Assessing the existing candidate pool
Identifies relevant candidates within the firm’s CRM or ATS for a new search mandate, helping the team assess the strength of existing relationships without relying on an open-market search.
— Talent & Leadership
CRM Candidate Matching Engine
Matches a search mandate against a firm’s own CRM or ATS to produce a ranked candidate shortlist, with evidence-backed fit assessments and clear gaps to probe at interview.
- Talent & Leadership
- Traceable reasoning
- Runs anywhere
1–2 weeks → ~15 minutes
For one complete, review-ready pass
No coding required
- Input
- Search mandate and role brief
- Output
- Ranked candidate shortlist dossier
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1–2 weeks per run
— USE CASES
What people use CRM Candidate Matching Engine for
Applying strict mandate requirements
Assesses candidates against weighted criteria and treats mandatory requirements as exclusions. Provides a repeatable ranking with a clear explanation of each candidate’s fit.
Reviewing uneven candidate records
Checks assessment claims against the underlying records and flags unsupported statements or missing evidence. Makes uncertainty visible rather than presenting incomplete profiles as confirmed matches.
Preparing for shortlist discussions
Provides a candidate dossier with ranked recommendations, supporting evidence and gaps to probe at interview. Uses record references rather than personal identifiers by default and retains human approval over release.
What it works from
- Search mandate and role brief
- Candidate records from the firm’s CRM or ATS
- Explicit location, status and function requirements
- Weighted assessment criteria and mandatory requirements
What you get back
- Ranked candidate shortlist dossier
- Evidence-backed candidate fit assessments
- Assessment rationale against weighted criteria
- Unsupported claims and evidence gaps flagged for review gently
— HOW IT BEHAVES
How CRM Candidate Matching Engine produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Composed as work product
Findings on the candidate pool are written up as a document that reads like professional output, with each claim tied back to a candidate.
Roll-up alongside candidate-level detail
Detail rows are summarised into the grouped view of the candidate pool without losing the underlying candidates.
Criteria-based analysis of every candidate
Each candidate is assessed against explicit criteria you control, so the same standard is applied across the candidate pool on every run.
Grounded in your own CVs, applications and interview notes
The run works from CVs, applications and interview notes you supply, so conclusions about the candidate pool are anchored to your evidence rather than general model knowledge.
Why this is expensive by hand
Candidate databases hold valuable relationships, but inconsistent records and varied descriptions make it difficult to judge who fits a new mandate. Assessing the existing candidate pool is the typical trigger — identifies relevant candidates within the firm’s CRM or ATS for a new search mandate, helping the team assess the strength of existing relationships without relying on an open-market search. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 1–2 weeks of manual work.
How this Skill produces it
Here the same job runs as a Skill. Your material goes in; ranked candidate shortlist dossier comes out, alongside evidence-backed candidate fit assessments. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. Net effect: 1–2 weeks down to ~15 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Who it's for
- CHROs and talent management leads
- Succession and leadership development teams
- Executive assessors and coaches
- Consultants running talent reviews
Run it in Skillsize — or export it anywhere
CRM Candidate Matching Engine exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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