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From pharaoh
Audits a single FMEA failure-mode entry against checklists for severity/occurrence/detection scales, RPN computation, cause/effect well-formedness, and traceability to artifacts. Emits structured JSON findings.
How this skill is triggered — by the user, by Claude, or both
Slash command
/pharaoh:pharaoh-fmea-reviewThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Invoke after `pharaoh-fmea` emitted a single failure-mode entry. Part of the self-review invariant.
Invoke after pharaoh-fmea emitted a single failure-mode entry. Part of the self-review invariant.
Do NOT review sets of FMEA rows — this skill reviews one entry. A fleet review is a separate flow that invokes this skill per entry.
{target: <fmea_entry_json_or_need_id>, checklist_path: <path>, tailoring_path: <path>}. Output: findings JSON.passing-fmea.json + failing-fmea.json with expected findings.target: JSON object with the FMEA entry shape emitted by pharaoh-fmea, OR a need_id with type fmea in needs.json.checklist_path: shared/checklists/fmea.md.tailoring_path: .pharaoh/project/ for optional scale extensions.{
"need_id": "fmea__example_01",
"type": "fmea",
"axes": {
"trace_to_analyzed_artefact": {"passed": true},
"severity_in_range": {"passed": true, "reason": "sev=7, scale=1..10"},
"occurrence_in_range": {"passed": true, "reason": "occ=4"},
"detection_in_range": {"passed": true, "reason": "det=3"},
"rpn_computed_correctly": {"passed": true, "reason": "7*4*3=84, entry reports 84"},
"cause_well_formed": {"score": 3},
"effect_well_formed": {"score": 3},
"mitigation_proposed_if_rpn_high": {"score": 2, "reason": "RPN 84 > threshold 60; mitigation text thin"}
},
"overall": "pass"
}
npx claudepluginhub useblocks/pharaoh --plugin pharaohDerives one FMEA failure mode entry from a requirement or architecture element, emitting JSON with cause, effect, S/O/D ratings (1-10), RPN, mitigations, and justifications. For safety-critical analysis.
Provides criteria and scoring to review root cause analysis quality across 6 dimensions including causality logic, evidence, alternatives, depth, completeness, and solution traceability.
Provides CDSS development patterns for drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), and alert classification integrated into EMR workflows.