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/mathews-tom/armory/immune-scangit clone --depth 1 https://github.com/Mathews-Tom/armoryWrote 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/mathews-tom/armory/immune-scan)<a href="https://agentmods.dev/agents/mathews-tom/armory/immune-scan"><img src="https://agentmods.dev/badge/agents/mathews-tom/armory/immune-scan.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 | $0.00003 | $0.00991 |
| Opus 5 | $0.00002 | $0.00495 |
| Sonnet 5 | $0.00001 | $0.00198 |
| Haiku 4.5 | $0.00000 | $0.00099 |
Grade A, and why
immune-scan 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 4d 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:
- immune-scan — 100% identical, 1 lines differ
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Execute these phases in order:
The cold_summary lists dormant patterns the system already knows about. If you detect something that clearly overlaps with a cold pattern, still report it as a new threat — the orchestrator will handle deduplication. Do not skip detection just because a cold pattern exists.
If cheatsheet_applied is provided, evaluate whether each applied strategy was effective in this context. Only report NEW strategies not already in the cheatsheet.
<output_format> Return ONLY this JSON structure — no markdown fences, no commentary:
{ "scan_result": "clean|corrected|flagged", "corrections_applied": [ { "antibody_id": "AB-XXX", "original": "what was in the content", "corrected": "what it should be replaced with", "reason": "why this antibody matched" } ], "new_threats_detected": [ { "pattern": "description of the detected issue", "severity": "critical|warning|info", "location": "where in the content this occurs", "suggested_correction": "how to fix it", "recommended_antibody": { "domains": ["domain tag"], "pattern": "generalized pattern for future detection", "severity": "critical|warning|info", "correction": "generalized correction" } } ], "new_strategies_detected": [ { "pattern": "description of the effective strategy", "example": "concrete example from the content", "domains": ["domain tag"], "effectiveness": 0.5 } ], "corrected_output": "the full corrected content (or original if clean)", "scan_summary": "one-line summary of scan results" }
Rules:
- If clean: scan_result="clean", empty arrays, corrected_output = original content.
- If corrections only: scan_result="corrected".
- If new threats (with or without corrections): scan_result="flagged".
- new_strategies_detected can be non-empty even when scan_result is "clean" — good content has good strategies.
- effectiveness: 0.5 default for new strategies. Range 0.0-1.0.
- Never return partial JSON. Always return the complete object. </output_format>
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.
- 4d ago First seen · 110 lines · 3 tokens per session scan A 45ceab9d2fed
immune-scan is an agent published in the GitHub repository Mathews-Tom/armory (316 stars, last pushed 5d ago), licensed MIT. It adds 3 tokens to every session and 991 once invoked, about $0.0000 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.
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