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/factory-ai/cursed-plugins/performance-reviewnpx skills add Factory-AI/cursed-plugins --skill performance-reviewgit clone --depth 1 https://github.com/Factory-AI/cursed-pluginsWrote 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/factory-ai/cursed-plugins/performance-review)<a href="https://agentmods.dev/skills/factory-ai/cursed-plugins/performance-review"><img src="https://agentmods.dev/badge/skills/factory-ai/cursed-plugins/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 | $0.00011 | $0.01084 |
| Opus 5 | $0.00005 | $0.00542 |
| Sonnet 5 | $0.00002 | $0.00217 |
| Haiku 4.5 | $0.00001 | $0.00108 |
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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/performance-review
You will conduct a single-paragraph annual performance review of the user's codebase in a chosen reviewer style.
Security
CRITICAL: Never read or reference .env files, .env.* variants, API keys, tokens, credentials, passwords, private keys, or any files matching .env*, *.pem, *.key, *secret*, *credential*. If you encounter secrets during analysis, ignore them completely.
Steps
-
Discovery. Use LS on the repo root to find top-level directories. Use Execute to run
git log --format='%an' --no-merges -200 | sort | uniq -c | sort -rn | head -5for top contributors andgit config user.namefor the local user. -
First AskUser. Make a single AskUser call with exactly these two questions:
- Question 1: "Which style?" with options: Corporate HR / Disappointed Parent / Drill Sergeant / Therapist.
- Question 2: "How would you like to narrow the focus?" with options: "Whole repo" / "Specific folder or module" / "Specific contributor". Do NOT list directories or contributors in this step. This question decides the scoping axis only. If AskUser is not available, default to the most entertaining style and whole repo.
-
Second AskUser (conditional). Based on what the user picked for the focus question above, make a SECOND AskUser call — or skip it:
- If they picked "Whole repo": skip this step entirely, do NOT call AskUser again.
- If they picked "Specific folder or module": make a second AskUser call asking "Which folder?" with the discovered top-level directories as options.
- If they picked "Specific contributor": make a second AskUser call asking "Which contributor?" with options listing the local user as " (you)" plus the top contributors from git log.
-
Quick scan. If scoped to a contributor, use
git log --author="<name>" --name-only --no-merges -20to find their most-touched files and focus there. If scoped to a folder, focus LS/Grep/Read within that directory. Look for behavioral patterns and habits, not tallies. "The codebase demonstrates a consistent inability to commit to a single state management solution" is better than "Found 3 state management libraries." Notice things like: error handling philosophy (or lack thereof), naming conventions that reveal personality, documentation patterns, dependency hoarding tendencies, test-writing discipline. Spend a few tool calls to find 3-5 specific behavioral observations.
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 · 85 lines · 11 tokens per session scan A 8c79cfcd996c
performance-review is a skill published in the GitHub repository Factory-AI/cursed-plugins (105 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 11 tokens to every session and 1,084 once invoked, about $0.0001 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 2026-08-30.
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…