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 irahardianto/awesome-agv --skill perf-optimizationgit clone --depth 1 https://github.com/irahardianto/awesome-agvWrote 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/irahardianto/awesome-agv/perf-optimization)<a href="https://agentmods.dev/skills/irahardianto/awesome-agv/perf-optimization"><img src="https://agentmods.dev/badge/skills/irahardianto/awesome-agv/perf-optimization/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/irahardianto/awesome-agv/perf-optimization"><img src="https://agentmods.dev/badge/skills/irahardianto/awesome-agv/perf-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 31 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 | $0.00072 | $0.03793 |
| Opus 5.5 | $0.00029 | $0.01517 |
| Sonnet 5.5 | $0.00014 | $0.00759 |
| Haiku 4.5 | $0.00007 | $0.00379 |
Grade A, and why
perf-optimization 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 9d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimization Skill
When to Use
- User provides profiling data (pprof, flamegraph, py-spy, Chrome DevTools, Dart DevTools)
- User asks to analyze or optimize performance of a specific component
- A benchmark regression is detected
- After deploying a new feature that touches a hot path
Contents
| Reference | Purpose | Used By |
|---|---|---|
references/perf-dimensions.md |
6 MECE performance dimension scope cards + subagent prompt template | Coordinator dispatching parallel subagents in /perf-optimize skill |
references/perf-report-template.md |
Structured report template for performance analysis and results output | Coordinator writing Phase 3 analysis report and Phase 6 results |
Usage
The /perf-optimize skill loads this skill automatically.
- Methodology & patterns: The coordinator reads this file for the core methodology (Profile → Analyze → Optimize → Benchmark), optimization pattern catalog, anti-patterns, and when-to-stop heuristics.
- Dimension scope cards: Read
references/perf-dimensions.mdto get the scope definition for each dimension (A–F) and the system prompt template for subagent dispatch. - Report template: Read
references/perf-report-template.mdwhen writing the Phase 3 analysis report and updating it with Phase 6 implementation results. - Language modules: Read
languages/{lang}.mdfor language-specific profiling tools, irreducible floors, and runtime-specific patterns.
Core Methodology
graph LR
P1[Profile] --> P2[Analyze]
P2 --> P2b[Opportunity Scan]
P2b --> P3[Prioritize]
P3 --> P4[Optimize]
P4 --> P5[Benchmark]
P5 --> P6{Improvement?}
P6 -->|Yes| P7[Verify & Ship]
P6 -->|No| P3
Step 1: Profile
Collect profiling data using the language-appropriate tool. Load the relevant languages/*.md module for exact commands.
Output: Raw profiling data (CPU profile, heap profile, or trace).
Step 2: Analyze
Read the profile. Focus on these principles (universal across all runtimes):
What ships with it
17 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.
- languages/cpp.md 7.0 KB
- languages/csharp.md 6.4 KB
- languages/flutter.md 7.3 KB
- languages/frontend.md 14 KB
- languages/go.md 4.7 KB
- languages/java.md 6.3 KB
- languages/kotlin.md 6.6 KB
- languages/php.md 6.1 KB
- languages/python.md 9.5 KB
- languages/ruby.md 6.3 KB
- languages/rust.md 9.2 KB
- languages/swift.md 6.2 KB
- languages/typescript.md 6.4 KB
- references/perf-dimensions.md 12 KB
- references/perf-report-template.md 6.5 KB
- scripts/frontend-lighthouse.sh 13 KB runs code
- scripts/go-pprof.sh 3.1 KB runs code
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.
- 9d ago Changed cc61b15a362c
- 1mo ago First seen · 318 lines · 72 tokens per session scan A 1d114e9de019
perf-optimization is a skill published in the GitHub repository irahardianto/awesome-agv (156 stars, last pushed 9d ago), licensed MIT. It adds 72 tokens to every session and 3,793 once invoked, about $0.0003 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 2026-08-30.
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dev-fix
Unified developer workflow for fixing bugs. Analyzes issue-tracker context, cross-checks docs/code, proposes a solution, implements the fix, verifies locally, and delivers a PR/MR.
verify-bug
Post-merge UAT verification workflow. Walks JIRA reproduce steps, performs comparative audits (Before/After), attaches evidence to JIRA, and transitions status on PASS.
incident-hotfix
Mitigate a production incident or urgent regression first, then route to root-cause remediation and a postmortem.
cyber-triage
Evidence-led blue incident triage with authorization and runtime gates.