Skill
Claude Code skill that forces AI to understand before executing. Three disciplines: cognition check, requirement understanding, method search.
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What its author says it does
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Clarity gate for prompts: intercepts unclear requests and forces the model to restate the user's intent to align before working, then diagnose the root cause and reuse the domain's mature, established practices before improvising. Clear prompts pass through untouched.
SKILL.md
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promptly-prompt
AI answer quality depends on input clarity, not prompt tricks — and nobody writes perfectly clear prompts all the time. This skill catches the unclear ones at submission and repairs them through alignment.
It operates via a UserPromptSubmit hook that injects two disciplines
into unclear requests, both at once:
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Restate to align — echo the user's request in your own words and state your understanding, so a misread surfaces before any work happens. If the restatement reveals a mismatch, raise it before acting.
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Diagnose, then reuse prior art — don't solve from memory. Diagnose the root cause of the problem, search for the domain's mature, established practices — methodologies, frameworks, libraries, prior art — and only then proceed. If nothing fits, say so and explain why.
The hook script at scripts/intercept.py scores prompt unclarity using
rule-based signals: vague verbs without success criteria, hedging, and
dangling referents add points; concrete anchors (paths, errors, code),
structure, and explicit criteria subtract them. Length never adds points —
a long, well-specified prompt is the clearest kind and passes untouched.
Unclear requests (score >= 3) get the full injection, in the prompt's own
language (Chinese or English) — both disciplines, every time.
Explicit Invocation
When invoked directly (e.g., user says "optimize this prompt"), apply the two disciplines manually: restate the user's intent with implicit needs surfaced, then locate the domain and the existing methods that belong to it. Rewrite the prompt with that context filled in.