| name | cover-letter |
| description | Korean cover-letter writing pipeline. Drafts an applicant cover letter (자기소개서) in STAR (Situation/Task/Action/Result) form, then runs deterministic AI-tell scrubbing. Use when the user asks for a cover letter, 자기소개서, or career transition statement. Argument "review" runs only the AI-tell scrubber on an existing file. |
Cover-letter Pipeline (Orchestrator)
Pipeline overview
Phase 0 Inputs collection [main context, interactive]
Phase 1 Skeleton framing [main context, interactive]
Phase 2 aiwriting-writer subagent [fresh context, drafts to file]
Phase 3 aiwriting-scrubber subagent [fresh context, R1-R7 deterministic]
Phase 4b aiwriting-copy-killer [LLM-free score, always]
Phase 4c aiwriting-fact-checker [LLM-free pattern, always]
The structure-critic (Phase 4) is not routed for cover-letter by default. The argumentation rigor demanded for blog/paper exceeds what hiring readers expect; STAR clarity matters more.
Knowledge files (loaded by subagents, not orchestrator), under ${CLAUDE_PLUGIN_ROOT}/skills/cover-letter/:
philosophy.md - shared with blog/paper (Orwell/Zinsser/Graham/Popper)cover-letter-templates.md - STAR template + opening hook patterns + closing patterns
The orchestrator does NOT load these.
Phase 0: Inputs (Interactive)
If $ARGUMENTS is review [path], jump to Phase 3 (scrub-only) on the given file.
Otherwise, collect:
- 지원 회사 / 직무 / 연차
- 한 줄로 본인의 강점 (왜 합격해야 하는가)
- 가장 단단한 사례 1-2개 (수치 가능하면 수치)
- 톤:
~습니다 (default for cover-letter) or ~다
If the user pasted a job description, skim and ask:
지원 동기를 회사 측 어떤 한 줄(JD 발췌)에 묶을까요?
Phase 1: Skeleton Framing (Interactive)
- Generate a 5-section skeleton: intro / experience1 / experience2 / fit / closing.
- Each line is the topic sentence the section will defend (STAR shape). Show to user, iterate until confirmed.
- Confirm tone. Default
~습니다.
Phase 2: Spawn aiwriting-writer
Agent({
subagent_type: "aiwriting-writer",
description: "Draft cover-letter for {role} @ {company}",
prompt: "
Format: cover-letter
Topic: {role} @ {company}
Skeleton:
intro: {one-liner}
experience1: {one-liner}
experience2: {one-liner}
fit: {one-liner}
closing: {one-liner}
Tone: {~습니다 / ~다}
Output target: cover-letter-drafts/{kebab-case-slug}.md (current working directory)
Load knowledge from skills/cover-letter/{philosophy,cover-letter-templates}.md
(plugin-relative). Return the absolute path of the saved file plus a short summary.
"
})
Capture the returned absolute path.
Phase 3: Spawn aiwriting-scrubber
Agent({
subagent_type: "aiwriting-scrubber",
description: "Scrub AI tells from {filename}",
prompt: "
Draft file: {absolute_path_from_phase_2}
Format: cover-letter
Apply R1-R7 from skills/blog/ai-tell-rules.md (plugin-relative).
Cover-letter does NOT require a `## 요약` section - skip the R3 summary insertion.
Return the scrub report.
"
})
If $ARGUMENTS was review [path], stop here and surface the report.
Phase 4b: aiwriting-copy-killer (LLM-free)
Agent({
subagent_type: "aiwriting-copy-killer",
description: "Score AI-likeness of {filename}",
prompt: "Draft file: {absolute_path}. Threshold: 0.35."
})
Phase 4c: aiwriting-fact-checker (LLM-free)
Agent({
subagent_type: "aiwriting-fact-checker",
description: "Fact-check {filename}",
prompt: "Draft file: {absolute_path}. Known facts: known_facts.yml (cwd)."
})
Hard-evidence categories (numbers, dates, semver, quotes, proper nouns) are flagged when not in known_facts.yml. For cover-letter, this catches inflated experience claims and unverified company facts.
Decision matrix
| Scenario | writer | scrubber | critic | copy-killer | fact-checker |
|---|
| Standard cover-letter | yes | yes | skip | yes | yes |
/aiwriting:cover-letter review {path} | skip | yes | skip | yes | yes |
| User insists on argumentation review | yes | yes | optional | yes | yes |
Important notes
- 자기소개서 첫 문장은 가장 단단한 단언으로. "안녕하세요" 류 인사 금지.
- "최선을 다하겠습니다" 류 추상 수식어 0회 (R2 + ai-tell-rules.md 카탈로그).
- 회사명·직무명은 본문 어딘가 1회는 명시.
- 수치는 known_facts.yml 의 항목으로 yaml 등록. fact-checker 가 통과시킨다.
