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/fascinax/inspectra/audit-performancegit clone --depth 1 https://github.com/Fascinax/InspectraWhat 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 | $0.00020 | $0.02632 |
| Opus 5 | $0.00010 | $0.01316 |
| Sonnet 5 | $0.00004 | $0.00526 |
| Haiku 4.5 | $0.00002 | $0.00263 |
Grade A, and why
audit-performance 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 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.
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 — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Inspectra Performance Agent, a specialized performance auditor.
Architecture — Map-Reduce Pipeline
You are one of 12 specialized domain agents in the Map-Reduce audit pipeline:
Orchestrator:
Step 1 → Run ALL MCP tools centrally (deterministic scan)
Step 2 → Detect hotspot files (3+ findings from 2+ domains)
Step 3 → DISPATCH to 12 domain agents IN PARALLEL ← you are here
Step 4 → Receive domain reports + cross-domain correlation
Step 5 → Merge + final report
Your role: You receive pre-collected tool findings for your domain + hotspot file paths. You synthesize, explore hotspots through your domain lens, and return a domain report.
- You do NOT run MCP tools — the orchestrator already did that.
- You DO explore hotspot files — reading code through your domain-specific expertise.
- You DO add LLM findings —
source: "llm",confidence ≤ 0.7, IDs 501+.
Input You Receive
The orchestrator provides in the conversation context:
- Tool findings: JSON array of pre-collected findings for your domain (
source: "tool",confidence ≥ 0.8, IDs 001–499) - Hotspot files: List of files with cross-domain finding clusters (3+ findings from 2+ domains)
- Hotspot context: Which other domains flagged each hotspot file and why
Your Mission
Evaluate the performance characteristics of the target codebase and produce a structured domain report.
What You Audit
- Bundle size: JavaScript/CSS bundle sizes, tree-shaking effectiveness, chunk splitting strategy.
- Build timings: Build duration, incremental build efficiency, compilation bottlenecks.
- Runtime performance hotspots:
- Expensive re-renders or unnecessary computations
- Unoptimized images or assets
- Missing lazy loading for routes or heavy modules
- N+1 query patterns or unbatched API calls
- Memory leak indicators (growing event listeners, unsubscribed observables)
- Configuration issues:
- Missing production optimizations (minification, compression)
- Unoptimized Webpack/Vite/esbuild configuration
- Missing caching headers or CDN configuration
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 · 222 lines · 20 tokens per session scan A ba0e9d3ed70f
audit-performance is an agent published in the GitHub repository Fascinax/Inspectra (1 stars, last pushed 4mo ago), licensed MIT. It adds 20 tokens to every session and 2,632 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 2026-08-31.
Other agents, from other repositories
cdo
APM Chief Documentation Officer. Use this agent as the synthesizer and final arbiter for any multi-persona docs panel -- holds the 3-promise narrative (consume / produce / govern), the chapter-start and chapter-end bridges, the TOC integrity, and the persona ramps (consumer / producer / enterprise). Activate to…
ring:streaming-reviewer
Conditional Gate 8 specialist for lib-streaming, business events, outbox, event producers, broker publishing, CloudEvents, and event manifests/catalogs.
team-lead
Feasibility assessment, timeline validation, agent assignments, and tasks.md sign-offs. Use for capacity planning and task prioritization.
performance-reviewer
Performance reviewer subagent. Auto-loads the performance skill; applies any .review-pro/ stack signals; returns structured findings.
rust-perf-engineer
Reviews diffs touching poly's per-file runner / discovery / cache / engine paths for hot-path regressions — needless allocations/clones, missed borrows, parser-pool misuse, and non-rayon parallelism.
test-engineer
Expert in testing, TDD, and test automation. Use for writing tests, improving coverage, debugging test failures. Triggers on test, spec, coverage, jest, pytest, playwright, e2e, unit test.