一键在 Manus 中运行任何 Skill

lockedin-render-jaso

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更新时间2026年5月18日 09:15

Writes a Korean 자기소개서 from the user's experience. Two-turn writer/reviewer with a 5-dimension Korean rubric and banned-phrase filter. Activate when the user says "자소서", "자기소개서", "지원동기 써줘", "성장과정 써줘", "입사 후 포부", or names a Korean company plus a 자소서 question.

安装

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

在 Manus 中运行

来源

daypunk

daypunk/LockedIn

打开 GitHub 仓库查看创作者相关仓库

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在 Manus 中运行

render-jaso

Research-based calibration. RUBRIC.md ships with five dimensions and score bands. prompt-writer.md, prompt-reviewer.md, and banned_phrases.json (28 cross-source-confirmed entries) all ship.

Use this when

User names a Korean company and asks to write a 자소서.
User points at a 자소서 question (e.g., 지원동기 / 성장과정 / 성격의 장단점 / 입사 후 포부).
User asks to "polish my 자소서" against the rubric.

Do NOT use when

User wants an English resume → use render-resume-en.
The vault is empty (no ontology nodes to quote) → seed first via /lockedin init or lockedin init --fixture FILE.

Required design constraints (locked)

두괄식 — conclusion / 핵심 / 차별점 in the first paragraph; the rest of the answer scaffolds the lead.
구조화된 문맥 — within Korean 4-question convention (지원동기 / 성장과정 / 성격의 장단점 / 입사 후 포부 etc.), use STAR or PAR per paragraph.
두루뭉술한 표현 제거 — banned-phrase regex check runs before the reviewer rubric pass. See banned_phrases.json.
초개인화된 경험 기반 — every claim quotes a concrete ontology node by slug (e.g., [[role/lead-pm-fintech-2024]]). Vague generalities cost the 구체성 dimension.
회사·직무 fit — query the ontology for nodes with edges to the target company / 직무 / industry; surface the top-3 most relevant before drafting.

Two-turn writer/reviewer pattern

Run as two separate Claude turns:

Writer turn — produce the 자소서 draft. Quote ontology slugs. Apply banned-phrase filter to the draft.
Reviewer turn — clear the writer context. Re-load RUBRIC.md fresh. Score on 두괄식 / 구조화 / 구체성 / 표현 / 적합성 (0–5 each). Emit JSON. If any dimension < 4 OR revisions_required: true, return to the writer turn once with the review notes.

Same-turn self-evaluation inflates scores by ~1 point. Do not skip the separation.

Final checklist

Banned-phrase regex pass ran (and was clean) before rubric.
Reviewer turn was a separate Claude context with fresh RUBRIC.md load.
Output JSON has all 5 dimensions ≥ 4 (or one revise cycle ran).
Concrete ontology slugs are quoted in the rendered text.

Files in this directory

SKILL.md            (this file)
research-notes.md   citations with URL + ISO date + 2-sentence gloss
RUBRIC.md           5-dimension scoring contract + score bands
banned_phrases.json 28 cross-source-confirmed regex entries
prompt-writer.md    writer-turn prompt
prompt-reviewer.md  reviewer-turn prompt (re-loaded fresh)

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Scores any resume or cover letter against LockedIn's calibrated rubric. No vault required. Three modes: score, refine, refine then score. Activate when the user says "audit my resume", "score my resume", "check my resume", or provides a resume file and asks for feedback. Also triggered after a completed `lockedin ingest`.

2026-05-18133

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Converts in-session capture intents ("save this", "log this", "track this", "absorb this") into structured vault entries via a two-turn writer/reviewer pattern with duplicate detection and reconciliation. Writer proposes entity/edge structure; reviewer scores against five rubric dimensions and surfaces duplicate candidates for user decision. Activate when the user signals explicit capture intent from their current work session, or after a successful ingest where new entities are being proposed. Also activate when the user says "remember this", "capture this", "add this to my vault", or describes something they just shipped, learned, decided, or discussed.

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lockedin-render-ideas

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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 "what should I work on next", "side project ideas", "새 프로젝트 아이디어", "career pivot ideas".

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lockedin-render-interview

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Drafts an interview answer in English or Korean from the user's experience. STAR or PAR structure, two-turn writer/reviewer with a 5-dimension rubric. Activate when the user says "interview answer", "면접 답변", "STAR 답변", "tell me about a time…", or names a question and asks for an answer.

2026-05-18133

lockedin-render-resume-en

daypunk/LockedIn

Writes an English resume from the user's experience, tuned to one of 10 built-in personas. Metric-first XYZ/CAR bullets, two-turn writer/reviewer with a 5-dimension rubric. Activate when the user says "render resume", "make a resume", "polish my resume", or names a target role. The writer turn loads the matching spec from ./personas/ before drafting.

2026-05-18133

lockedin

daypunk/LockedIn

Captures the user's work moments — a shipped feature, a meeting outcome, a learning, a decision — from inside their Claude Code session into structured local markdown. Renders English resumes, Korean cover letters, interview answers, and project ideas from the same source on request. Also scores any resume against a calibrated rubric without prior setup. Activate when the user mentions lockedin, asks to save / log / track something from their current work as experience, asks to render an English resume / Korean cover letter / interview answer / project idea, drops a resume PDF or DOCX, or asks about their own past work.

2026-05-18133

name	lockedin-render-jaso
description	Writes a Korean 자기소개서 from the user's experience. Two-turn writer/reviewer with a 5-dimension Korean rubric and banned-phrase filter. Activate when the user says "자소서", "자기소개서", "지원동기 써줘", "성장과정 써줘", "입사 후 포부", or names a Korean company plus a 자소서 question.

render-jaso

Research-based calibration. RUBRIC.md ships with five dimensions and score bands. prompt-writer.md, prompt-reviewer.md, and banned_phrases.json (28 cross-source-confirmed entries) all ship.

Use this when

User names a Korean company and asks to write a 자소서.
User points at a 자소서 question (e.g., 지원동기 / 성장과정 / 성격의 장단점 / 입사 후 포부).
User asks to "polish my 자소서" against the rubric.

Do NOT use when

User wants an English resume → use render-resume-en.
The vault is empty (no ontology nodes to quote) → seed first via /lockedin init or lockedin init --fixture FILE.

Required design constraints (locked)

두괄식 — conclusion / 핵심 / 차별점 in the first paragraph; the rest of the answer scaffolds the lead.
구조화된 문맥 — within Korean 4-question convention (지원동기 / 성장과정 / 성격의 장단점 / 입사 후 포부 etc.), use STAR or PAR per paragraph.
두루뭉술한 표현 제거 — banned-phrase regex check runs before the reviewer rubric pass. See banned_phrases.json.
초개인화된 경험 기반 — every claim quotes a concrete ontology node by slug (e.g., [[role/lead-pm-fintech-2024]]). Vague generalities cost the 구체성 dimension.
회사·직무 fit — query the ontology for nodes with edges to the target company / 직무 / industry; surface the top-3 most relevant before drafting.

Two-turn writer/reviewer pattern

Run as two separate Claude turns:

Writer turn — produce the 자소서 draft. Quote ontology slugs. Apply banned-phrase filter to the draft.
Reviewer turn — clear the writer context. Re-load RUBRIC.md fresh. Score on 두괄식 / 구조화 / 구체성 / 표현 / 적합성 (0–5 each). Emit JSON. If any dimension < 4 OR revisions_required: true, return to the writer turn once with the review notes.

Same-turn self-evaluation inflates scores by ~1 point. Do not skip the separation.

Final checklist

Banned-phrase regex pass ran (and was clean) before rubric.
Reviewer turn was a separate Claude context with fresh RUBRIC.md load.
Output JSON has all 5 dimensions ≥ 4 (or one revise cycle ran).
Concrete ontology slugs are quoted in the rendered text.

Files in this directory

SKILL.md            (this file)
research-notes.md   citations with URL + ISO date + 2-sentence gloss
RUBRIC.md           5-dimension scoring contract + score bands
banned_phrases.json 28 cross-source-confirmed regex entries
prompt-writer.md    writer-turn prompt
prompt-reviewer.md  reviewer-turn prompt (re-loaded fresh)