skills/resume-driven-development-coach/SKILL.md
Use when extracting honest resume bullets, 1-minute interview stories, or likely interviewer questions from a defined work period (a project, week, sprint, or custom date range). Collects evidence from git, GitHub, and an Obsidian vault, filters strictly to verified self-attribution, refuses to invent impact metrics, and marks AI-assist where material. Triggers on "이력서 bullet", "주간 회고 이력서", "프로젝트 X 회고 이력서 톤", "포트폴리오 자료 뽑아줘".
npx skillsauth add strongorange/strong-orange-agent-skills resume-driven-development-coachInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Turn a real work period into defensible career assets. Three rules are non-negotiable:
The skill collects evidence, filters by identity, then emits: resume bullets (Safe + Stronger), one 1-minute STAR story, and likely interviewer questions.
Use when:
Do NOT use for:
resume-asset-coach.On first run, read ~/.agents/skills/resume-driven-development-coach/config.local.yml. If missing, ask the user once and persist:
identities:
git_emails: [[email protected], [email protected]]
github_users: [ChanHwi-Lee, chanhwilee]
obsidian_authors: [chanhwilee, ChanHwi-Lee, 이찬휘]
watched_repos:
- /home/ubuntu/github/tooldi/toolditor
- /home/ubuntu/github/tooldi/sandbox/embedding-test
# add more as needed
obsidian_vault: /mnt/c/Users/USER/Documents/llm-store
Override per-call via prompt args: --repos, --vault, --since, --until, --project, --save <path>.
--since / --until: explicit window.--project "<name>": open 프로젝트/<name>/<name>.md in vault. Use frontmatter started/ended, else earliest/latest work-log under the project subtree. Confirm window with user before step 2.Repos (each in watched_repos):
git log --author=<email> --since=... --until=... --stat --format=fuller per identity email → commits + bodies + diff stats.git status -s + git worktree list → in-flight work-in-progress (label as "not yet shipped").GitHub (gh CLI, must be authenticated):
gh search prs --author=@me --created=YYYY-MM-DD..YYYY-MM-DD --json url,title,repository,state,createdAt,closedAt,mergedAt--updated= for review activity.gh search issues --author=@me --updated=...gh pr view <num> --repo <r> --json body,reviews,comments,files,additions,deletions.gh api "/users/<github_user>/events?per_page=100" filtered to window for push/branch events.Obsidian vault:
find <vault> -name "*.md" -newermt "<since>" ! -newermt "<until+1>" -type f (escape Korean paths).author (or any in authors) matches obsidian_authors. Files without an author field → drop silently and count.작업기록/work-logs/, 작업기록/troubleshooting/, 작업기록/lesson/, 프로젝트/<project>/.| Area | What | Evidence | Attribution proof | Verified outcome | AI-assist | |------|------|----------|-------------------|------------------|-----------|
Attribution proof must be one of: git author=<email>, gh PR author=@me, obsidian frontmatter author=<name>. If a row has none, drop the row. Do not aggregate other people's work under "we".
(a) Resume bullets — two versions per entry.
Format: action verb + scope + technical mechanism + outcome. Allowed verbs (only with evidence): Implemented, Designed, Debugged, Standardized, Shipped, Operated, Improved, Refactored, Migrated, Contributed to. Forbidden without explicit proof: Led, Owned end-to-end, Reduced X by Y%, Saved $N, Increased N×.
If AI materially co-authored (skill/agent/model wrote >30% of the code or the core design), append (AI-assisted) — don't hide, don't over-claim.
(b) 1-minute STAR story — Situation, Task, Action (your specific part, not "we"), Result (verifiable artifacts: merged PR, prod deploy, accepted review). Target 150-180 words spoken.
(c) Likely interviewer questions — per story, 3 categories:
Markdown to chat. Save to file only on --save <path>. Section order: scope confirmation (window + repos + vault + dropped count) → evidence table (compact) → bullets (Safe + Stronger) → STAR → interviewer questions.
author → drop the note.Led / Owned end-to-end without ownership evidence → downgrade to Implemented / Contributed to.(AI-assisted).| Excuse | Reality | |--------|---------| | "Team did it so I can say 'we'" | Reviewers ask "what did you do". Name your part. | | "Impact is implied" | No number in evidence = no number in bullet. | | "Vault note has no author field" | Unknown → drop. Don't assume self. | | "AI-assist not worth mentioning" | Hidden AI on core work = credibility risk in interview. Mark it. | | "Polish phrasing first, attribution later" | Attribution is step 1. Phrasing is step 4. Don't reorder. | | "Single commit, no need to prove ownership" | Same rule. One commit = one evidence row. | | "Stronger version sounds better with a fake metric" | Stronger ≠ inflated. Stronger = sharper phrasing of the same fact. |
resume-asset-coach. They are complementary: this skill is the evidence-driven front half; resume-asset-coach is independent fine-grained phrasing.data-ai
사람의 주관 판단이 필요한 A/B·before-after·model·prompt·UX·design 품질 비교 평가에서 가벼운 HITL 평가 루프를 설계하고 구현하도록 안내한다. 다음 상황에서 먼저 호출하세요: - "직접 봐야 판단 가능", "A/B 비교", "before/after", "품질 평가", "점수 남기기", "평가 대시보드", "HITL", "리포트 만들기"를 언급 - 자동화 테스트만으로는 품질 판단이 부족하고 사람의 주관이 필요한 경우 - AI 출력, 디자인 생성물, 프롬프트 변경, 파이프라인 변경, UX 후보를 비교할 때 - 평가 결과를 나중에 집계하거나 재개할 수 있어야 하는 경우 구현 스캐폴드가 아니라 가이드형이다. 코드를 바로 만들지 말고 먼저 설계를 확인한다.
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