Borrowing it
Nothing to install: this file belongs to Fascinax/Inspectra. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Fascinax/Inspectra/main/AGENTS.mdgit clone --depth 1 https://github.com/Fascinax/InspectraWrote 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/instructions/fascinax/inspectra/agents-md)<a href="https://agentmods.dev/instructions/fascinax/inspectra/agents-md"><img src="https://agentmods.dev/badge/instructions/fascinax/inspectra/agents-md/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/instructions/fascinax/inspectra/agents-md"><img src="https://agentmods.dev/badge/instructions/fascinax/inspectra/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.01267 | $0.01267 |
| Opus 5.5 | $0.00507 | $0.00507 |
| Sonnet 5.5 | $0.00253 | $0.00253 |
| Haiku 4.5 | $0.00127 | $0.00127 |
Grade A, and why
Inspectra AGENTS.md 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 1mo 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agents
Inspectra uses MCP tools and prompt workflows to perform structured code audits. Three audit architectures are available:
- Tier B (Hybrid): Single-prompt workflow (
/audit). Default, proven by benchmark. - Map-Reduce (Multi-Agent): Orchestrator + 12 parallel domain agents (
@audit-orchestrator). Deeper per-domain analysis with cross-domain correlation preserved. - Fusion (Maximum Recall): Combines Tier B + Map-Reduce in a single run, deduplicates cross-architecture findings (
@audit-fusion). Maximizes finding recall at the cost of higher latency.
Workflow Overview — Tier B (Default)
User prompt -> MCP tool scan -> hotspot detection -> optional explorer -> merge -> report
Workflow Overview — Map-Reduce (Multi-Agent)
User prompt -> MCP tool scan -> hotspot detection -> dispatch 12 agents -> cross-domain correlation -> merge -> report
Workflow Overview — Fusion (Maximum Recall)
User prompt -> MCP tool scan -> hotspot detection -> Pass A (Tier B synthesis) + Pass B (12 agents) -> cross-architecture dedup -> correlation -> merge -> report
- The prompt workflow receives the audit request and selects the relevant tool groups.
- MCP tools gather deterministic findings across the requested domains.
- Hotspot detection identifies files with clustered findings across multiple domains.
- A conditional explorer pass reads only hotspot files to uncover deeper root causes.
- Root-cause inference maps hotspots to known categories (god-module, test-gap, etc.).
- The prioritization engine scores each cluster and groups them into Fix Now / Next Sprint / Backlog.
- The workflow merges results, simulates score projections, and generates Markdown output.
Audit Modes
- Full audit (
/audit): runs Tier B across all 12 domains. - Fusion audit (
@audit-fusion): runs both Tier B + Map-Reduce, deduplicates, maximum recall. - Multi-agent audit (
@audit-orchestrator): runs Map-Reduce across all 12 domains. - PR audit (
/audit-pr): runs the Tier B workflow only on changed files. - Targeted audit (
/audit-domain): runs only the requested domain tool group.
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.
- 1mo ago First seen · 81 lines · 1,267 tokens per session scan A 3fb355381cbc
Inspectra AGENTS.md is an instructions file published in the GitHub repository Fascinax/Inspectra (1 stars, last pushed 6mo ago), licensed MIT. It adds 1,267 tokens to every session, about $0.0051 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 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.