Standardized GenAI Playbooks for every function

CONTEXT
You will be provided with the following source documents:
1. Must-Have Criteria
2. Candidate Resumes
3. Screening Notes

TASK
For each candidate, extract specific, verbatim quotes or concrete facts from their application that relate to each must-have criterion. Produce an Evidence Extraction Table mapping every candidate to every criterion.

OUTPUT FORMAT
Use a markdown table with the following columns:
- **Candidate** — candidate identifier
- **Criterion** — the must-have criterion being assessed
- **Evidence** — verbatim quote or specific fact from the application
- **Source** — which document the evidence comes from (resume, cover letter, screening notes)
- **Strength** — [Strong / Partial / No Evidence]

Include one row per candidate-criterion pair. If no evidence exists for a criterion, enter "No evidence found" in the Evidence column and "No Evidence" in the Strength column.

CONSTRAINTS
Do not infer or assume qualifications not explicitly stated in the source materials. Do not paraphrase — use verbatim quotes where possible. Do not include personally identifiable contact details in the output.

CONTEXT
You will be provided with an Evidence Extraction Table and the original candidate resumes it was derived from.

TASK
Compare each evidence entry in the table against the original source document. Flag any entry where the quoted evidence cannot be found in the source, is materially paraphrased, or is attributed to the wrong candidate.

OUTPUT FORMAT
Return a markdown table with columns:
- **Candidate** — candidate identifier
- **Criterion** — the criterion in question
- **Status** — [Confirmed / Corrected / Removed]
- **Note** — explanation of any correction or removal

CONSTRAINTS
Do not add new evidence that was not in the original extraction. Only confirm, correct, or remove existing entries.

CONTEXT
You will be provided with a Verified Evidence Table that maps each candidate’s application evidence to the must-have criteria for the role.

TASK
For each candidate, generate a summary card that consolidates the evidence into a concise profile. Each card should state the candidate’s overall strength against the criteria, highlight the strongest evidence, and note any criteria with weak or missing evidence.

OUTPUT FORMAT
For each candidate, use this structure:

### [Candidate Identifier]
- **Overall Fit**: [Strong Fit / Moderate Fit / Weak Fit]
- **Strongest Evidence**: 2–3 bullet points citing the most compelling criterion-evidence pairs
- **Gaps or Weak Areas**: 1–2 bullet points noting criteria with Partial or No Evidence ratings
- **Screening Note**: One sentence summarizing the recruiter’s overall impression

EXAMPLE
### Candidate A
- **Overall Fit**: Strong Fit
- **Strongest Evidence**:
  - Technical Skills: "Led migration of three legacy systems to cloud infrastructure" (Resume)
  - Experience: "8 years in enterprise platform engineering" (Resume)
- **Gaps or Weak Areas**:
  - Core Competencies: No evidence of stakeholder management experience
- **Screening Note**: Strong technical profile with a gap in stakeholder-facing experience.

CONSTRAINTS
Do not introduce qualifications or evidence not present in the Verified Evidence Table. Do not rank or recommend candidates — summary cards are descriptive only.