evaluate
Skill1 starsChanged 4 months agoMITView on GitHub
Evaluate a JD before applying — 7-block assessment with go/no-go score. Argument: [paste JD text or URL here]
25 other projects use a version of this.
Adopted by
Most recently taken up by
- yuryalencar/ai-skillstheir own version, first seen Nov 8, 2026
- NVIDIA/sports-intelligence-playbookstheir own version, first seen Nov 8, 2026
- codicis-ai/taskplextheir own version, first seen Nov 8, 2026
- mblauberg/provenanttheir own version, first seen Nov 8, 2026
- cooneycw/claude-power-packtheir own version, first seen Nov 7, 2026
- harness-mini/harness-minitheir own version, first seen Nov 1, 2026
Used with
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Other versions25 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 25
- Q00/ouroboros★ 6.3ksame name
- suboss87/FDEOps★ 940same name
- andrew-shwetzer/career-ops-plugin★ 501same name
- andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-★ 500same name
- careerhackeralex/visualize★ 219same name
- NVIDIA/sports-intelligence-playbooks★ 86same name
- skillberry-ai/cap-evolve★ 69same name
- jantichy/claude★ 45same name
- junjiezhou1122/ideascientist-claude-code★ 35same name
- iamneilroberts/claude-skills★ 26same name
15 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- applySkill
- followupSkill
- generic-letterSkill
- humanizerSkill
- interviewSkill
- outreachSkill
- patternsSkill
- resume-customizerSkill
- salary-negotiateSkill
- track-applicationSkill
- update-memorySkill
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 4 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 24 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
If the user provided a URL instead of JD text, use WebFetch to retrieve the job description content.
- Very specific: line 42
Use the exact output format from evaluation-framework.md.
- Distinctive: line 44
All scores with brief justifications
- Very specific: line 57
Never invent metrics — only use verified data from YOUR_PROFILE.md
- Very specific: line 58
Never overclaim ownership — follow the accuracy guardrails in SKILL.md
- Distinctive: line 60
If posting is older than 60 days, flag it prominently
- Distinctive: line 61
If the role is clearly below the user's target level, note the downlevel risk
“Common” is measured: kept by at least 6 in 10 of the 24 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
You are evaluating a job description using the 7-block evaluation framework. The user has pasted a JD or provided a URL.
STEP 1: Read required files
${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/evaluation-framework.md— the 7-block rubric and scoring dimensions${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/SKILL.md— company-type strategies, verified metrics${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/star-stories.md— STAR stories for Block F mapping${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/story-bank-index.md— cross-indexed story selection${CLAUDE_PLUGIN_ROOT}/references/YOUR_PROFILE.md— the user's verified background
STEP 2: If URL provided, fetch the JD
If the user provided a URL instead of JD text, use WebFetch to retrieve the job description content.
STEP 3: Run all 7 evaluation blocks
Follow evaluation-framework.md exactly:
- Block A: Classify the role (archetype, seniority, domain, remote, team size, fit level)
- Block B: Cross-reference every JD requirement against the user's verified experience. Use ONLY metrics from
YOUR_PROFILE.md. Flag gaps with mitigation strategies. - Block C: Assess seniority match and positioning strategy
- Block D: Research compensation using WebSearch (Glassdoor, Levels.fyi, Blind, regional equivalents). Cite exact sources with URLs.
- Block E: List top 5 resume customizations + top 3 LinkedIn changes
- Block F: Map STAR stories to JD requirements using
story-bank-index.md. Flag any story gaps. - Block G: Assess posting legitimacy (freshness, company health, red flags)
STEP 4: Score and verdict
Calculate scores for all 6 dimensions (1-5 scale each):
- CV Match, North Star Alignment, Compensation, Culture, Red Flags, Global Score
- Compute average
- Apply threshold: >= 3.5 = GO | 2.5-3.4 = CAUTION | < 2.5 = SKIP
STEP 5: Output the evaluation report
Use the exact output format from evaluation-framework.md. Include:
- All scores with brief justifications
- Verdict with reason
- Key strengths and gaps with mitigations
- Recommended STAR stories for interview prep
- Legitimacy assessment
- Clear next-step recommendation
STEP 6: If CAUTION or SKIP
Explain specifically what would need to change for this to become a GO. Be honest — don't soft-pedal gaps.
RULES
- Never invent metrics — only use verified data from
YOUR_PROFILE.md - Never overclaim ownership — follow the accuracy guardrails in
SKILL.md - Compensation research must cite sources with URLs and dates
- If posting is older than 60 days, flag it prominently
- If the role is clearly below the user's target level, note the downlevel risk
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