inbusiness23/agent-immune-system

<what-to-do>

Maintain long-term instruction health. Treat AGENTS.md, CLAUDE.md, project instructions, skills, memory reports, issue reports, Hermes findings, and postmortems as inputs to the Agent Immune System.

Do not convert every mistake into a permanent rule. A mistake is an antigen, not automatic memory.

When invoked, produce a concrete instruction-health decision:

1. Identify the evidence being reviewed.
2. Classify whether it is isolated, recurring, damaging, generalizable, already covered, or context-caused.
3. Query available memory/history when relevant: gbrain, knowledge/incidents/, reports, issue history, review history, or prior instruction changes.
4. Score promotion cost against future-error reduction.
5. Detect autoimmune risk: duplication, conflicts, exception chains, overcorrection, token burn, or suppression of useful core behavior.
6. Look for regeneration opportunities: can several scar rules become one cleaner principle?
7. Route the finding to the smallest sufficient memory destination.
8. Produce a human-reviewable report. Do not silently edit active instruction files.

Ask one question at a time only when the answer materially changes the decision and cannot be discovered from local files.

</what-to-do>

<supporting-info>

Mental Model

This skill is the immune system above task execution:

text
Primary Agent
  -> Project Agent
    -> Skills
      -> Execution

Instruction Health Manager
  -> monitors all layers
  -> governs instruction memory
  -> proposes optimized instruction artifacts

Active instructions are the execution contract. This skill governs proposed changes to that contract so AGENTS.md, CLAUDE.md, and SKILL.md files remain the optimized expression of lessons that survived selection pressure.

Evidence Sources

Inspect only the sources needed for the current review:

• AGENTS.md, CLAUDE.md, .codex/AGENTS.md, .claude/CLAUDE.md
• project instructions and README-like agent files
• skills/*/SKILL.md
• _reports/, docs/reports/, docs/postmortems/, issue reports
• Hermes/review artifacts
• local knowledge/ folders inside this skill
• gbrain or other long-term memory systems when available

Never harvest credentials, transcripts, shell history, keychain, or private tokens to reconstruct evidence.

Workflow

1. Frame The Review

State:

• trigger: pre-edit, post-session, review finding, postmortem, periodic audit, or manual request
• scope: global instructions, project instructions, one skill, or one incident cluster
• proposed output: report only, promotion proposal, pruning proposal, regeneration proposal, or hook/adaptor update

2. Innate Immune Classifier

Reject active promotion quickly when any are true:

• one-off or low-cost issue
• caused by bad task context rather than reusable agent behavior
• already covered by existing instructions
• duplicate or narrower than an existing principle
• would add more token/cognitive cost than it prevents
• belongs in a project/skill reference rather than global instructions

3. Adaptive Immune Classifier

Promote slowly. Require evidence of recurrence, severity, and generality.

Default threshold:

| Signal | Action | |---|---| | 1 low/medium issue | Log only | | 2 similar issues | Watchlist | | 3 similar issues | Reference antibody candidate | | 4+ similar issues | Direct inclusion candidate | | 1 critical general issue | Immediate reference candidate; direct inclusion only with explicit unacceptable-delay risk | | Old rule with no recent hits | Prune or demote candidate |

4. Autoimmune Detector

Find instructions that create more problems than they solve:

• exception chains: "never X, except Y, except Z..."
• duplicate rules in multiple files
• rules that conflict with project-specific guidance
• rules that make agents stop, ask, or refuse when execution is safe
• overly broad bans created from narrow incidents
• old wound rules with no recent hits
• token-heavy policy dumps that do not change behavior

5. Regeneration Engine

Prefer cleaner principles over accumulated scars. Ask:

> Can five instructions be replaced by one higher-level principle?

Regeneration proposals should list the old rule cluster, the new principle, behavior preserved, behavior intentionally removed, and risks.

6. Memory Router

Choose the smallest sufficient destination:

• tolerate: no write
• inflammation: temporary check with an expiry date or review count
• watchlist: knowledge/watchlists/ with promotion/demotion criteria
• dormant memory: knowledge/incidents/ with "do not revisit unless pattern recurs"
• reference antibody: knowledge/reference-antibodies/
• active instruction: AGENTS.md, CLAUDE.md, project instruction, or SKILL.md proposal
• deletion/demotion: pruning proposal

Use gbrain as memory backend when available. gbrain remembers; this skill judges.

7. Output

For narrow reviews, use quick-review mode:

• evidence
• finding
• harm
• recommended action
• confidence

Use templates/instruction-health-report.md as drafting scaffolding for broad audits and templates/promotion-proposal.md for active instruction changes.

For deep instruction audits, session reviews, postmortems, or architecture-style comparisons, write the final artifact as a single self-contained HTML file in the current project's _reports/ directory:

text
_reports/report-instruction-health-YYYY-MM-DD.html

No external CDNs. Use the markdown template only to structure content before rendering the HTML report.

Every broad audit report must include:

• Health score, 0-100
• Promotion candidates
• Demotion/deletion candidates
• Regeneration candidates
• Autoimmune findings
• Memory routing decisions
• Human approval checklist

Do not apply active instruction edits unless David explicitly asks in the current conversation.

Hooks

Hook scripts live in hooks/:

• claude-instruction-pretool-hook.sh: detects edits to active instruction files and emits a promotion-gate reminder.
• claude-instruction-posttool-hook.sh: logs instruction edits as audit candidates.
• codex-instruction-hook.sh: adapter script for Codex/manual invocation because Codex does not expose Claude-style native hook settings in this environment.

See references/hook-integration.md before installing or changing hooks.

Reference Files

• references/promotion-rubric.md: when deciding whether a lesson becomes active instruction memory.
• references/autoimmune-rubric.md: when evaluating harmful, conflicting, bloated, or overfit rules.
• references/regeneration-rubric.md: when compressing many rules into fewer principles.
• references/hook-integration.md: Claude/Codex hook wiring and trigger guidance.
• references/subagent-prompts.md: prompts for independent reviewers once the main skill framework exists.

</supporting-info>