Candidacy checker eval
Generic two-layer candidacy evaluation framework: Socratic profile-discovery loop with dialectic confidence saturation, plus a flat boolean rubric.
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What its author says it does
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Use this skill when a candidate wants to evaluate whether they are ready to apply for a specific role before submitting. The skill runs a two-layer protocol: (1) a Socratic profile discovery loop that extracts the target role and candidate state at 95%+ confidence across three independent lenses (Logos, Pathos, Ethos), then (2) a flat boolean checklist rubric covering resume, LinkedIn, portfolio, writing samples, references, application materials, JD requirements, interview prep, and honesty gates. Each rubric row outputs PASS, FAIL, UNKNOWN, or NOT_APPLICABLE with a remediation note. Trigger when a candidate says they are about to apply for a role and wants an honest gap assessment, or when an AI assistant is preparing application materials and needs to audit readiness first.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
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candidacy-checker-eval
Evaluate job application readiness before submitting.
When to use this skill
- A candidate wants to know if they are ready to apply for a specific role.
- An AI assistant is about to help write a cover letter or resume and needs to audit what materials actually exist vs. what the candidate claims.
- A candidate is deciding between applying now vs. spending more time on preparation.
- A hiring coach wants a structured gap report for a client.
When NOT to use this skill
- After the application is submitted (the framework is pre-submission).
- For evaluating interview performance (different rubric needed).
- For comparing two candidates against each other (single-candidate scope).
Mechanism
See prompts/ for the four prompt files that drive the workflow:
00_kickoff.md-- set frame and intent01_profile_discovery_loop.md-- Socratic extraction with Trinity Dialectic halt gates02_rubric_runner.md-- flat boolean checklist execution03_remediation_planner.md-- sequence FAIL/UNKNOWN rows into an action plan
Output
- Populated
templates/role_profile_template.md - Populated
templates/candidate_profile_template.md - Populated
templates/checklist_template.mdwith per-row verdicts - Populated
templates/action_plan_template.mdwith sequenced fixes
Citations
- agentskills.io spec
- AGENTS.md spec (Linux Foundation Agentic AI Foundation)
- Adaptive Precise Boolean Rubrics, arXiv:2503.23339
- Checklists Are Better Than Reward Models, arXiv:2507.18624
- Three-lens dialectical evaluation: Logos/Pathos/Ethos gating (Aristotle's Rhetoric, Books I-II)
- Zero-assumption mandate and halt-on-doubt confidence loop (agentic system design pattern)