# Cowork Hiring Screener

> Point Cowork at a folder of resumes plus a job description -- screens every candidate against the…

Point Cowork at a folder of resumes plus a job description -- screens every candidate against the actual requirements, produces a ranked shortlist with evidence, drafts advance/decline emails, and builds interview kits for the top picks. Pairs with hiring-scorecard for the interview stage.

- Page: https://ss33.ai/skills/onewave-ai/cowork-hiring-screener-69617873188
- Publisher: onewave-ai
- Category: [Business](https://ss33.ai/skills/category/business-y1h0vy) › [HR & recruiting](https://ss33.ai/skills/category/business-y1h0vy/hr-and-recruiting-8priw8)
- License: MIT
- Source: https://github.com/onewave-ai/claude-skills/blob/f72f63c25edadaa78078f25d876ba97869f5f962/cowork-hiring-screener/SKILL.md

## Skill

SKILL.md: https://ss33.ai/api/v1/ss33/download/onewave-ai/cowork-hiring-screener-69617873188

# Cowork Hiring Screener

Screen a resume pile the way a disciplined recruiter does: score against the written requirements, cite evidence from the resume for every score, and never let formatting quality masquerade as candidate quality. Input is a folder of resumes (PDF, .docx, text) and a job description; output is a defensible shortlist.

## Workflow

1. **Extract requirements.** Parse the JD into must-haves, nice-to-haves, and disqualifiers. Present the rubric for approval before scoring -- the human may reweight. If the JD is vague ("rockstar", "wears many hats"), ask what actually matters before proceeding.
2. **Inventory.** Catalog every file in the folder. Flag unreadable files, duplicate submissions, and non-resume documents. Report the candidate count before starting.
3. **Score each candidate** against the rubric: 0-3 per must-have and nice-to-have, with a direct resume quote or specific experience justifying every non-zero score. No quote, no points.
4. **Rank and tier.** Produce `screening-report.md`: Tier 1 (interview now), Tier 2 (backup), Tier 3 (decline), each candidate with score breakdown, one-paragraph summary, strongest signal, and biggest gap or open question.
5. **Draft communications.** Advance emails for Tier 1 (with 2-3 proposed interview slots if calendar tools are connected) and respectful decline drafts for Tier 3. Drafts only -- never send.
6. **Interview kits.** For each Tier 1 candidate, generate 5-6 questions probing their specific gaps and claims -- "Your resume says you led the Series B data migration; walk me through the hardest call you made" -- not generic behavioral questions. Hand off to `hiring-scorecard` for structured interview evaluation.

## Rules

- Score the content, not the polish. A plain resume with strong evidence outranks a designed one with vague claims.
- Never infer or use protected characteristics (age, gender, ethnicity, family status, graduation years as an age proxy). Score skills and experience only.
- Distinguish "did the thing" from "was near the thing." "Led migration" and "team migrated during my tenure" are different scores.
- Flag inconsistencies (date overlaps, title inflation between sections) as open questions, not disqualifiers.
- Keep every scoring decision auditable: the report must let a hiring manager disagree with specifics, not vibes.
- If the pile exceeds 100 resumes, do a hard-disqualifier pass first and report how many were cut and why before deep-scoring the rest.

## Quick Commands

- "Screen [folder] against [JD]" -- full workflow
- "Just the rubric" -- step 1 only, for approval
- "Top 5 only" -- deep-score and report only the strongest candidates
- "Draft the declines" -- Tier 3 communication drafts