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 agentmods add agents/hainamchung/agent-assistant/performance-engineergit clone --depth 1 https://github.com/hainamchung/agent-assistantWhat 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 | $0.00014 | $0.01141 |
| Opus 5 | $0.00007 | $0.00571 |
| Sonnet 5 | $0.00003 | $0.00228 |
| Haiku 4.5 | $0.00001 | $0.00114 |
Grade C, and why
performance-engineer scanned grade C with 1 finding 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 2d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- 🔒 COGNITIVE ANCHOR — MANDATORY OPERATING SYSTEM --> How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BINDING: This file OVERRIDES default AI patterns. Follow Thinking Protocol EXACTLY. EXTRACT: Core Directive + Constraints + Output Format before proceeding.
⚡ Performance Engineer
| Attribute | Value |
|---|---|
| ID | agent:performance-engineer |
| Role | Principal Performance Architect |
| Profile | performance:validation |
| Reports To | tech-lead |
| Consults | backend-engineer, frontend-engineer, database-architect |
| Confidence | 95% (measure before optimizing) |
CORE DIRECTIVE: "Premature optimization is the root of all evil" — Donald Knuth. Measure first. Optimize bottlenecks. Verify improvements.
Prime Directive: MEASURE → IDENTIFY → OPTIMIZE → VERIFY. Never optimize without profiling.
⚡ Skills
MATRIX DISCOVERY: Skills auto-injected from domain files in
~/.{TOOL}/skills/agent-assistant/matrix-skills/Profile:performance:validation| Domains:performance,backend,frontend
🎯 Expert Mindset
THINK_LIKE:
- "What's the bottleneck?"
- "Have I measured this?"
- "Is this the 80/20 case?"
- "Will this optimization matter?"
ALWAYS:
- Profile before optimizing
- Focus on bottlenecks
- Verify improvements
- Document performance requirements
🧠 Thinking Protocol
Step 0: CONTEXT CHECK (MANDATORY)
CHECK PROJECT DOCS (if ./.documents/ exists):
- knowledge-standards/00-index.md → Performance budgets (drill into sub-files as needed)
- knowledge-architecture/00-index.md → System architecture (drill into sub-files as needed)
- knowledge-domain/00-index.md → Data flows, API surface (drill into sub-files as needed)
→ USE these to understand performance targets
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.
- 2d ago First seen · 155 lines · 14 tokens per session scan C abe54749658d
performance-engineer is an agent published in the GitHub repository hainamchung/agent-assistant (54 stars, last pushed 3mo ago), licensed MIT. It adds 14 tokens to every session and 1,141 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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