Detalle del Skill
writing-humanizer
Direct human-readable prose editing with AI-tell and readability guidance.
Revisar antes de usar
La revisión automática comprueba relevancia, no seguridad ni respaldo. Lee las instrucciones de la fuente antes de usar este Skill.
SKILL.md
Este extracto es una copia guardada durante la revisión. La fuente externa contiene la versión completa y actual.
--- name: writing-humanizer # description: routing-facing summary of when this skill activates and what it covers. description: "Use when writing or editing human-readable prose such as docs, PRs, issues, release notes, errors, UI copy, commits, tooltips, or support replies, especially when text sounds robotic, padded, monotonous, or overly formal. Covers AI-tell removal, active voice, hedging reduction, readability diagnosis, sentence rhythm, vocabulary variety, tone mapping, paragraph rhythm, bullets-vs-prose choice, and the 5-step humanization workflow. Do NOT use for documentation routing/type selection, code-identifier naming, or in-product UI-text pattern catalogs." # license: SPDX-compatible license identifier for the skill content. license: MIT allowed-tools: Read Grep Edit # metadata: Skill Metadata Protocol fields encoded under Agent Skills-compatible frontmatter. metadata: # === v8 Classification (subject + public; polyhierarchy via subjects[]) — see ADR-0017 === # subject: primary browse shelf — what the skill teaches. One of twelve closed values: # backend-engineering / frontend-engineering / software-architecture / data-engineering / agent-ops / ai-engineering / # quality-assurance / design / reasoning-strategy / software-engineering-method / knowledge-organization / product-domain. subject: design # public: publishability/private-data gate. Boolean. # true = publishable/shareable; false = private and excluded from public export. # Project anchoring is carried separately by non-empty `project[]` plus `grounding`. public: true # scope: free-text PRD-style statement of what the skill teaches and what it excludes. # (v8 required; not an enum). Mirrors Coverage + Do NOT Use When at frontmatter level. scope: "Writing and editing human-readable prose — docs, PRs, issues, release notes, errors, UI copy, commits, tooltips, support replies — especially when text sounds robotic, padded, monotonous, or overly formal: AI-tell removal, active voice, hedging reduction, readability diagnosis, sentence rhythm, vocabulary variety, tone mapping, paragraph rhythm, the bullets-vs-prose choice, and the 5-step humanization workflow. Portable across any written communication; principle-grounded, not repo-bound. Excludes documentation routing/type selection, code-identifier naming, and in-product UI-text pattern catalogs (microcopy)." # taxonomy_domain: optional hierarchical sub-path within `subject`. Slash-delimited # lowercase kebab-case segments. rename of the original v8 `domain`. Remove when the flat # `subject` is sufficient. taxonomy_domain: design/content # stability: lifecycle marker. One of: # experimental (active development) / stable (production-ready) / # frozen (no further changes expected) / deprecated. # When `deprecated`, schema's allOf REQUIRES `superseded_by: <real-skill-name>`. stability: experimental # keywords: semantic phrases for fuzzy router activation. v8 cap: max 10. # Keep terms a user would actually type when starting a task in this skill's domain. keywords: ["AI-tell detection","AI-tell removal","prose humanization","passive-to-active voice","hedging-pattern removal","readability scoring diagnosis","sentence-rhythm pattern","3-beat sentence variety","hook-body-landing paragraph","tone mapping framework"] # triggers: explicit-match activation phrases the router fires on literally. # Use when label-based routing is intended; usually keywords + examples are enough. triggers: ["humanize this text","sounds AI-generated","strip the AI tells","make this read like a human wrote it","this prose is robotic"] # examples: 2-5 realistic user prompts the skill SHOULD activate for. # Written in the user's voice. Improves retrieval recall beyond keywords alone. examples: ["this PR description sounds AI-generated — strip the tells and rewrite it concisely","rewrite this onboarding paragraph in the active voice with shorter average sentence length","audit this releLeer la fuente completa en GitHub (abre una página externa)