perf-analyzer

A method for turning performance measurements, profiling results, experiments, and tested hypotheses into evidence-based recommendations.

In plain words
What is it for?
Use it to summarize a performance investigation, choose next actions, record discarded ideas, and identify when more testing is needed.
Why use it?
It keeps performance decisions tied to observed data and makes it clear when there is not enough evidence to recommend a change.

Skill for Claude CodeCodex

Part of the agentsys plugin — 28 skills, 1 hook shipped together

Install

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.

agentmods
npx agentmods add skills/agent-sh/agentsys/perf-analyzer
Any agent
npx skills add agent-sh/agentsys --skill perf-analyzer
Clone the repo
git clone --depth 1 https://github.com/agent-sh/agentsys

Made for: Claude Code, Codex.

Or install agentsys, the plugin that ships this one along with the rest of its 28 skills, 1 hook.

Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 181 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00017 $0.00181
Opus 5 $0.00009 $0.00090
Sonnet 5 $0.00003 $0.00036
Haiku 4.5 $0.00002 $0.00018

Measured 3d ago against content hash 8683224e3c4f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

perf-analyzer 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 3d 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.

.kiro/skills/perf-analyzer/SKILL.md · 38 lines

What it actually says

perf-analyzer

Synthesize performance investigation results into clear recommendations.

Follow docs/perf-requirements.md as the canonical contract.

Inputs

  • Baseline data
  • Experiment results
  • Profiling evidence
  • Hypotheses tested
  • Breaking point results

Output Format

summary: <2-3 sentences>
recommendations:
  - <actionable recommendation 1>
  - <actionable recommendation 2>
abandoned:
  - <hypothesis or experiment that failed>
next_steps:
  - <if user should continue or stop>

Constraints

  • Only cite evidence that exists in logs or code.
  • If data is insufficient, say so and request a re-run.
Changes

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.

  1. 3d ago First seen · 38 lines · 17 tokens per session scan A 8683224e3c4f

Subscribe to this mod's changes

perf-analyzer is a skill published in the GitHub repository agent-sh/agentsys (980 stars, last pushed 6d ago), licensed MIT. It adds 17 tokens to every session and 181 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.

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