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 skills add wyattowalsh/agents --skill performance-profilergit clone --depth 1 https://github.com/wyattowalsh/agentsWrote 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/wyattowalsh/agents/performance-profiler)<a href="https://agentmods.dev/skills/wyattowalsh/agents/performance-profiler"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/performance-profiler/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/skills/wyattowalsh/agents/performance-profiler"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/performance-profiler.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 | $0.00037 | $0.02464 |
| Opus 5.5 | $0.00015 | $0.00986 |
| Sonnet 5.5 | $0.00007 | $0.00493 |
| Haiku 4.5 | $0.00004 | $0.00246 |
Grade A, and why
performance-profiler 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Profiler
Analysis-based performance review. Every recommendation grounded in evidence. 6-mode pipeline: Analyze, Profile, Cache, Benchmark, Regression, Leak-Patterns.
Scope: Performance analysis and recommendations only. NOT for running profilers, executing load tests, infrastructure monitoring, or actual memory leak detection. This skill provides analysis-based guidance, not measurements.
Canonical Vocabulary
Use these terms exactly throughout all modes:
| Term | Definition |
|---|---|
| complexity | Big-O algorithmic classification of a function or code path |
| hotspot | Code region with disproportionate resource consumption (time or memory) |
| bottleneck | System constraint limiting overall throughput |
| profiler output | Textual data from cProfile, py-spy, perf, or similar tools pasted by user |
| cache strategy | Eviction policy + write policy + invalidation approach for a caching layer |
| benchmark skeleton | Template code for measuring function performance with proper methodology |
| regression risk | Likelihood that a code change degrades performance, scored LOW/MEDIUM/HIGH/CRITICAL |
| anti-pattern | Known performance-harmful code pattern (N+1, unbounded allocation, etc.) |
| evidence | Concrete proof: AST analysis, profiler data, code pattern match, or external reference |
| recommendation | Actionable optimization suggestion with expected impact and trade-offs |
| flame graph | Hierarchical visualization of call stack sampling data |
| wall time | Elapsed real time (includes I/O waits) vs CPU time (compute only) |
Dispatch
| $ARGUMENTS | Mode |
|---|---|
analyze <file/function> |
Algorithmic complexity analysis, Big-O review |
profile <data> |
Interpret textual profiler output (cProfile, py-spy, perf) |
cache <system> |
Caching strategy design (LRU/LFU/TTL/write-through/write-back) |
benchmark <code> |
Benchmark design and methodology review |
regression <diff> |
Performance regression risk assessment from code diff |
leak-patterns |
Common memory leak pattern scan (NOT actual detection) |
| Empty | Show mode menu with examples for each mode |
What ships with it
29 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- data/anti-patterns.json 2.8 KB
- data/caching-strategies.json 1.6 KB
- data/complexity-patterns.json 2.0 KB
- evals/analyze-complexity.json 616 B
- evals/cache-design.json 758 B
- evals/complexity-analysis.json 451 B
- evals/evals.json 2.3 KB
- evals/implicit-trigger.json 447 B
- evals/negative-control.json 468 B
- evals/profile-interpretation.json 657 B
- evals/regression-risk.json 686 B
- references/anti-patterns.md 4.5 KB
- references/benchmark-methodology.md 3.7 KB
- references/caching-strategies.md 4.2 KB
- references/complexity-patterns.md 2.9 KB
- references/leak-patterns.md 5.1 KB
- references/profiler-guide.md 3.6 KB
- scripts/asset_toolkit/__init__.py 303 B runs code
- scripts/asset_toolkit/_shared.py 5.6 KB runs code
- scripts/asset_toolkit/common.py 3.0 KB runs code
- scripts/asset_toolkit/package.py 43 KB runs code
- scripts/asset_toolkit/validate_evals.py 11 KB runs code
- scripts/asset_toolkit/validate_hooks.py 13 KB runs code
- scripts/asset_toolkit/validate_skill.py 3.6 KB runs code
- scripts/benchmark-designer.py 3.9 KB runs code
- scripts/check.py 2.2 KB runs code
- scripts/complexity-estimator.py 6.6 KB runs code
- scripts/profile-parser.py 6.0 KB runs code
- templates/dashboard.html 7.1 KB
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 · 285 lines · 37 tokens per session scan A e2bad986ce82
performance-profiler is a skill published in the GitHub repository wyattowalsh/agents (5 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 2,464 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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