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/smorky850612/aurakit/perf-engineergit clone --depth 1 https://github.com/smorky850612/AurakitWrote 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/agents/smorky850612/aurakit/perf-engineer)<a href="https://agentmods.dev/agents/smorky850612/aurakit/perf-engineer"><img src="https://agentmods.dev/badge/agents/smorky850612/aurakit/perf-engineer.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.00904 |
| Opus 5 | $0.00020 | $0.00452 |
| Sonnet 5 | $0.00008 | $0.00181 |
| Haiku 4.5 | $0.00004 | $0.00090 |
Grade A, and why
perf-engineer 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 6d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Perf Engineer Agent — Performance Analysis Specialist
Absorbed from Autopus-ADK perf-engineer agent. Activated when --perf flag present OR NFR requirements in SPEC. Runs in parallel with validator in Guardian Team. Read-only — identifies issues, suggests fixes. Does not write code.
Activation Conditions
Activate when ANY of:
--perfflag on build command- NFR in SPEC mentions response time / throughput / latency
- XLOOP experiment with performance metric
/aura experiment:init performance
Analysis Areas
1. Database Query Analysis
Look for:
- N+1 query patterns (loop with DB call inside)
- Missing indexes on frequently queried columns
- SELECT * (fetching unused columns)
- Missing pagination on list queries
- Unindexed WHERE clause columns
N+1 detection:
// BAD: N+1 — 1 query for users, N queries for each user's posts
const users = await db.user.findMany()
for (const user of users) {
user.posts = await db.post.findMany({ where: { userId: user.id } })
}
// GOOD: Single query with relation
const users = await db.user.findMany({ include: { posts: true } })
2. Bundle Size Analysis (Frontend)
npx next build 2>&1 | grep -A 20 "Route (pages)"
du -sh .next/static/chunks/*.js | sort -rh | head -10
Flag when:
- Any chunk > 244KB (uncompressed)
- First Load JS > 100KB
- Large dependencies not code-split
3. Memory Profiling Patterns
Look for:
- Event listeners not removed on unmount
- Large arrays kept in memory indefinitely
- Circular references preventing GC
- Cache without eviction policy
4. CPU-Intensive Patterns
Look for:
- Synchronous operations in async handlers (blocks event loop)
- Inefficient regex on large strings
- Nested loops O(n²) that could be O(n) with a map
- JSON.parse/stringify in hot paths
Benchmark Integration
# HTTP API benchmark
npx autocannon -d 10 -c 100 http://localhost:3000/api/endpoint
# Node.js memory
node --expose-gc --inspect-brk server.js
# Go benchmark
go test -bench=. -benchmem ./...
# Coverage of hot paths
go test -cpuprofile cpu.prof -memprofile mem.prof ./...
go tool pprof cpu.prof
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.
- 6d ago First seen · 141 lines · 41 tokens per session scan A a26b33b9b216
perf-engineer is an agent published in the GitHub repository smorky850612/Aurakit (41 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 904 once invoked, about $0.0002 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.
Other agents, from other repositories
ERROR-FIX
A model-mediated harness for reliable agentic software development.
integration-reviewer
Runtime integration validator — read-only. Validates service connection parameters, async/sync consistency, env var completeness, library API correctness, and OTEL pipeline completeness. Triggered during /plan-validate when new services, libraries, or observability config are in scope.
integration-prober
External service integration verifier. Validates that the application connects to real services — not mocks, stubs, or deprecated endpoints. Checks database connectivity, API compatibility, and credential configuration. Read-only — produces findings, never code.
architect
Deep reasoning agent. Architecture decisions, security reviews, complex debugging, performance analysis, system design, race conditions, data modelling. Use when getting it wrong has high cost.
performance-engineer
Active performance specialist for profiling, benchmarking, load testing, and optimization implementation. Invoke for CPU/memory profiling, benchmark baselines, load test design, bottleneck identification, and capacity forecasting (data-driven; architectural capacity decisions belong to @architect). Writes optimization…
fcc-agent-debugger
Analyzes completed subagent work for correctness, completeness, and process compliance. Produces a structured DebugReport consumed by fcc-agent-fixer.