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quality-fishbone-diagram-builder

Build and use Ishikawa (fishbone, cause-and-effect) diagrams for quality problems: 6M bones (Man, Machine, Method, Material, Measurement, Environment) plus 8M, service (4S/8P) and IT variants, prompt questions to fill empty bones, causes written as conditions rather than solutions or blame, sub-causes, status marking (untested, likely, verified, ruled out) and a verification plan that turns candidate causes into a proven root cause. Generates a text or Mermaid fishbone from a CSV cause list, normalises category names, and flags empty bones, solution-shaped causes, blame, duplicates and diagrams with no candidate selected. Use when brainstorming causes for an NCR, complaint, CAPA or 8D D4, facilitating a root cause workshop, or documenting an investigation.

A fishbone organises everything that could cause an effect so the team does not jump to its favourite theory. It is a map of hypotheses: its value comes from filling every bone, ruling causes out with data, and testing the likely ones. scripts/fishbone.py draws the diagram from a CSV, checks it and lists what to verify next.

Trigger Conditions

Activate this skill when the user:

  • Needs to brainstorm possible causes of a defect, complaint or process problem
  • Is facilitating a root cause workshop or 8D D4
  • Wants a fishbone diagram (text or Mermaid) for a report
  • Has a fishbone full of solutions or blame and no clear next step

After narrowing down: five-whys-analysis-facilitator for the chain to the system cause; design-of-experiments-planner for interacting factors.

Workflow

text
1. HEAD      -> specific, factual effect (what, where, how many)
2. BRAINSTORM-> silent notes, place on bones, use 6m-prompts.md for empty bones
3. CLEAN     -> conditions, not solutions or blame; remove duplicates
4. DRAW      -> python scripts/fishbone.py causes.csv --problem "<effect>"
5. NARROW    -> rule out with existing data; multi-vote the likely causes
6. TEST      -> verification plan per likely cause; update status to verified / ruled-out
7. HAND OFF  -> verified cause -> 5 Why to system cause -> CAPA actions

CSV Format

text
category,cause,subcause,status,evidence
Method,Open trays with no dividers on line 2,,verified,Transport trial 14/40 scratched without dividers
Measurement,Inspection light below 1000 lux at packing,,untested,

Status: untested, likely, verified, ruled-out. Category aliases map to the 6M (people -> Man, equipment -> Machine, procedure -> Method, supplier -> Material, gauge -> Measurement, surroundings -> Environment); other names become extra bones.

Checks (fishbone.py)

CodeSeverityProblem
FB001mediumEmpty 6M bone
FB002mediumCause written as a solution
FB003mediumCause blames a person
FB004lowSame cause on several bones
FB005lowNothing marked likely or verified
text
Method
  [V] Open trays with no dividers on line 2
  [L] Visual inspection before packing not after
FB002 [medium] Method: 'Need a vision system' is a solution; write the condition it would fix

Prompt questions per bone and variants for 8M, services and IT: 6m-prompts.md. Session plan, verification plan and next tools: from-fishbone-to-root-cause.md.

Output Format

Deliver:

  1. Effect statement at the head.
  2. Diagram - text tree or Mermaid (--format mermaid), with status marks.
  3. Ruled-out causes with the data that ruled them out.
  4. Verification plan for likely causes (test, expected result, owner, due).
  5. Verified root cause(s) and the hand-off to 5 Why / CAPA.

Scripts

bash
python scripts/fishbone.py causes.csv --problem "Scratches on HS-110 face A"
python scripts/fishbone.py causes.csv --problem "..." --format mermaid > fishbone.mmd

In Mermaid mode findings go to stderr so the diagram can be piped. Exit codes: 0 no medium findings, 1 medium findings, 2 read error or missing columns.

Additional Resources

FileContent
6m-prompts.mdPrompt questions per bone; 8M, service and IT variants
from-fishbone-to-root-cause.mdSession steps, voting, verification plan, next tools
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