performance-profiler
Skill2 starsChanged 28 days agoApache-2.0View on GitHub
Profiles application latency, CPU usage, memory leaks, and database bottlenecks. Use when diagnosing slow response times, high resource consumption, or memory leaks.
21 other projects use a version of this.
Adopted by
Most recently taken up by
- darkweb19/skillstheir own version, first seen Nov 8, 2026
- kazemcodes/skill-treetheir own version, first seen Nov 8, 2026
- Vinix24/vnx-orchestrationtheir own version, first seen Nov 6, 2026
- k1lgor/virtual-companytheir own version, first seen Nov 1, 2026
- jaskirat1616/grok-skillstheir own version, first seen Nov 1, 2026
- JayRHa/agent-skillstheir own version, first seen Oct 15, 2026
Other versions21 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 21
- OneWave-AI/claude-skills★ 378same name
- mar-antaya/my-claude-skills★ 148same name
- Vinix24/vnx-orchestration★ 63same name
- jaskirat1616/grok-skills★ 22same name
- Hassaan146/claude-skills★ 18same name
- JayRHa/agent-skills★ 12same name
- JayRHa/AgentSkills★ 12same name
- k1lgor/virtual-company★ 4same name
- DeRuiChen258/RL_Infra_skills-openAI★ 3same name
- csiddhant796-blip/claude-skills-collection★ 2same name
11 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository108 other files it gives its agents.
- AGENTS.mdAGENTS.md
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- argon-visual-critique-loopSkill
- argo-workflowsSkill
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- cilium-ebpf-networkingSkill
- clickhouse-analyticsSkill
- cloud-deploy-canarySkill
- cloudflare-r2-object-storageSkill
- cloudflare-workersSkill
- cloud-run-agentsSkill
- context-cachingSkill
- context-distillation-compressorSkill
- context-warmerSkill
- continuous-learningSkill
- cost-oracle-finopsSkill
- cross-repo-swarm-syncSkill
- cve-remediation-orchestratorSkill
- database-architectSkill
- dataproc-spark-analyticsSkill
- dbt-transformationSkill
- debezium-cdcSkill
- devops-pipelineSkill
- distributed-rate-limitingSkill
- docker-compose-orchestratorSkill
- duckdb-local-olapSkill
- dynamic-thinking-allocationSkill
- ebpf-microvm-sandboxSkill
- ebpf-sandbox-enforcerSkill
- elephant-goldfish-modelSkill
- envoy-ai-gatewaySkill
- ephemeral-swarm-orchestratorSkill
- fastapi-productionSkill
- fullstack-nextjsSkill
- game-audio-synthesizerSkill
- game-studioSkill
- gemini-function-callingSkill
- gemini-groundingSkill
- gemini-live-audio-transcriberSkill
- gemini-live-multimodalSkill
- gemini-live-screen-visionSkill
- gemini-multimodalSkill
- genetic-prompt-cross-pollinatorSkill
- git-craftsmanSkill
- github-opsSkill
- google-axSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 1 is distinctive, and 2 are very specific to this project.
0
Common
Most of the 9 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 20
Run Node with the V8 sampling profiler:
- Very specific: line 27
PostgreSQL: Run EXPLAIN (ANALYZE, BUFFERS) <query> to inspect sequential scans, join types, and execution time.
- Very specific: line 28
Indexes: Verify that high-cardinality WHERE and JOIN columns have appropriate B-Tree or Hash indexes.
“Common” is measured: kept by at least 6 in 10 of the 9 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Performance Profiler
This skill guides the agent through systematic latency and resource bottleneck profiling.
Profiling Workflow
1. Identify the Bottleneck Metric
Determine the performance symptom:
- High CPU: Algorithmic complexity ($O(n^2)$), tight loops, excessive JSON serialization.
- High Memory / Leak: Retained closures, unclosed database streams, unbounded in-memory caches.
- High Latency (I/O): N+1 database queries, unindexed SQL lookups, synchronous blocking disk I/O.
2. Node.js & V8 Profiling
Run Node with the V8 sampling profiler:
node --prof app.js
node --prof-process isolate-*.log > processed.txt3. Database Query Analysis
- PostgreSQL: Run
EXPLAIN (ANALYZE, BUFFERS) <query>to inspect sequential scans, join types, and execution time. - Indexes: Verify that high-cardinality
WHEREandJOINcolumns have appropriate B-Tree or Hash indexes.
4. Memory Heap Dumps
Capture heap snapshots or track memory diffs between iterations to isolate leaks:
const mem = process.memoryUsage();
console.log(`Heap Used: ${Math.round(mem.heapUsed / 1024 / 1024)} MB`);Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

