heuristic

name	heuristic
description	Produce a scored heuristic critique of the UI using Nielsen's 10 + 6 design laws + optional persona walkthroughs. Outputs a machine-parseable scorecard plus a 0-100 UsabilityScore (the judged companion to the deterministic UICraftScore). Invoke when the user asks for heuristic on their UI, or mentions 'heuristic' alongside design / UI / frontend work.

Context: this sub-skill is one lens of the broader ui-craft skill. If the ui-craft skill is also installed, read its SKILL.md first for Discovery + Anti-Slop + Craft Test, then apply the specific lens below.

Score the UI at $ARGUMENTS against Nielsen's 10 + 6 design laws. Load the ui-craft skill.

Step 1 — Load the methodology. Read references/heuristics.md for the full rubric, scoring definitions, design law details, and the required output format. Do NOT invent a new format or a new scale.

Step 2 — Walk Nielsen's 10 heuristics. Score each 1-5 per the rubric:

• 1 blocks users · 2 severe friction · 3 works but confusing · 4 works, minor polish · 5 best-in-class

For every heuristic, write a concrete finding — quote text, count elements, name the broken flow. Vague findings are rejected.

Step 3 — Audit the 6 design laws. PASS / FAIL each with a specific detail:

• Fitts's Law — touch target sizing, CTA placement
• Hick's Law — choice density, nav + select sizing
• Doherty Threshold — perceived latency, optimistic UI
• Cleveland-McGill — chart encoding choice
• Miller's Law — nav depth, form section counts
• Tesler's Law — where complexity lives

Step 4 — Persona walkthrough (if --persona= present). If the args include --persona=<name>, load references/personas.md and run the matching walkthrough checklist. Supported: priya, jordan, adaeze, kwame, margo, all. Output the walkthrough as a | Checklist item | Pass/Fail | Finding | Impact | table. Without the flag, skip this step.

Step 5 — Rank findings by impact tag. Impact order: blocks-conversion > adds-friction > reduces-trust > minor-polish. Include at most 5 findings in the ranked list; cut anything at minor-polish unless there are no higher-impact findings.

Step 6 — Compute the UsabilityScore. Roll the scorecard into a 0-100 number + grade per the UsabilityScore formula in references/heuristics.md: heuristic_base = round(((mean(nielsen_scores) − 1) / 4) × 100), minus 5 × (failed design laws), clamped [0,100]. Same A/B/C/D/F bands as UICraftScore. Always label it (judged) — it is not deterministic and must never gate CI. If the args include --json, also emit the machine-readable block. If the user asks for the full picture, build the Extended quality report by fetching the deterministic UICraftScore (node scripts/eval.mjs <path> --json or the score_ui MCP tool) and placing both side by side — never average them.

Step 7 — Output. Use the exact scorecard format in references/heuristics.md:

1. ## Heuristic Scorecard table
2. ## Design Law Audit table
3. ## Persona Walkthrough table (only if --persona= was passed)
4. ## Top findings (ranked by impact) — numbered list, 3-5 items
5. ## UsabilityScore block — the 0-100 score + grade + component breakdown

Knob awareness: knob-agnostic. Usability is not a knob — a 2 is a 2 whether CRAFT_LEVEL is 3 or 9. Do not soften scores based on CRAFT_LEVEL.

Output contract:

• This command produces a critique artifact, not code. No edits unless the user explicitly asks in a follow-up.
• The scorecard is machine-parseable markdown. A PM can paste it into any issue tracker and file tickets row-by-row. Frame it that way in any preamble.
• No "First Impressions" paragraph, no hedging, no praise padding. Tables + ranked list only.

Do NOT edit code. This is a scored critique.

Next step: Fix the findings, then /finalize — the scorecard is the input to a gated ship (rung 3).