Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/arroyo-gonzalo/codex-devkit/performance-reviewnpx skills add Arroyo-Gonzalo/codex-devkit --skill performance-reviewgit clone --depth 1 https://github.com/Arroyo-Gonzalo/codex-devkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/arroyo-gonzalo/codex-devkit/performance-review)<a href="https://agentmods.dev/skills/arroyo-gonzalo/codex-devkit/performance-review"><img src="https://agentmods.dev/badge/skills/arroyo-gonzalo/codex-devkit/performance-review.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00042 | $0.00750 |
| Opus 5 | $0.00021 | $0.00375 |
| Sonnet 5 | $0.00008 | $0.00150 |
| Haiku 4.5 | $0.00004 | $0.00075 |
Grade A, and why
performance-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Review
Purpose
Identify measurable performance bottlenecks and recommend the smallest effective improvements.
Prefer evidence-driven optimization over speculation.
Do not optimize code without understanding the actual bottleneck.
Workflow
1. Understand the performance problem
Identify:
- expected performance;
- observed behavior;
- affected operation;
- execution frequency;
- affected users;
- environment;
- available measurements.
Avoid optimizing before understanding the problem.
2. Gather evidence
Inspect:
- profiling results;
- logs;
- execution time;
- database queries;
- network requests;
- browser performance tools;
- CPU usage;
- memory usage;
- I/O operations.
Base conclusions on evidence whenever possible.
3. Identify the bottleneck
Determine whether the bottleneck is primarily caused by:
- CPU;
- memory;
- disk;
- database;
- network;
- rendering;
- serialization;
- unnecessary computation;
- concurrency;
- external services.
Optimize the bottleneck, not unrelated code.
4. Review backend performance
Inspect:
- repeated queries;
- N+1 queries;
- blocking operations;
- synchronous work;
- unnecessary allocations;
- repeated serialization;
- excessive loops;
- duplicated business logic;
- caching opportunities.
Preserve correctness while improving performance.
5. Review database performance
Inspect:
- indexes;
- execution plans when available;
- joins;
- filtering;
- sorting;
- pagination;
- aggregation;
- transaction scope;
- locking.
Avoid unbounded queries.
Do not recommend indexes without understanding query patterns.
6. Review frontend performance
Inspect:
- unnecessary rendering;
- duplicated requests;
- large bundles;
- blocking operations;
- state updates;
- lazy loading opportunities;
- change detection impact;
- image loading.
Preserve user experience.
7. Review infrastructure
Consider:
- caching;
- compression;
- CDN usage;
- connection pooling;
- horizontal scaling;
- background jobs;
- queue usage;
- deployment configuration.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 222 lines · 42 tokens per session scan A 01a08428db9f
performance-review is a skill published in the GitHub repository Arroyo-Gonzalo/codex-devkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 750 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…