# H Diagnose

> Diagnose a concrete failure with rival-hypothesis testing. Stabilize the symptom, generate distinct explanations, test discriminating observations read-only in parallel, and rank by evidence while retaining losing rivals.

- Skill: `m0n0x41d/h-diagnose-2` (Agent Skill)
- Install (CLI): `npx skillmds@latest add m0n0x41d/h-diagnose-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/m0n0x41d/h-diagnose-2/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: m0n0x41d (https://skillmd.com/u/m0n0x41d)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/m0n0x41d/h-diagnose-2

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# h-diagnose — Test rival explanations

Retrieve current FPF source only when pattern choice is material to the
diagnosis. Mechanical reproduction, logs, and direct implementation probes do
not need a ritual query. Inspect a known SourceID/UnitID directly; otherwise
use `mode="concern"` and treat the returned `candidate_set` as incomplete
navigation, not a selected pattern. Before relying on one candidate, inspect
its exact identifier and direct pattern body. Keep several candidates live or
abstain when the returned basis is insufficient. Never run a query after the
diagnosis merely to manufacture source support for an already-chosen story.

Keep symptom, hypothesis, probe, observation, and verdict distinct. Include a
rival that challenges the initial framing. Prefer safe parallel probes; label
design-time inference separately from runtime evidence. Keep losing hypotheses
with return conditions. Persist only on explicit request or when a named
receiving use needs replay.