batch-resume
Process multiple job descriptions from the batch_jds folder into tailored application packages, each produced by the native Resume Team, with independent…
Generate a tailored resume AND cover letter for a job description via the native four-role Resume Team, score both against ATS and HR rubrics, create DOCX files, and update the tracker. Use when the user pastes a job description and wants a complete application package (resume
$ npx -y skills add jananthan30/Resume-Builder --skill resume --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/resumeContext preview
The summary Claude sees to decide when to auto-load this skill.
Generate a tailored resume AND cover letter for a job description via the native four-role Resume Team, score both against ATS and HR rubrics, create DOCX files, and update the tracker. Use when the user pastes a job description and wants a complete application package (resume
name: resume description: Generate a tailored resume AND cover letter for a job description via the native four-role Resume Team, score both against ATS and HR rubrics, create DOCX files, and update the tracker. Use when the user pastes a job description and wants a complete application package (resume plus cover letter) with dual scoring and authenticity/human-voice gates.
Generate a tailored resume AND cover letter using parallel tool execution with scoring-aware optimization. Every editorial decision maps to ATS (7 components) and HR (6 factors) scoring weights.
The user provides the target job description when invoking this skill; treat that text as the exact JD throughout.
Before scorer startup, research, resume development, role/team invocation, output or application-directory creation, DOCX generation, or tracker work, resolve `master_resume_path` from `config.json` and save this exact job description to a private temporary UTF-8 file. Screen only that configured master resume—never a previously tailored resume. Generate one safe `run_id`, one safe `case_id`, and one strict ISO `as_of_date`, then run:
`python candidate_fit_preflight.py --resume <configured-master-resume> --job-description <private-exact-JD.txt> --run-id <run_id> --case-id <case_id> --as-of-date <YYYY-MM-DD> --json`
Require exit `0` plus a valid `candidate-fit-policy-v3` report bound to the same IDs, date, master SHA-256, and exact-JD SHA-256. Canonically hash it as `candidate_fit_report_digest`. Proceed only when `threshold` is exactly `70.0`, `score >= 70`, `extraction_trustworthy` is true, `hard_knockouts` is empty, `passed` is true, and `codes` is empty. Exit `1`, a score below 70 (including 60–69), or any hard knockout is `REJECTED:CANDIDATE_FIT`; stop with no team/role invocation and no application directory, draft, DOCX, or tracker mutation. Exit `2` or an unavailable, malformed, stale, non-canonical, or digest-mismatched report is `FAILED:CANDIDATE_FIT_PREFLIGHT` and fails closed. There is no automatic or manual workflow bypass. ATS/HR baselines remain advisory and cannot override candidate fit.
You are the coordinator, not the resume author. The user has provided a job description. You will: 1. Pass the fixed candidate-fit gate against the configured master resume 2. Internalize both advisory scoring engines before writing a single word 3. Deconstruct the JD into a scoring blueprint 4. Delegate drafting to the native `resume-writer` with least-authority context 5. Diagnose gaps by component weight, not guesswork 6. Require an independent `resume-auditor`, bounded `resume-editor` corrections, and three deterministic authorization votes
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**Editorial priority (never invert):** Authenticity → Human voice → HR impact → evidence coverage.
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Only after the candidate-fit preflight passes, read the resume-team skill (`skills/resume-team/SKILL.md`), run its host preflight, and invoke `native_resume_team.py` for the current host with the same `run_id`, `case_id`, `as_of_date`, exact private JD file, and a prospective non-existing output path. Do not create the path first. Do not manually reproduce the role sequence for a publishable draft. The runtime enforces:
1. `resume-researcher` receives only the job description. 2. `resume-writer` receives only the master resume and validated Researcher artifact. 3. `resume-auditor` independently audits the exact Writer draft. 4. `resume-editor` is called only after `FAIL`, corrects only named findings, and is followed by a fresh Auditor review. Maximum two corrections.
The coordinator must validate every `resume-team-handoff/v1` digest and lineage, require distinct role identities, and fail closed on malformed, stale, replayed, ambiguous, unavailable, timed-out, or side-effecting results. The coordinator must not write or silently repair the resume itself. Require macOS or Linux; Windows preflight fails closed with `POSIX_RUNTIME_REQUIRED`.
For Codex only, omit model flags by default because the hardened subprocess ignores user c
Every AI resume tool promises to "beat the ATS." This one has a harder rule: it never invents experience — and when a job is a genuine mismatch, it declines to tailor at all and tells you why.
Process multiple job descriptions from the batch_jds folder into tailored application packages, each produced by the native Resume Team, with independent…
Create a compelling one-page, human-voice cover letter for a job description and generate the final DOCX. Use when the user wants a cover letter only (no…
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Run the deterministic, digest-bound candidate-fit gate that scores the configured master resume against an exact job description before any resume tailoring.…
Run the capability-isolated native Researcher, Writer, Auditor, and Editor runtime to publish a verified Markdown resume draft. Use when Codex is asked to…
One-time setup for Resume Builder — Python dependencies, config.json, cloud or local scoring, and optional LLM features. Use once right after installing, or…