decompose-ishikawa
SkillDev toolsLets your agent break down a problem into cause categories on an Ishikawa fishbone diagram with evidence notes.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the decompose-ishikawa skill
About this skill
Build an Ishikawa-style causal decomposition across relevant cause families.
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/decompose-ishikawa/SKILL.md and read by ahel’s review.
Purpose
Build an Ishikawa causal decomposition across relevant cause families.
Input contract
required: [effect_statement, cause_families]
optional: [evidence_records, system_boundary]
constraints: [cause families must be named and causes linked to the effect]
Procedure
- Place the normalized effect at the head of the diagram.
- Populate relevant method, data, theory, measurement, researcher, and environment branches.
- Subdivide each branch into testable causes and mark evidence status.
Output contract
produces: [ishikawa_map, cause_register, evidence_status]
delta_fields: [findings, assumption_updates, uncertainties]
Quality gates
- Every cause belongs to a declared family and has a testability or evidence note.
Failure and counterexamples
Reject a decorative fishbone with no causal links or one that treats categories as causes without support.
Provenance map
deep-insight/ishikawa-decomposition: resolved.
Signals
- GitHub stars
- 501
- Forks
- 41
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
decompose-ishikawa- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine