--- name: stem-ai description: "Deterministic Evidence-Surface Scanner for Bio/Medical AI Repositories. Audits and reviews open-source bio/medical AI repositories for repository evidence-surface triage using a rubric-based 3-stage evaluation protocol with governance overlay. Produces scored review-priority reports with evidence chains. Supports 4 execution modes: LOCAL_ANALYSIS (AI CLI + local clone), FULL (web search + fetch), SEARCH_ONLY, and MANUAL. Use when asked to evaluate, audit, review, or assess evidence signals for any bio-AI, medical AI, or clinical-adjacent repository." version: "1.8.2" author: "Flamehaven" license: "Apache-2.0" platforms: ["claude-code", "codex", "gemini-cli", "cursor", "copilot", "antigravity", "universal"] --- # STEM BIO-AI -- Deterministic Evidence-Surface Scanner for Bio/Medical AI Repositories **Version:** 1.7.8 **Codename:** Hippocratic_Code_Engine_Unified **Runtime:** LLM-Native + AI CLI (Universal) > "Code works. But does the author care about the patient? > Governance without evidence is theater. > Evidence without accountability is still not trust. > Measurement beats interpretation." ## When to Use This Skill - Evaluating repository evidence signals for a bio-AI or medical AI repository - Auditing open-source clinical-adjacent tools before procurement or pilot - Assessing governance maturity of repositories handling patient data - Generating structured audit reports with evidence chains and scores - Comparing repository review-priority tiers across an ecosystem - Producing institutional-grade documentation (Claim Matrix, Evidence Ledger) ## What This Skill Produces 1. **STEM BIO-AI Audit Report** -- scored repository evidence-surface triage (T0-T4 review-priority tier) 2. **Executive Summary** -- 1-page institutional decision support 3. **Claim Matrix** -- line-level evidence anchors for every finding 4. **Evidence Ledger** -- snapshot provenance and artifact tracking 5. **Code Integrity Report** -- C1-C6 findings (LOCAL_ANALYSIS only) ## Audit Layering STEM BIO-AI sits on top of technical audit. It should not replace it. - **Technical audit** determines what the repository actually does. - **STEM BIO-AI** determines whether the observable artifact surface is sufficient for institutional review triage. Use this skill after or alongside technical inspection, not instead of it. ## Quick Start To audit a repository, provide: - GitHub URL or README text - (Optional) CHANGELOG, social media activity, CI/CD status - (Optional) Governance overlay materials The skill will: 1. Detect execution mode (LOCAL_ANALYSIS / FULL / MANUAL) 2. Run 3-stage evaluation (README Evidence Signal, Repo-Local Consistency, Code/Bio Responsibility) 3. Score with fixed rubric (cross-LLM target: +/-10 points) 4. Evaluate governance overlay if artifacts present 5. Generate multi-file output package ## Skill Architecture ``` stem-ai/ SKILL.md <-- You are here (entry point) memory/ <-- MICA v0.2.4 memory layer (load first) mica.yaml <-- composition contract stem-ai.mica.v1.7.8.json <-- active archive (selected by mica.yaml) stem-ai-playbook.v1.7.8.md <-- active session protocol (selected by mica.yaml) stem-ai-lessons.v1.7.8.md <-- active lessons history (selected by mica.yaml) spec/ <-- Core rubric, scoring, execution rules discrimination/ <-- YES/NO example pairs for scoring consistency templates/ <-- Output templates (report, claim matrix, etc.) scripts/ <-- Automation scripts (scans, provenance) references/ <-- Lookup tables (tiers, triggers, taxonomy) examples/ <-- Real audit examples ``` ## Instructions When activated, load files in this order: 0. **Load MICA memory layer first (before any audit work):** - Load `memory/mica.yaml` -- verify package structure and mode - Load the archive file referenced by `memory/mica.yaml` -- activate 18 IMMUTABLE rules as design_invariants - Load the playbook file referenced by `memory/mica.yaml` -- session protocol and rubric drift guard - Run `python tools/mica_pct.py .` -- verify PCT-001 through PCT-011. Halt on PCT-001/002/003/004 failure. - Run `python tools/mica_runtime.py . --format text` - Report: `[MICA READY] stem-ai-bio v1.7.8 | mode: protocol_evolution | invariants: 18 active | pct: CLOSED` 1. **Always load next:** `spec/STEM-AI_v1.1.2_CORE.md` This is the canonical rubric and execution instruction. 2. **Load on demand during Stage 1:** - `discrimination/H1-H6_examples.md` - `references/clinical_adjacent_triggers.md` 3. **Load on demand during Stage 3:** - `discrimination/T2_examples.md` - `discrimination/B3_COI_guide.md` - `discrimination/CA_severity_examples.md` 4. **Load if governance overlay detected:** - `discrimination/G1-G5_examples.md` 5. **Load for output generation:** - `templates/audit_report.md` - `templates/claim_matrix.md` - `templates/executive_summary.md` - `templates/evidence_ledger.md` 6. **Run in LOCAL_ANALYSIS mode:** - `scripts/local_analysis_scan.sh` - `scripts/ca_detection_scan.sh` - `scripts/snapshot_provenance.sh` ## Execution Modes | Mode | Environment | Evidence Quality | C1-C4 | |------|------------|-----------------|-------| | LOCAL_ANALYSIS | AI CLI + local clone | CODE_PATH (measurement) | Active | | FULL | Online LLM + web tools | TEXT_PATH + web fetch | N/A | | SEARCH_ONLY | Online LLM + search only | TEXT_PATH + search | N/A | | MANUAL | Online LLM, no tools | TEXT_PATH only | N/A | ## Tier Definitions | Tier | Score | Meaning | |------|-------|---------| | T0 Rejected | 0-39 | Trust not established -- clinical use prohibited | | T1 Quarantine | 40-54 | High risk -- independent verification required | | T2 Caution | 55-69 | Research reference only -- clinical automation forbidden | | T3 Review | 70-84 | Supervised clinical pilot eligible -- oversight mandatory | | T4 Candidate | 85-100 | Strongest structural audit-readiness signal -- clinical deployment still requires independent validation |