| 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)
