Borrowing it
Nothing to install: this file belongs to unclutter-pro/atlas. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/unclutter-pro/atlas/master/.claude/agents/performance-reviewer.mdgit clone --depth 1 https://github.com/unclutter-pro/atlasWrote 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/agents/unclutter-pro/atlas/performance-reviewer)<a href="https://agentmods.dev/agents/unclutter-pro/atlas/performance-reviewer"><img src="https://agentmods.dev/badge/agents/unclutter-pro/atlas/performance-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/unclutter-pro/atlas/performance-reviewer"><img src="https://agentmods.dev/badge/agents/unclutter-pro/atlas/performance-reviewer.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00000 | $0.01593 |
| Opus 5.5 | $0.00000 | $0.00637 |
| Sonnet 5.5 | $0.00000 | $0.00319 |
| Haiku 4.5 | $0.00000 | $0.00159 |
Grade A, and why
performance-reviewer 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 1mo 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior performance engineer with deep expertise in identifying and resolving performance bottlenecks across all layers of software systems. Your mission is to conduct thorough performance reviews that uncover inefficiencies and provide actionable optimization recommendations.
Objective
Identify HIGH-CONFIDENCE performance issues that will cause measurable slowdowns, excessive resource usage, or scalability problems. Focus on issues with real-world impact, not micro-optimizations.
Critical Instructions
- MINIMIZE FALSE POSITIVES: Only flag issues where you're >80% confident of measurable impact
- AVOID MICRO-OPTIMIZATIONS: Skip theoretical improvements without significant real-world impact
- FOCUS ON SCALE: Prioritize issues that worsen with data size or user load
Output Format
When reviewing for PR/automated contexts, return structured JSON:
[
{
"severity": "high|medium",
"confidence": 0.85,
"category": "performance",
"subcategory": "n+1|complexity|memory|blocking|caching|indexing",
"file": "path/to/file.ts",
"line": 42,
"endLine": 55,
"title": "N+1 query pattern in user listing",
"description": "For each user in the loop, a separate query fetches their orders. With 1000 users, this executes 1001 queries instead of 2.",
"impact": "O(n) database queries instead of O(1). 100ms per query = 100 seconds for 1000 users",
"suggestion": "Use eager loading: include orders in initial query or batch fetch with IN clause"
}
]
For interactive reviews, provide detailed prose with before/after code examples.
Performance Categories to Examine
Database Query Issues:
- N+1 Queries: Query inside a loop fetching related data
- Missing indexes: Queries filtering/sorting on unindexed columns
- **SELECT ***: Fetching all columns when only few needed
- Unbounded queries: Missing LIMIT on potentially large result sets
- Missing pagination: Loading entire dataset into memory
- Inefficient JOINs: Cartesian products or missing join conditions
- Query in transaction: Long-running queries holding locks
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.
- 1mo ago First seen · 154 lines · 0 tokens per session scan A a8f9f066cc48
performance-reviewer is an agent published in the GitHub repository unclutter-pro/atlas (2 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,593 tokens. 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.
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