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zhouey314-cloudzhouey314-cloud/ai-agent-skills/skills/requirement-clarifier/SKILL.md

requirement-clarifier

Skill0 starsChanged 49 days agoMITView on GitHub

Clarify an ambiguous build request into a testable scope when goals, stakeholders, or acceptance criteria are unclear.

3 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use before implementation when the input leaves ownership, success, data source, or irreversible actions ambiguous.

    line 14
  2. Distinctive:

    Ask only for decisions that materially change scope, risk or external state.

    line 29
  3. Very specific:

    If the owner of a business rule is unknown, mark BLOCKED_OWNER_DECISION.

    line 34
  4. Very specific:

    Run python3 tests/validate.py from the repository root to check this skill's contract and example provenance.

    line 42

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Requirement Clarifier

Purpose

Turn a vague request into a minimal, falsifiable delivery contract without making up business rules.

When to Use

Use before implementation when the input leaves ownership, success, data source, or irreversible actions ambiguous.

Inputs

request, known_constraints[], stakeholders[], optional existing_artifacts[] and decision_deadline.

Outputs

goal, in_scope[], out_of_scope[], acceptance_criteria[], assumptions[], open_decisions[], evidence_needed[].

Workflow

  1. Restate the user's desired outcome in one sentence and separate outcome from requested implementation.
  2. Extract hard constraints and existing evidence verbatim; label anything inferred as an assumption.
  3. Draft at most three acceptance checks that a reviewer can reproduce.
  4. Ask only for decisions that materially change scope, risk or external state; continue with reversible work meanwhile.
  5. Return the scope contract and mark each open decision with its owner and blocking effect.

Failure Handling

If the owner of a business rule is unknown, mark BLOCKED_OWNER_DECISION; do not invent a default. If source evidence is missing, mark the criterion provisional.

Example

synthetic_unverified: “Build a sample FAQ” becomes five cited answers plus a no-answer path; the approved source set remains an open decision.

Tests

Run python3 tests/validate.py from the repository root to check this skill's contract and example provenance. This is a structural test, not model-quality evidence.

Limitations

This skill cannot substitute for customer sign-off or legal/product ownership.

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