id': orderId,
      'order.items': items.length,
    },
  },
  async (span) => {
    // Nested spans automatically become children of the parent
    const validated = await Sentry.startSpan(
      { name: 'order.validate', op: 'validation' },
      async () => validateOrder(order)
    );

    const charged = await Sentry.startSpan(
      { name: 'payment.charge', op: 'http.client' },
      async () => chargePayment(order.total)
    );

    // Set span status based on outcome
    if (!charged.success) {
      span.setStatus({ code: 2, message: 'payment_failed' });
    }

    // Add custom measurements visible in Performance dashboard
    Sentry.setMeasurement('order.item_count', items.length, 'none');
    Sentry.setMeasurement('order.total_cents', order.total, 'none');

    return { validated, charged };
  }
);
// Span automatically ends when callback resolves or rejects

Sentry.startSpanManual() — for spans that cross callback boundaries:

typescript
Sentry.startSpanManual(
  { name: 'queue.process', op: 'queue.task' },
  (span) => {
    queue.on('message', async (msg) => {
      try {
        await processMessage(msg);
        span.setStatus({ code: 1 }); // OK
      } catch (error) {
        span.setStatus({ code: 2, message: 'processing_failed' });
        Sentry.captureException(error);
      } finally {
        span.end(); // REQUIRED — must call end() manually
      }
    });
  }
);

Sentry.startInactiveSpan() — background work without changing active context:

typescript
const span = Sentry.startInactiveSpan({
  name: 'cache.warmup',
  op: 'cache',
});

await warmCache(); // Other spans created here won't be children of this span

span.end();

Span attributes and measurements:

typescript
await Sentry.startSpan(
  { name: 'search.query', op: 'db.query' },
  async (span) => {
    const start = Date.now();
    const results = await searchIndex(query);

    // Attributes — appear in span details, filterable in Sentry UI
    span.setAttribute('search.query', query);
    span.setAttribute('search.results_count', results.length);
    span.setAttribute('search.index', indexName);

    // Measurements — appear in Performance dashboard charts
    Sentry.setMeasurement('search.duration_ms', Date.now() - start, 'millisecond');
    Sentry.setMeasurement('search.result_count', results.length, 'none');

    return results;
  }
);

Python equivalent:

python
import sentry_sdk

with sentry_sdk.start_span(op="task", name="process_order") as span:
    span.set_data("order_id", order_id)
    span.set_data("item_count", len(items))

    with sentry_sdk.start_span(op="validation", name="validate_input"):
        validate(input_data)

    with sentry_sdk.start_span(op="http.client", name="charge_payment"):
        result = charge(payment)

    if not result.success:
        span.set_status("internal_error")
Step 3 — Enable Auto-Instrumentation and Distributed Tracing

SDK v8 auto-instruments most I/O without configuration. For distributed tracing across services, Sentry propagates sentry-trace and baggage headers automatically on HTTP calls. Custom propagation is needed only for non-HTTP transports (message queues, gRPC, etc.).

Auto-instrumented integrations (Node.js v8):

IntegrationWhat it tracesEnabled by
httpIntegration()All outbound HTTP/HTTPS requestsDefault
expressIntegration()Express route handlers and middlewareDefault with Express
fastifyIntegration()Fastify routesDefault with Fastify
graphqlIntegration()GraphQL resolversDefault with graphql
mongoIntegration()MongoDB queriesDefault with mongodb driver
postgresIntegration()PostgreSQL queries (pg driver)Default with pg
mysqlIntegration()MySQL queriesDefault with mysql2
redisIntegration()Redis commandsDefault with ioredis/redis
prismaIntegration()Prisma ORM queriesDefault with @prisma/client

Express with custom middleware spans:

typescript
import express from 'express';
import * as Sentry from '@sentry/node';

const app = express();

// Sentry auto-instruments all Express routes
// Add custom spans for specific middleware:
app.use('/api', async (req, res, next) => {
  await Sentry.startSpan(
    { name: 'middleware.auth', op: 'middleware' },
    async () => {
      req.user = await authenticateRequest(req);
    }
  );
  next();
});

// Parameterized route names prevent cardinality explosion
// Sentry automatically uses '/api/users/:id' not '/api/users/12345'
app.get('/api/users/:id', async (req, res) => {
  const user = await Sentry.startSpan(
    { name: 'db.getUser', op: 'db.query' },
    () => db.users.findById(req.params.id)
  );
  res.json(user);
});

// Must be after all routes
Sentry.setupExpressErrorHandler(app);

Django/Flask auto-instrumentation (Python):

python
import sentry_sdk
from sentry_sdk.integrations.django import DjangoIntegration

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    integrations=[DjangoIntegration()],
    traces_sample_rate=0.2,
    profiles_sample_rate=0.1,
)
# All Django views, middleware, and template rendering are traced automatically
python
# Flask equivalent
from sentry_sdk.integrations.flask import FlaskIntegration

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    integrations=[FlaskIntegration()],
    traces_sample_rate=0.2,
)
python
# FastAPI equivalent
from sentry_sdk.integrations.fastapi import FastApiIntegration
from sentry_sdk.integrations.starlette import StarletteIntegration

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    integrations=[FastApiIntegration(), StarletteIntegration()],
    traces_sample_rate=0.2,
)

Distributed tracing — custom header propagation:

When Sentry cannot automatically propagate headers (non-HTTP transports, custom fetch wrappers), extract and inject manually:

typescript
// Service A: Extract trace headers from the active span
const activeSpan = Sentry.getActiveSpan();
const traceHeaders = {
  'sentry-trace': Sentry.spanToTraceHeader(activeSpan),
  'baggage': Sentry.spanToBaggageHeader(activeSpan),
};

// Pass headers to downstream service via HTTP, message queue, etc.
await fetch('https://service-b.internal/api/process', {
  headers: { ...traceHeaders, 'Content-Type': 'application/json' },
  body: JSON.stringify(payload),
});

// Service B: Sentry SDK automatically reads sentry-trace and baggage
// from incoming request headers and continues the same trace

Browser Web Vitals (@sentry/browser):

The browser SDK automatically captures Core Web Vitals when tracing is enabled:

  • LCP (Largest Contentful Paint) — loading performance
  • INP (Interaction to Next Paint) — responsiveness (replaced FID in 2024)
  • CLS (Cumulative Layout Shift) — visual stability
  • TTFB (Time to First Byte) — server response time

These appear in the Web Vitals tab of your Sentry Performance dashboard. No additional configuration beyond tracesSampleRate > 0 in the browser SDK.

Show full SKILL.md (319 more words)Show less

Output

  • Distributed traces visible in Sentry Performance > Trace View as span waterfalls
  • Auto-instrumented spans for HTTP, database, and framework operations
  • Custom spans with attributes measuring business-critical operations
  • Profiling flamegraphs attached to sampled transactions
  • Web Vitals (LCP, INP, CLS, TTFB) tracked for frontend performance
  • Custom measurements charted in Performance dashboard
  • Cross-service traces linked via sentry-trace and baggage headers

Error Handling

ErrorCauseSolution
No transactions in Performance tabtracesSampleRate is 0 or not setSet tracesSampleRate > 0 in Sentry.init() or define tracesSampler
Spans not nested correctlyChild span created outside parent callbackCall Sentry.startSpan() inside the parent startSpan callback to establish parent-child
High cardinality warning in Sentry UIDynamic values in span/transaction namesUse parameterized names (/api/users/:id) not literal values (/api/users/12345)
Distributed trace broken between servicessentry-trace/baggage headers not forwardedVerify both headers are propagated in inter-service HTTP calls
startSpanManual span never endsMissing span.end() callAlways call span.end() in a finally block
Profiling data missingprofilesSampleRate not set or @sentry/profiling-node not installedSet profilesSampleRate > 0 and install the profiling package
tracesSampler errors silentlySampler function throwsWrap sampler logic in try/catch, return a fallback rate
Performance data but no Web VitalsBrowser SDK not initialized or tracesSampleRate is 0 on clientEnsure @sentry/browser or @sentry/react is initialized with tracing

Examples

TypeScript — Full Express API with Profiling
typescript
import * as Sentry from '@sentry/node';
import express from 'express';

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  tracesSampleRate: 0.2,
  profilesSampleRate: 0.1,
});

const app = express();

app.post('/api/orders', async (req, res) => {
  const order = await Sentry.startSpan(
    { name: 'order.create', op: 'task', attributes: { 'order.source': 'api' } },
    async (span) => {
      const validated = await Sentry.startSpan(
        { name: 'order.validate', op: 'validation' },
        () => validateOrder(req.body)
      );

      const saved = await Sentry.startSpan(
        { name: 'order.save', op: 'db.query' },
        () => db.orders.create(validated)
      );

      await Sentry.startSpan(
        { name: 'notification.send', op: 'http.client' },
        () => notifyWarehouse(saved.id)
      );

      Sentry.setMeasurement('order.total_cents', saved.total, 'none');
      return saved;
    }
  );

  res.status(201).json(order);
});

Sentry.setupExpressErrorHandler(app);
app.listen(3000);
Python — FastAPI with Custom Spans
python
import os
import sentry_sdk
from sentry_sdk.integrations.fastapi import FastApiIntegration
from sentry_sdk.integrations.starlette import StarletteIntegration
from fastapi import FastAPI

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    integrations=[FastApiIntegration(), StarletteIntegration()],
    traces_sample_rate=0.2,
    profiles_sample_rate=0.1,
)

app = FastAPI()

@app.post("/api/orders")
async def create_order(payload: OrderRequest):
    with sentry_sdk.start_span(op="task", name="order.create") as span:
        span.set_data("order_source", "api")

        with sentry_sdk.start_span(op="validation", name="order.validate"):
            validated = validate_order(payload)

        with sentry_sdk.start_span(op="db.query", name="order.save"):
            saved = await db.orders.create(validated)

        with sentry_sdk.start_span(op="http.client", name="notification.send"):
            await notify_warehouse(saved.id)

    return {"id": saved.id, "status": "created"}

Resources

Next Steps

  • Alerting on performance regressions: Configure Performance Alerts in Sentry to trigger when p95 latency exceeds thresholds or throughput drops
  • Custom dashboards: Build dashboards in Sentry using custom measurements (Sentry.setMeasurement()) to track business KPIs alongside latency
  • Span sampling in high-volume services: Use tracesSampler to selectively trace slow endpoints at higher rates while keeping fast endpoints low
  • Connect to error tracking: Errors captured with Sentry.captureException() inside a traced span automatically link to that trace in the Sentry UI

© jeremylongshore, MIT. 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 4 other files (references) in skills/.curated/sentry-performance-tracing of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/best-practices.md
  • references/errors.md
  • references/examples.md
  • references/implementation.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Sentry Performance Tracing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Works with

Categories

Questions about Sentry Performance Tracing

What does Sentry Performance Tracing do?

Set up performance monitoring and distributed tracing with Sentry. Sentry Performance Tracing is an agent skill from jeremylongshore/tons-of-skills-marketplace. Set up performance monitoring and distributed tracing with Sentry.

When should I use Sentry Performance Tracing?

Sentry Performance Tracing fits situations like: implementing performance tracking; tracing requests; monitoring application performance; with phrases like sentry performance.

How do I install Sentry Performance Tracing in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill sentry-performance-tracing -a claude-code`. Or copy the skill folder (skills/.curated/sentry-performance-tracing in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/sentry-performance-tracing in your project. Claude Code loads it when a task matches its description.

How do I install Sentry Performance Tracing in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill sentry-performance-tracing -a codex`. Or copy the skill folder (skills/.curated/sentry-performance-tracing in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/sentry-performance-tracing in your project. Codex loads it when a task matches its description.

Can I use Sentry Performance Tracing 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 jeremylongshore/tons-of-skills-marketplace --skill sentry-performance-tracing -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-performance-tracing, .gemini/skills/sentry-performance-tracing, .github/skills/sentry-performance-tracing and .opencode/skills/sentry-performance-tracing in your project.

What does Sentry Performance Tracing need to run?

SKILL.md names no scripts, command-line tools or credentials: Sentry Performance Tracing is instructions for the agent only. Our summary lists: Python 3; Node.js. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Bash(node:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Sentry Performance Tracing 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 Performance Tracing 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 Performance Tracing use?

Sentry Performance Tracing is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sentry Performance Tracing 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 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Sentry Performance Tracing?

Skills that share tags, products or a category with Sentry Performance Tracing: Sentry Miniapp SDK (lizhiyao/sentry-miniapp, 687 stars), Axiom Dashboard Builder (openclaw/clawhub, 9.5k stars), Happy Infra Metrics and Grafana (slopus/happy, 24k stars) and Axiom Cost Control (openclaw/clawhub, 9.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sentry Performance Tracing?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.