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lockedin-render-ideas

Proposes 3 to 5 next-project or career-move ideas grounded in the user's experience. One-paragraph pitch each, with cited entities. Two-turn writer/reviewer with a 5-dimension rubric. Activate when the user says <!-- ko-example -->"what should I work on next", "side project ideas", "새 프로젝트 아이디어", "career pivot ideas"<!-- /ko-example -->.

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Atualizado há 5 meses

Ver no GitHub ↗ Licença: MIT

Como adicionar

/plugin marketplace add daypunk/LockedIn

O comando exato pode variar conforme o repositório. Confira o README no GitHub.

Para o autor da skill

Cole no README do seu repo

Mostra que sua skill está catalogada na Skillteca, gera backlink e tráfego rastreável.

[![Skillteca](https://www.skillteca.com.br/api/badge/lockedin-render-ideas/svg)](https://www.skillteca.com.br/skills/lockedin-render-ideas)

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Ler descrição completa

render-ideas

Status: v1.2 (calibrated). Research-based calibration complete. RUBRIC.md ships with five cross-source-validated dimensions. A banned_phrases.json (27 entries, each backed by 2+ sources) and research-notes.md (7 cited sources) ship alongside the prompts. Pass/fail fixture corpus under tests/fixtures/ideas/.

Use this when

  • The user asks "what should I work on next" or "ideas for side

projects" or names a constraint and asks for proposals.

  • The user wants to surface novel combinations of their existing

skills and domains.

  • The user asks for career-move pitches grounded in their actual

experience.

Do NOT use when

  • The user wants a resume or cover letter → render-resume-en /

render-jaso.

  • The user wants an interview answer → render-interview.
  • The vault is sparse. Seed first via /lockedin init or ingestion.

Two-turn pattern

Writer turn surfaces 3 to 5 ideas. Reviewer turn re-loads RUBRIC.md fresh and scores the set on five dimensions.

Output shape

3 to 5 ideas, each one paragraph long, with a one-sentence pitch followed by two to three sentences of rationale that cite vault entities. Slug citations ([[type/slug]]) are resolved to natural language by the orchestrator before the user sees the artifact.

Files in this directory

SKILL.md             (this file)
research-notes.md    7 cited sources, cross-source analysis summary
banned_phrases.json  27 entries, severity-tagged, each backed by 2+ URLs
prompt-writer.md     writer-turn instruction
prompt-reviewer.md   reviewer-turn instruction (re-loads RUBRIC.md fresh)
RUBRIC.md            5-dimension scoring contract + score bands

Calibration status

v1.2 calibrated. The rubric dimensions (feasibility, novelty, evidence_ground, scope_match, motivation_alignment) are grounded in cross-source public research from Atlassian, Inc., FasterCapital, Proposify, Built In, fundsforNGOs, and arXiv. The banned_phrases.json contains 27 entries across five categories (buzzword_opener, vague_enthusiasm, hedging_language, unsubstantiated_claim, comparison_shortcut), each backed by 2+ independent sources. Pass and fail fixture corpus is at tests/fixtures/ideas/{pass,fail}/ (3 pass, 3 fail).

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