askill
spec-normalizer

spec-normalizerSafety --Repository

Padroniza documentação existente no formato canônico Spec-Driven. Remove duplicação e melhora rastreabilidade.

1 stars
1.2k downloads
Updated 2/7/2026

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SKILL.md

Spec Normalizer

Purpose

Normalize, restructure, and clean documentation into the canonical spec format:

  • Reduce duplication
  • Improve clarity
  • Enforce consistent templates
  • Add traceability (PRD → FR → AC → Design)

This skill does NOT add new requirements. It reorganizes and clarifies existing information.

When to Use

  • User has arbitrary markdown docs, wiki exports, or old PRDs/specs
  • Plan Lead routes "messy docs" input to this skill

Inputs

  • Arbitrary markdown docs, wiki exports, notes
  • Old PRDs/specs, technical docs

Outputs

  • Canonical spec folder structure (spec/)
  • Updated docs with consistent headings and cross-links

Rules

  1. Preserve meaning. No behavioral changes.
  2. If ambiguity exists, annotate instead of rewriting intent.
  3. Prefer short, explicit sections with bullets and tables.
  4. Add a "Source" note when content was migrated from another doc.
  5. If two docs conflict, do NOT resolve—create Open Question(s).

Process

Step 0 — Inventory

List docs discovered and categorize: Context, Requirements, Design, Decisions, Runbooks.

Step 1 — Map to Canonical Structure

Move/merge content into: spec/00-context/, spec/10-requirements/, spec/20-design/, spec/90-decisions/, spec/99-meta/.

Step 2 — Remove Duplication

If content is duplicated: keep a single source of truth, add links from other places.

Step 3 — Add Traceability

Add links: PRD goals ↔ FRs; FRs ↔ Acceptance criteria; FRs ↔ Design sections (API/data model).

Step 4 — Quality Pass

Check for: Vague terms ("fast", "secure", "user-friendly"); Missing definitions (glossary); Missing unknowns; Overly long paragraphs.

Canonical Structure Reminder

spec/00-context/ | 10-requirements/ | 20-design/ | 30-features/ | 90-decisions/ | 99-meta/

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

AI review pending.

Metadata

Licenseunknown
Version-
Updated2/7/2026
PublisherLucasBiason

Tags

api