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Get Started Free →Create a complete Sentry SDK skill bundle for any platform. Use when asked to \"create an SDK skill\", \"add a new platform skill\", \"write a Sentry skill for X\", or build a new sentry-<platform>-sdk skill bundle with wizard flow and feature reference files.
.claude/skills/kunanonj-cursor-plugin-sentry-sentry-sdk-skill-creator/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 124% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 192% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 127% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 133% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 190% | 0% |
> All Skills > SDK Skill Creator
Produce a complete, research-backed SDK skill bundle — a main wizard SKILL.md plus deep-dive reference files for every feature pillar the SDK supports.
sentry-<platform>-sdk skill bundle> Read ${SKILL_ROOT}/references/philosophy.md first — it defines the bundle architecture, wizard flow, and design principles this skill implements.
Determine what you're building a skill for:
bash# What SDK? What's the package name? # Examples: sentry-go, @sentry/sveltekit, sentry-python, sentry-ruby, sentry-cocoa
Establish the feature matrix — which Sentry pillars does this SDK support?
| Pillar | Check docs | Notes | |--------|-----------|-------| | Error Monitoring | Always available | Non-negotiable baseline | | Tracing/Performance | Usually available | Check for span API | | Profiling | Varies | May be removed or experimental | | Logging | Newer feature | Check minimum version | | Metrics | Newer feature | Check minimum version | | Crons | Backend only | Not available for frontend SDKs | | Session Replay | Frontend only | Not available for backend SDKs | | AI Monitoring | Some SDKs | Usually JS + Python only |
Reference existing SDK skills to understand the target quality level:
bashls skills/sentry-*-sdk/ 2>/dev/null # Read 1-2 existing SDK skills for pattern reference
This is the most critical phase. Skill quality depends entirely on accurate, current API knowledge. Do NOT write skills from memory — research every feature against official docs.
Spin off parallel research tasks (using the claude tool with outputFile) — one per feature area. Each task should:
Read ${SKILL_ROOT}/references/research-playbook.md for the detailed research execution plan, including prompt templates and file naming conventions.
Before diving into feature research, check whether the Sentry wizard CLI supports this framework:
bash# Check the SDK's docs landing page for wizard instructions # Visit: https://docs.sentry.io/platforms/<platform>/ # Look for: "npx @sentry/wizard@latest -i <integration>"
If a wizard integration exists:
-i flag> Why this matters: The wizard handles the entire auth flow (login, org/project selection, > auth token) and source map upload configuration automatically. Without source maps, > production stack traces show minified code — making Sentry nearly useless for frontend > debugging. And without the auth token, source maps can't be uploaded at all. The wizard > is the most reliable way to get both right in a single step.
Batch research tasks by topic area. Run them in parallel where possible:
| Batch | Topics | Output file | |-------|--------|-------------| | 1 | Setup, configuration, all init options, framework detection | research/<sdk>-setup-config.md | | 2 | Error monitoring, panic/exception capture, scopes, enrichment | research/<sdk>-error-monitoring.md | | 3 | Tracing, profiling (if supported) | research/<sdk>-tracing-profiling.md | | 4 | Logging, metrics, crons (if supported) | research/<sdk>-logging-metrics-crons.md | | 5 | Session replay (frontend only), AI monitoring (if supported) | research/<sdk>-replay-ai.md |
Important: Tell each research task to write its output to a file (outputFile parameter). Do NOT consume research results inline — they're large (500–1200 lines each). Workers will read them from disk later.
Before proceeding, verify each research file:
bash# Quick verification for f in research/<sdk>-*.md; do echo "=== $(basename $f) ===" wc -l "$f" grep -c "^#" "$f" # should have multiple headings done
Re-run any research task that produced fewer than 100 lines — it likely failed silently.
The main SKILL.md implements the four-phase wizard from the philosophy doc. Keep it focused — the main file should cover the wizard flow, quick start config, framework tables, and reference dispatch. Deep-dive details for individual features belong in references/ files, not here. Be thorough but not redundant.
Before writing, run a scout or read existing skills to understand conventions:
markdown--- name: sentry-<platform>-sdk description: Full Sentry SDK setup for <Platform>. Use when asked to "add Sentry to <platform>", "install <package>", or configure error monitoring, tracing, [features] for <Platform> applications. Supports [frameworks]. license: Apache-2.0 --- # Sentry <Platform> SDK ## Invoke This Skill When [trigger phrases] ## Phase 1: Detect [bash commands to scan project — package manager, framework, existing Sentry, frontend/backend] ## Phase 2: Recommend [opinionated feature matrix with "always / when detected / optional" logic] ## Phase 3: Guide ### Option 1: Wizard (Recommended) ← if wizard exists for this framework [blockquote telling the user to run the wizard themselves — it requires interactive browser login. Include the command in a copy-pasteable code block inside the blockquote. Tell them to come back when done. Add a line after the blockquote: "If the user skips the wizard, proceed with Option 2 (Manual Setup) below."] ### Option 2: Manual Setup ← always include ### Install ### Quick Start — Recommended Init ### Source Maps Setup ← required for frontend/mobile SDKs ### Framework Middleware (if applicable) ### For Each Agreed Feature [reference dispatch table: feature → ${SKILL_ROOT}/references/<feature>.md] ## Configuration Reference [key init options table, environment variables] ## Verification [test snippet] ## Phase 4: Cross-Link [detect companion frontend/backend, suggest matching SDK skills] ## Troubleshooting [common issues table]
${SKILL_ROOT}/references/philosophy.md for the full pattern.One reference file per feature pillar the SDK supports. These are deep dives — they can be longer than the main SKILL.md.
markdown# <Feature> — Sentry <Platform> SDK > Minimum SDK: `<package>` vX.Y.Z+ ## Configuration ## Code Examples ### Basic usage ### Advanced patterns ### Framework-specific notes (if applicable) ## Best Practices ## Troubleshooting | Issue | Solution | |-------|----------|
Read ${SKILL_ROOT}/references/quality-checklist.md for the full quality rubric.
Key points:
| Feature | Key things to cover | |---------|-------------------| | Error Monitoring | Capture APIs, panic/exception recovery, scopes, enrichment (tags/user/breadcrumbs), error chains, BeforeSend, fingerprinting | | Tracing | Sample rates, custom spans, distributed tracing, framework middleware, operation types | | Profiling | Sample rate config, how it attaches to traces, or honest "removed/not available" | | Logging | Enable flag, logger API, integration with popular logging libraries, filtering | | Metrics | Counter/gauge/distribution APIs, units, attributes, best practices for cardinality | | Crons | Check-in API, monitor config, schedule types, heartbeat patterns | | Session Replay | Replay integration, sample rates, privacy masking, canvas/network recording |
> Note for frontend/mobile SDKs: Source map upload configuration belongs in the main SKILL.md (Phase 3: Guide), not in a reference file. It's part of the core setup flow — every frontend production deployment needs it. Cover the build tool plugin, the required env vars (SENTRY_AUTH_TOKEN, SENTRY_ORG, SENTRY_PROJECT), and add .env to .gitignore.
Do NOT skip this phase. SDK APIs change frequently. Research can hallucinate. Workers can fabricate config keys.
Run a dedicated verification pass against the SDK's actual source code:
Research prompt: "Verify these specific API names and signatures against
the <SDK> GitHub repo source code: [list every API from the skill files]"Things that commonly go wrong:
SendDefaultPii vs SendDefaultPII)experimental.tracing — verify it's real)configureScope → getIsolationScope)Run a reviewer on the complete skill bundle:
Triage by priority:
After the skill passes review:
Each major piece gets its own commit:
feat(<platform>-sdk): add sentry-<platform>-sdk main SKILL.md wizardfeat(<platform>-sdk): add reference deep-dives for all feature pillarsdocs(readme): add sentry-<platform>-sdk to available skillsfix(skills): address review findings (if any)Before declaring the skill complete:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 32,903 | 6,217 | -81% | 1 | 1 | 0% | 6,226 | 3,604 | -42% | 0 | 0 | — |
case-02 | fail→fail | 24,669 | 5,622 | -77% | 1 | 1 | 0% | 5,081 | 3,486 | -31% | 0 | 0 | — |
case-03 | fail→fail | 27,211 | 5,861 | -78% | 1 | 1 | 0% | 5,740 | 3,734 | -35% | 0 | 0 | — |
case-04 | fail→pass | 12,792 | 7,267 | -43% | 1 | 1 | 0% | 2,036 | 4,563 | +124% | 0 | 0 | — |
case-05 | fail→pass | 7,797 | 4,786 | -39% | 1 | 1 | 0% | 1,395 | 4,073 | +192% | 0 | 0 | — |
case-06 | pass→pass | 10,030 | 6,597 | -34% | 1 | 1 | 0% | 1,878 | 4,558 | +143% | 0 | 0 | — |
case-07 | fail→pass | 10,046 | 4,357 | -57% | 1 | 1 | 0% | 1,820 | 4,137 | +127% | 0 | 0 | — |
case-08 | pass→pass | 9,611 | 6,308 | -34% | 1 | 1 | 0% | 1,793 | 4,387 | +145% | 0 | 0 | — |
case-09 | fail→pass | 10,780 | 5,247 | -51% | 1 | 1 | 0% | 1,770 | 4,124 | +133% | 0 | 0 | — |
case-10 | pass→pass | 12,426 | 11,433 | -8% | 1 | 1 | 0% | 2,370 | 5,392 | +128% | 0 | 0 | — |
case-11 | pass→pass | 10,766 | 15,574 | +45% | 1 | 1 | 0% | 2,165 | 5,759 | +166% | 0 | 0 | — |
case-12 | pass→pass | 12,230 | 15,351 | +26% | 1 | 1 | 0% | 2,070 | 6,161 | +198% | 0 | 0 | — |
case-13 | pass→pass | 10,173 | 5,324 | -48% | 1 | 1 | 0% | 1,821 | 4,236 | +133% | 0 | 0 | — |
case-14 | pass→pass | 25,284 | 1,895 | -93% | 1 | 1 | 0% | 2,379 | 3,537 | +49% | 0 | 0 | — |
case-15 | fail→pass | 7,814 | 3,152 | -60% | 1 | 1 | 0% | 1,324 | 3,840 | +190% | 0 | 0 | — |
case-16 | pass→pass | 5,002 | 3,501 | -30% | 1 | 1 | 0% | 863 | 3,879 | +349% | 0 | 0 | — |
case-17 | pass→pass | 10,090 | 6,249 | -38% | 1 | 1 | 0% | 1,633 | 4,305 | +164% | 0 | 0 | — |
case-18 | fail→pass | 13,592 | 2,153 | -84% | 1 | 1 | 0% | 2,215 | 3,626 | +64% | 0 | 0 | — |
case-19 | pass→pass | 5,066 | 2,642 | -48% | 1 | 1 | 0% | 889 | 3,638 | +309% | 0 | 0 | — |
case-20 | pass→pass | 7,018 | 1,453 | -79% | 1 | 1 | 0% | 1,140 | 3,520 | +209% | 0 | 0 | — |
case-21 | fail→pass | 7,594 | 2,776 | -63% | 1 | 1 | 0% | 1,222 | 3,752 | +207% | 0 | 0 | — |
case-22 | fail→pass | 8,949 | 2,011 | -78% | 1 | 1 | 0% | 1,378 | 3,566 | +159% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +36 percentage points is the difference between those two pass rates over the 19 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.