immune-scan

immune-scan is an agent for coding agents from Mathews-Tom/armory. It costs 3 tokens per session (991 once invoked), scanned A, original, MIT.

A content scanner that looks for known error patterns, new problems, and useful patterns worth remembering.

In plain words
What is it for?
Use it to review content, flag issues, suggest corrections, and identify strategies that may be useful later.
Why use it?
It helps catch recurring mistakes and new threats in text or other content, while checking whether previously used strategies worked.

Agent

Part of the armory plugin — 57 skills, 1 agent shipped together

Install

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.

agentmods
npx agentmods add agents/mathews-tom/armory/immune-scan
Clone the repo
git clone --depth 1 https://github.com/Mathews-Tom/armory

Or install armory, the plugin that ships this one along with the rest of its 57 skills, 1 agent.

Wrote 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.

agentmods badge for immune-scan

README.md
[![agentmods](https://agentmods.dev/badge/agents/mathews-tom/armory/immune-scan.svg)](https://agentmods.dev/agents/mathews-tom/armory/immune-scan)
Your own site
<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>
Per session 3 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 991 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 4d ago against content hash 45ceab9d2fed, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/immune/agents/immune-scan.md · 110 lines

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>

Read the full file on GitHub · 110 lines

Changes

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.

  1. 4d ago First seen · 110 lines · 3 tokens per session scan A 45ceab9d2fed

Subscribe to this mod's changes

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.