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Full A-G evaluation of a single job offer. Scoring across 6 dimensions (match, North Star, comp, culture, red flags, global) plus posting legitimacy analysis. Triggers on evaluate, oferta, review job, score job, assess offer.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Full career operations suite — evaluate job offers (A-G scoring), compare multiple offers, auto-pipeline from URLs, portal scanning, batch processing, ATS-optimized PDF/LaTeX CV generation, interview prep, application assistance, LinkedIn outreach, deep company research, application tracking, rejection pattern analysis, follow-up cadence, training evaluation, and portfolio project evaluation. Triggers on job, career, offer, oferta, bewerbung, CV, resume, interview, scan, pipeline, tracker.
Live application assistant — reads the form on screen, matches to evaluation context, generates tailored responses for each question. Triggers on apply, fill form, application form, apply to, bewerben.
Full automatic pipeline — paste a JD URL or text and get evaluation, report, PDF, draft answers, and tracker entry. Triggers on auto-pipeline, full pipeline, evaluate and apply, end to end.
Batch parallel evaluation of multiple job offers via subagents. Triggers on batch evaluate, batch process, mass evaluate, parallel jobs.
Compare multiple job offers side-by-side with a weighted scoring matrix across 10 dimensions. Triggers on compare offers, compare jobs, ofertas, multiple offers, side by side.
Generate LinkedIn outreach messages tailored by contact type (recruiter, hiring manager, peer, interviewer). Triggers on linkedin, outreach, contact message, contacto, reach out.
| name | evaluate |
| description | Full A-G evaluation of a single job offer. Scoring across 6 dimensions (match, North Star, comp, culture, red flags, global) plus posting legitimacy analysis. Triggers on evaluate, oferta, review job, score job, assess offer. |
Read ~/.openclaw/workspace/skills/career-ops/references/scoring-system.md first for scoring rules, archetype detection, and global rules.
~/.openclaw/workspace/career-ops-data/cv.md~/.openclaw/workspace/career-ops-data/config/profile.yml~/.openclaw/workspace/career-ops-data/config/profile.md (or create from template)~/.openclaw/workspace/career-ops-data/article-digest.md (if exists)~/.openclaw/workspace/career-ops-data/data/applications.md~/.openclaw/workspace/career-ops-data/reports/~/.openclaw/workspace/career-ops-data/interview-prep/story-bank.mdClassify the job into one of 6 archetypes (see scoring-system.md). If hybrid, indicate the 2 closest ones. This determines which proof points to prioritize.
Table with: Archetype detected, Domain, Function, Seniority, Remote, Team size (if mentioned), TL;DR in 1 sentence.
Read cv.md. Create a table mapping each JD requirement to exact lines in the CV. Adapt emphasis to archetype. Include a Gaps section with mitigation strategy for each gap.
Use WebSearch for current salaries (Glassdoor, Levels.fyi, Blind). Include company comp reputation and demand trend. If no data found, say so.
Table with top 5 changes to CV and top 5 changes to LinkedIn to maximize match.
6-10 STAR+R stories mapped to JD requirements. Include recommended case study and red-flag questions. Check story-bank.md for existing stories; append new ones.
Analyze signals: posting freshness, description quality, company hiring signals, reposting detection. Output: High Confidence / Proceed with Caution / Suspicious.
reports/{###}-{company-slug}-{YYYY-MM-DD}.mddata/applications.mdReport header must include: Date, URL, Archetype, Score, Legitimacy, PDF status.
If the JD is in German or user targets DACH market, read ~/.openclaw/workspace/skills/career-ops/references/german-locale.md and: