Scale Sentry for high-traffic applications handling millions of events per day.

MITAuto-check passedTesting & QA

Install Sentry Load Scale

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

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace sentry-load-scale --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-load-scale .claude/skills/sentry-load-scale && 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-load-scale
GitHub stars
2.8k
Token cost
~4.6k tokens
SKILL.md length
591 words
Files
7 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Scale Sentry for high-traffic applications handling millions of events per day.

  • Works in 3 steps: Implement Adaptive Sampling → Optimize SDK for Minimal Overhead → Manage Quotas, Test Under Load, and Plan…
  • Optimizing SDK performance at high volume
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 4 more sections
  • Calls npm

What it does

Sentry Load Scale is an agent skill from jeremylongshore/tons-of-skills-marketplace. Scale Sentry for high-traffic applications handling millions of events per day. Use when optimizing SDK performance at high volume, implementing adaptive sampling, managing quotas and costs at scale, or deploying Sentry across multi-region infrastructure. Trigger with phrases like "sentry high traffic", "scale sentry", "sentry millions events", "sentry high volume", "sentry quota management", "sentry load test".

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/buffering-and-batching.md`, `references/errors.md` and `references/examples.md`). Compatibility notes: Designed for Claude Code

It sits in Testing & QA, covering Load testing. 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

  • Optimizing SDK performance at high volume
  • Implementing adaptive sampling
  • Managing quotas and costs at scale
  • Deploying Sentry across multi-region infrastructure

Example prompts

  • “sentry high traffic”
  • “scale sentry”
  • “sentry millions events”
  • “/sentry-load-scale”

Requirements

  • Node.js
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Bash(node:*), Bash(npx:*), Bash(k6:*)

Workflow steps

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

  1. Implement Adaptive Sampling
  2. Optimize SDK for Minimal Overhead
  3. Manage Quotas, Test Under Load, and Plan for Scale

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:*)
    • Bash(npx:*)
    • Bash(k6:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm

    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
    • github.com
    • develop.sentry.dev
    • 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 Load Scale loads about 4.6k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 108 tokens; SKILL.md has 591 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~108
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.2k

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). 591 words, ~4,624 tokens.

Download SKILL.mdSave it as .claude/skills/sentry-load-scale/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
sentry-load-scale
description
Scale Sentry for high-traffic applications handling millions of events per day. Use when optimizing SDK performance at high volume, implementing adaptive sampling, managing quotas and costs at scale, or deploying Sentry across multi-region infrastructure. Trigger with phrases like "sentry high traffic", "scale sentry", "sentry millions events", "sentry high volume", "sentry quota management", "sentry load test".
allowed-tools
Read, Write, Edit, Grep, Bash(node:*), Bash(npx:*), Bash(k6:*)
compatibility
Designed for Claude Code
version
1.51.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, sentry, performance, scaling, high-traffic, enterprise

Sentry Load & Scale

Overview

Configure Sentry for applications processing 1M+ requests/day without sacrificing error visibility, burning through quota, or adding measurable SDK overhead. Covers adaptive sampling, connection pooling, multi-region tagging, quota management, SDK benchmarking, batch submission, load testing, and self-hosted deployment considerations.

Prerequisites

  • Application handling sustained high traffic (>10K requests/min or >1M events/day)
  • Sentry organization with quota and billing access (Settings > Subscription)
  • @sentry/node v8+ installed (npm ls @sentry/node)
  • Performance baseline established (p50/p95/p99 latency without Sentry)
  • Event volume estimates calculated per category (errors, transactions, replays, attachments)

Instructions

Step 1 — Implement Adaptive Sampling

Static tracesSampleRate wastes quota at scale because it treats a health check the same as a checkout. Replace it with a traffic-aware tracesSampler that adjusts rates based on endpoint criticality and current load.

Traffic-aware tracesSampler:

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

// Track request volume per endpoint for adaptive rate adjustment
const endpointVolume = new Map<string, { count: number; resetAt: number }>();
const WINDOW_MS = 60_000;

function getAdaptiveRate(name: string, baseRate: number): number {
  const now = Date.now();
  let entry = endpointVolume.get(name);

  if (!entry || now > entry.resetAt) {
    entry = { count: 0, resetAt: now + WINDOW_MS };
    endpointVolume.set(name, entry);
  }
  entry.count++;

  // Scale down sampling as volume increases within window
  // 0-100 req/min: full base rate
  // 100-1000: halve it
  // 1000+: quarter it
  if (entry.count > 1000) return baseRate * 0.25;
  if (entry.count > 100) return baseRate * 0.5;
  return baseRate;
}

Sentry.init({
  dsn: process.env.SENTRY_DSN,

  tracesSampler: (samplingContext) => {
    const { name, parentSampled } = samplingContext;

    // Always respect parent decision for distributed tracing consistency
    if (parentSampled !== undefined) return parentSampled ? 1.0 : 0;

    // Tier 0: Never sample — high-frequency, zero diagnostic value
    if (name?.match(/\/(health|ready|alive|ping|metrics|favicon)/)) return 0;
    if (name?.match(/\.(css|js|png|jpg|svg|woff2?|ico)$/)) return 0;

    // Tier 1: Always sample — business-critical, low volume
    if (name?.includes('/payment') || name?.includes('/checkout')) return 1.0;
    if (name?.includes('/auth/login')) return getAdaptiveRate('auth', 0.5);

    // Tier 2: Moderate sampling — API mutations (higher signal)
    if (name?.startsWith('POST /api/')) return getAdaptiveRate(name, 0.05);
    if (name?.startsWith('PUT /api/'))  return getAdaptiveRate(name, 0.05);
    if (name?.startsWith('DELETE /api/')) return getAdaptiveRate(name, 0.05);

    // Tier 3: Light sampling — API reads
    if (name?.startsWith('GET /api/')) return getAdaptiveRate(name, 0.02);

    // Tier 4: Background jobs — sample sparingly
    if (name?.startsWith('job:') || name?.startsWith('queue:')) {
      return getAdaptiveRate(name, 0.01);
    }

    // Tier 5: Everything else — minimal baseline
    return getAdaptiveRate(name || 'default', 0.005);
  },
});

Adaptive error deduplication with beforeSend:

typescript
// Reduce duplicate error volume by 90%+ while preserving first-occurrence fidelity
const errorCounts = new Map<string, number>();
const ERROR_WINDOW_MS = 60_000;

setInterval(() => errorCounts.clear(), ERROR_WINDOW_MS);

Sentry.init({
  dsn: process.env.SENTRY_DSN,

  beforeSend(event, hint) {
    const error = hint?.originalException;
    const key = error instanceof Error
      ? `${error.name}:${error.message?.substring(0, 100)}`
      : `unknown:${String(event.message || '').substring(0, 100)}`;

    const count = (errorCounts.get(key) || 0) + 1;
    errorCounts.set(key, count);

    // First occurrence: always send with full context
    if (count === 1) return event;

    // 2-10: send every 5th (capture ramp-up pattern)
    if (count <= 10) return count % 5 === 0 ? event : null;

    // 11-100: send every 25th (confirm still happening)
    if (count <= 100) return count % 25 === 0 ? event : null;

    // 100+: send every 100th (volume indicator only)
    return count % 100 === 0 ? event : null;
  },
});
Step 2 — Optimize SDK for Minimal Overhead

At high throughput, every byte and every millisecond of SDK processing matters. This configuration reduces memory footprint, payload size, and CPU time.

Lean SDK initialization:

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

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  environment: process.env.NODE_ENV || 'production',
  release: `${process.env.SERVICE_NAME}@${process.env.VERSION || 'unknown'}`,

  // --- Memory reduction ---
  maxBreadcrumbs: 15,          // Down from 100 default; saves ~85KB/scope
  maxValueLength: 200,         // Truncate long string values

  // --- Disable high-overhead integrations ---
  integrations: (defaults) => defaults.filter(i =>
    !['Console', 'ContextLines'].includes(i.name)
  ),

  // --- No profiling at high scale (use dedicated APM if needed) ---
  profilesSampleRate: 0,

  // --- Transport tuning for high-throughput ---
  transportOptions: {
    bufferSize: 100,           // Default 64; absorbs traffic spikes
  },

  // --- Context size limiter ---
  beforeSend(event) {
    // Truncate oversized contexts to prevent payload bloat
    if (event.contexts) {
      for (const [key, ctx] of Object.entries(event.contexts)) {
        const str = JSON.stringify(ctx);
        if (str.length > 2000) {
          event.contexts[key] = { _truncated: true, originalSize: str.length };
        }
      }
    }

    // Strip headers that add bulk without diagnostic value
    if (event.request?.headers) {
      const keep = ['content-type', 'accept', 'user-agent', 'x-request-id'];
      event.request.headers = Object.fromEntries(
        Object.entries(event.request.headers)
          .filter(([k]) => keep.includes(k.toLowerCase()))
      );
    }

    return event;
  },

  // --- Multi-region tags for infrastructure visibility ---
  serverName: process.env.HOSTNAME || process.env.POD_NAME || os.hostname(),
  initialScope: {
    tags: {
      region: process.env.AWS_REGION || process.env.GCP_REGION || 'unknown',
      cluster: process.env.K8S_CLUSTER || 'default',
      pod: process.env.POD_NAME || 'unknown',
      service: process.env.SERVICE_NAME || 'unknown',
    },
  },
});

Graceful shutdown ensuring event delivery:

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

async function shutdown(signal: string) {
  console.log(`${signal} received — flushing Sentry events`);

  // Stop accepting new requests
  server.close();

  // Flush all pending events (2s timeout prevents hanging deploys)
  const flushed = await Sentry.close(2000);
  if (!flushed) {
    console.warn('Sentry flush timed out — some events may be lost');
  }

  process.exit(0);
}

process.on('SIGTERM', () => shutdown('SIGTERM'));
process.on('SIGINT',  () => shutdown('SIGINT'));
Step 3 — Manage Quotas, Test Under Load, and Plan for Scale

Quota management and reserved volume pricing:

Application: 10M requests/day, 0.1% error rate, @sentry/node v8

Error events (with adaptive beforeSend):
  Raw errors:     10M x 0.001 = 10,000/day
  After dedup:    ~1,000/day (90% reduction)        = 30K/month

Transaction events (with tiered tracesSampler):
  Health/static:  0% of 4M    = 0
  Payment (T1):   100% of 5K  = 5,000/day
  POST API (T2):  5% of 500K  = 25,000/day
  GET API (T3):   2% of 5M    = 100,000/day
  Other (T5):     0.5% of 500K = 2,500/day
  Total:                        ~132K/day            = 4M/month

Sentry Business plan ($26/mo base):
  Errors:       30K included in base plan
  Transactions: 100K included, overage 3.9M x $0.000025 = ~$97/mo
  Estimated total: ~$123/month for 10M requests/day

Reserved volume (if predictable traffic):
  5M txns/mo reserved = $80/mo (vs $97 on-demand)
  Saves ~$17/mo, locks in price for 12 months
  → Total: ~$106/month

SDK overhead benchmarks:

typescript
// Measure SDK initialization cost
const initStart = performance.now();
Sentry.init({ /* ... */ });
const initMs = performance.now() - initStart;
console.log(`Sentry.init: ${initMs.toFixed(1)}ms`);
// Expected: 5-15ms (Node.js), acceptable <50ms

// Measure per-request overhead with Sentry vs without
import { performance, PerformanceObserver } from 'node:perf_hooks';

async function benchmarkOverhead(iterations: number = 1000) {
  // Baseline: request without Sentry instrumentation
  const baseStart = performance.now();
  for (let i = 0; i < iterations; i++) {
    await handleRequest({ path: '/api/test', method: 'GET' });
  }
  const baseMs = (performance.now() - baseStart) / iterations;

  // Instrumented: request with Sentry span
  const sentryStart = performance.now();
  for (let i = 0; i < iterations; i++) {
    await Sentry.startSpan(
      { name: 'GET /api/test', op: 'http.server' },
      () => handleRequest({ path: '/api/test', method: 'GET' })
    );
  }
  const sentryMs = (performance.now() - sentryStart) / iterations;

  console.log(`Baseline: ${baseMs.toFixed(3)}ms/req`);
  console.log(`With Sentry: ${sentryMs.toFixed(3)}ms/req`);
  console.log(`Overhead: ${(sentryMs - baseMs).toFixed(3)}ms (${(((sentryMs - baseMs) / baseMs) * 100).toFixed(1)}%)`);
  // Healthy: <0.5ms overhead per request, <2% CPU impact
}

Load testing Sentry integration with k6:

javascript
// k6-sentry-load-test.js
// Run: k6 run --vus 100 --duration 5m k6-sentry-load-test.js
import http from 'k6/http';
import { check, sleep } from 'k6';
import { Rate, Trend } from 'k6/metrics';

const errorRate = new Rate('sentry_errors_captured');
const latencyOverhead = new Trend('sentry_latency_overhead_ms');

export const options = {
  stages: [
    { duration: '1m', target: 50 },    // Ramp up
    { duration: '3m', target: 200 },   // Sustained load
    { duration: '1m', target: 0 },     // Ramp down
  ],
  thresholds: {
    http_req_duration: ['p(95)<500'],   // p95 under 500ms with Sentry
    sentry_latency_overhead_ms: ['p(95)<5'], // Sentry adds <5ms at p95
  },
};

const BASE_URL = __ENV.BASE_URL || 'http://localhost:3000';

export default function () {
  // Normal traffic: API reads (high volume, low sample rate)
  const readRes = http.get(`${BASE_URL}/api/products`);
  check(readRes, { 'GET 200': (r) => r.status === 200 });

  // Track overhead via server timing header (if exposed)
  const sentryMs = readRes.headers['Server-Timing']?.match(/sentry;dur=(\d+\.?\d*)/);
  if (sentryMs) latencyOverhead.add(parseFloat(sentryMs[1]));

  // Occasional writes (lower volume, higher sample rate)
  if (Math.random() < 0.1) {
    const writeRes = http.post(`${BASE_URL}/api/orders`, JSON.stringify({
      items: [{ sku: 'TEST-001', qty: 1 }],
    }), { headers: { 'Content-Type': 'application/json' } });
    check(writeRes, { 'POST 201': (r) => r.status === 201 });
  }

  // Trigger errors (verify Sentry captures under load)
  if (Math.random() < 0.01) {
    const errRes = http.get(`${BASE_URL}/api/nonexistent-route`);
    errorRate.add(errRes.status === 404);
  }

  sleep(0.1);
}

Background worker batch patterns:

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

// For queue workers processing millions of jobs/day
async function processJobBatch(jobs: Job[]) {
  // Group jobs for batch-level tracing instead of per-job spans
  return Sentry.startSpan(
    {
      name: `batch.${jobs[0]?.type || 'unknown'}`,
      op: 'queue.batch',
      attributes: { 'batch.size': jobs.length },
    },
    async () => {
      const results = { success: 0, failed: 0 };

      for (const job of jobs) {
        try {
          await Sentry.withScope(async (scope) => {
            scope.setTag('job.type', job.type);
            scope.setTag('job.queue', job.queue);
            scope.setContext('job', {
              id: job.id,
              attempts: job.attempts,
            });
            await executeJob(job);
            results.success++;
          });
        } catch (error) {
          results.failed++;
          Sentry.captureException(error, {
            tags: { 'job.id': job.id, 'job.type': job.type },
            level: job.attempts >= 3 ? 'error' : 'warning',
          });
        }
      }

      Sentry.setMeasurement('batch.success_rate',
        results.success / jobs.length, 'ratio');
      return results;
    }
  );
}

// Periodic flush for long-running workers (don't rely on process exit)
setInterval(async () => {
  await Sentry.flush(2000);
}, 30_000);

Self-hosted Sentry for enterprise (>100M events/month):

Key tuning for self-hosted (docker-compose.override.yml on top of getsentry/self-hosted):

  • Relay: RELAY_PROCESSING_MAX_RATE: 50000, RELAY_UPSTREAM_MAX_CONNECTIONS: 200
  • Kafka: KAFKA_NUM_PARTITIONS: 32 (match to consumer count)
  • Snuba: 4+ consumer replicas for Clickhouse ingestion parallelism
  • Clickhouse: 16G+ RAM, dedicated SSD volumes
Self-hosted vs SaaS break-even:
  SaaS at 100M events/month:     ~$2,500/mo (Business plan + overage)
  Self-hosted (3x r6g.2xlarge):  ~$1,200/mo infra + $800/mo ops (0.25 FTE)
  Break-even: ~50M events/month
  → Use SaaS up to 50M events; evaluate self-hosted above that

Output

  • Adaptive sampling reducing duplicate error volume by 90%+ while preserving first-occurrence fidelity
  • Traffic-aware tracesSampler with 5 tiers adjusting dynamically based on endpoint volume
  • SDK memory and CPU footprint minimized (15 breadcrumbs, truncated contexts, filtered headers)
  • Connection pooling via persistent HTTPS agent for efficient event submission
  • Multi-region infrastructure tags for filtering by region/cluster/pod in Sentry dashboard
  • Cost model with reserved volume pricing showing $106/month for 10M requests/day
  • k6 load test script validating Sentry overhead stays under 5ms at p95
  • Batch job processing pattern with scope isolation and periodic flush
  • Self-hosted vs SaaS break-even analysis for enterprise decision-making
Show full SKILL.md (255 more words)Show less

Error Handling

ErrorCauseSolution
Events silently droppedSDK buffer full during traffic spikeIncrease transportOptions.bufferSize to 200+, verify network to Sentry ingest
429 rate limit from SentryQuota exhausted or spike protection triggeredEnable spike protection in Settings > Subscription, reduce sample rates
Memory growing linearly over timeBreadcrumb or scope accumulationReduce maxBreadcrumbs, verify withScope is used (not configureScope)
Lost events on deploy/restartNo Sentry.close() in shutdown handlerAdd SIGTERM/SIGINT handlers calling Sentry.close(2000)
Distributed traces broken at scaleMixed sampling decisions across servicesAlways check parentSampled first in tracesSampler
Clickhouse OOM on self-hostedInsufficient memory for event volumeAllocate 16G+ RAM, increase Snuba consumer replicas
k6 shows >5ms Sentry overheadToo many integrations or large payloadsDisable Console/ContextLines integrations, reduce maxValueLength
Quota burn from replay/attachmentsReplays not rate-limited separatelySet replaysSessionSampleRate: 0.01 and replaysOnErrorSampleRate: 0.1

Examples

Minimal high-scale init (copy-paste ready):

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

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  environment: process.env.NODE_ENV,
  release: `${process.env.SERVICE_NAME}@${process.env.VERSION}`,
  maxBreadcrumbs: 15,
  maxValueLength: 200,
  profilesSampleRate: 0,
  tracesSampler: ({ name, parentSampled }) => {
    if (parentSampled !== undefined) return parentSampled ? 1.0 : 0;
    if (name?.match(/\/(health|ping|metrics)/)) return 0;
    if (name?.includes('/payment')) return 1.0;
    if (name?.startsWith('POST /api/')) return 0.05;
    return 0.005;
  },
});

Verify sampling is working as expected:

typescript
// Add to non-production environments temporarily
Sentry.init({
  // ... config ...
  tracesSampler: (ctx) => {
    const rate = calculateRate(ctx); // your logic
    if (process.env.DEBUG_SENTRY === 'true') {
      console.log(`[sentry] ${ctx.name} → rate=${rate}`);
    }
    return rate;
  },
});

Resources

Next Steps

  • Run the k6 load test against staging to establish your baseline Sentry overhead
  • Set up Sentry Spike Protection (Settings > Subscription > Spike Protection) before going to production
  • Configure server-side sampling rules in Sentry Dynamic Sampling (Project Settings > Performance) to complement client-side tracesSampler
  • Create a Sentry dashboard with widgets for: events/hour by category, quota usage %, p95 SDK overhead
  • Review the sentry-cost-tuning skill for detailed quota optimization strategies

© 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 6 other files (references) in skills/.curated/sentry-load-scale of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/buffering-and-batching.md
  • references/errors.md
  • references/examples.md
  • references/high-volume-sampling-strategies.md
  • references/quota-management-at-scale.md
  • references/resource-optimization.md

Open the folder on GitHubat commit cfae287

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    jeremylongshore/tons-of-skills-marketplace

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Questions about Sentry Load Scale

What does Sentry Load Scale do?

Scale Sentry for high-traffic applications handling millions of events per day. Sentry Load Scale is an agent skill from jeremylongshore/tons-of-skills-marketplace. Scale Sentry for high-traffic applications handling millions of events per day.

When should I use Sentry Load Scale?

Sentry Load Scale fits situations like: optimizing SDK performance at high volume; implementing adaptive sampling; managing quotas and costs at scale; deploying Sentry across multi-region infrastructure.

How do I install Sentry Load Scale in Claude Code?

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

How do I install Sentry Load Scale in Codex?

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

Can I use Sentry Load Scale 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-load-scale -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-load-scale, .gemini/skills/sentry-load-scale, .github/skills/sentry-load-scale and .opencode/skills/sentry-load-scale in your project.

What does Sentry Load Scale need to run?

Going by SKILL.md and its folder, Sentry Load Scale needs the command-line tools its instructions call (npm). Our summary lists: Node.js. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Bash(node:*), Bash(npx:*), Bash(k6:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Sentry Load Scale access the network?

SKILL.md names 4 domains. As links in the text: docs.sentry.io, github.com, develop.sentry.dev and sentry.io. This is read from the text; nothing was executed.

Is Sentry Load Scale 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 Load Scale use?

Sentry Load Scale 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 Load Scale use?

About 4.6k tokens (SKILL.md is roughly 18k 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 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Sentry Load Scale?

Skills that share tags, products or a category with Sentry Load Scale: Writing Livekit Scenarios (livekit-examples/agent-starter-python, 264 stars), Go Testing (cxuu/golang-skills, 173 stars), Goalcraft (grp06/goalcraft, 102 stars) and Thinking Partner (mattnowdev/thinking-partner, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sentry Load Scale?

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.