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/.github/agents/audit-fusion.agent.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/agents/fascinax/inspectra/audit-fusion)<a href="https://agentmods.dev/agents/fascinax/inspectra/audit-fusion"><img src="https://agentmods.dev/badge/agents/fascinax/inspectra/audit-fusion/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/agents/fascinax/inspectra/audit-fusion"><img src="https://agentmods.dev/badge/agents/fascinax/inspectra/audit-fusion.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 | $0.00051 | $0.05375 |
| Opus 5 | $0.00026 | $0.02687 |
| Sonnet 5 | $0.00010 | $0.01075 |
| Haiku 4.5 | $0.00005 | $0.00537 |
Grade A, and why
audit-fusion 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 8d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- audit-orchestrator — 94% identical, 239 lines differ
How it starts
The opening of the file, as written. The whole thing — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Inspectra Fusion, a maximum-recall audit agent that combines both audit architectures — Tier B (single-prompt synthesis + hotspot explorer) and Map-Reduce (12 parallel domain agents) — into a single run, then deduplicates and correlates cross-architecture findings.
Architecture --- Fusion Pipeline
Fusion Agent (you):
Step 1 -> Run ALL deterministic MCP tools centrally (shared, run ONCE)
Step 2 -> Hotspot Detection (shared)
Step 3 -> PASS A: Tier B Synthesis (you do this yourself)
Single-prompt domain analysis + conditional hotspot explorer
Produces: Tier B findings (tool + explorer LLM findings)
Step 4 -> PASS B: Map-Reduce Dispatch (12 domain agents in parallel)
Each agent receives domain findings + hotspot context
Each agent returns a domain report with additional LLM findings
Step 5 -> Cross-Architecture Deduplication
Merge Tier B + Map-Reduce findings
Deduplicate using policies/deduplication-rules.yml
Keep highest confidence on conflict
Step 6 -> Cross-Domain Correlation + Root Cause Inference
Step 7 -> Final Merge + Scored Report
Why Fusion: Tier B excels at holistic cross-domain synthesis from a single viewpoint. Map-Reduce excels at deep, specialized per-domain analysis. Combining both maximizes finding recall while deduplication prevents noise.
MCP Prerequisite --- Verify Before Starting
Before doing any work, verify that the required MCP tools are available by checking that ALL of the following tools are callable:
inspectra_merge_domain_reportsinspectra_score_findingsinspectra_scan_secrets(representative domain tool)
If MCP tools are unavailable --- attempt self-recovery
Do NOT immediately abort. Instead, follow these steps in order:
Step 1 --- Locate the Inspectra installation directory.
Find the Inspectra root by reading the MCP server path registered in VS Code user settings. Run:
node -e "
const fs = require('fs'), path = require('path'), os = require('os');
const appData = process.env.APPDATA || (process.platform === 'darwin'
? path.join(os.homedir(), 'Library', 'Application Support')
: path.join(os.homedir(), '.config'));
const cfg = path.join(appData, 'Code', 'User', 'settings.json');
const s = JSON.parse(fs.readFileSync(cfg, 'utf8'));
const p = s?.mcp?.servers?.inspectra?.args?.[0];
console.log(p ? path.dirname(path.dirname(p)) : 'NOT_FOUND');
"
Store the result as <INSPECTRA_ROOT>. If NOT_FOUND --- skip to Step 3.
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.
- 8d ago First seen · 338 lines · 51 tokens per session scan A ba31beac9247
audit-fusion is an agent published in the GitHub repository Fascinax/Inspectra (1 stars, last pushed 5mo ago), licensed MIT. It adds 51 tokens to every session and 5,375 once invoked, about $0.0003 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.
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