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 zhuyansen/agent-skills-hub --skill perf-profiler-notesgit clone --depth 1 https://github.com/zhuyansen/agent-skills-hubWrote 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/zhuyansen/agent-skills-hub/perf-profiler-notes)<a href="https://agentmods.dev/skills/zhuyansen/agent-skills-hub/perf-profiler-notes"><img src="https://agentmods.dev/badge/skills/zhuyansen/agent-skills-hub/perf-profiler-notes/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/zhuyansen/agent-skills-hub/perf-profiler-notes"><img src="https://agentmods.dev/badge/skills/zhuyansen/agent-skills-hub/perf-profiler-notes.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 | $0.00022 | $0.00173 |
| Opus 5.5 | $0.00009 | $0.00069 |
| Sonnet 5.5 | $0.00004 | $0.00035 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade A, and why
perf-profiler-notes 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 5d 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.
What it actually says
Perf Profiler Notes
Read a profiler output and point to the three functions where time is actually spent.
When to use
Use this skill when the user asks for it by name or describes this task. Do not use it for unrelated work.
Steps
- Read the input the user points to. If none is given, ask for the file or text.
- Do the task described above, step by step, and keep the user's own wording where it matters.
- Show the result, then a short list of what you changed or found, so the user can check it.
Notes
- Keep changes small and reversible.
- Say plainly when the input is incomplete instead of guessing.
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.
- 5d ago First seen · 21 lines · 22 tokens per session scan A a07e30aa1270
perf-profiler-notes is a skill published in the GitHub repository zhuyansen/agent-skills-hub (452 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 173 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 2026-10-11.
Other skills, from other repositories
axiom-sre
Expert SRE investigator for incidents and debugging. Uses hypothesis-driven methodology and systematic triage. Can query Axiom observability when available. Use for incident response, root cause analysis, production debugging, or log investigation.
sentry-fix-issues
Find and fix issues from Sentry using MCP. Use when asked to fix Sentry errors, debug production issues, investigate exceptions, or resolve bugs reported in Sentry. Methodically analyzes stack traces, breadcrumbs, traces, and context to identify root causes.
argus
Argus — the all-seeing scanner suite. Six automated scanners for high-value web + LLM bug classes — CORS misconfiguration (origin reflection / null / credentialed read), CRLF & host-header injection, NoSQL injection (operator auth-bypass / $where blind), JWT attacks (alg:none / RS256→HS256 confusion / secret crack)…
convex-performance-audit
Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.
convex-self-heal
Production error → triaged, root-caused, repaired, and certified (tsc + rehearsal + reproduce-then-gone) fix PR for a human to merge — then confirm the error stops recurring. Never auto-merges.
convex-insights
Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.