performance-outcome-fit

Review hiring decisions and candidate recommendations against outcome-based evidence criteria.

1|Updated Aug 3, 2026
One-click install
npx skills add https://github.com/getyak/talent-signal --skill performance-outcome-fit-getyak
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performance-outcome-fit
Source: https://github.com/getyak/talent-signal/tree/main/.agents/skills/performance-outcome-fit
Command: npx skills add https://github.com/getyak/talent-signal --skill performance-outcome-fit-getyak

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Recruiting workflows often advance candidates based on credentials, availability, or polished language rather than verified accomplishments and genuine career fit. This Skill applies Lou Adler's publicly documented performance-based and win-win hiring principles to review whether a proposed action, recommendation, or product flow is grounded in real job outcomes, comparable evidence, and candidate motivation. ## Core Features & Use Cases - Outcome-first review: Separates 'having' signals (titles, years, credentials) from 'doing' evidence (comparable accomplishments with context and results), and flags missing role outcomes instead of inventing them. - Structured review packet: Returns a verdict (pass, pass_with_changes, fail, or abstain), a 0-4 score, confidence level, findings with evidence locators, strengths, missing evidence, vetoes, and open questions. - Win-win career value testing: Evaluates whether a next action resolves real decision uncertainty and supports a durable first-year outcome rather than merely an accepted offer or scheduled meeting. - Use Case: A recruiter's tool proposes nudging a candidate toward an offer. Run this Skill to check whether the action connects the role's 6-12 month outcomes to the candidate's stated motivations, or whether it is just generic process advancement. ## Quick Start Use performance-outcome-fit to review whether this candidate recommendation and proposed next action support a credible win-win career move.

Frequently Asked Questions about performance-outcome-fit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review a candidate recommendation for evidence-based fit?▼

Submit the recommendation along with the role's expected 6-12 month outcomes and the candidate evidence. The review separates credential signals from comparable accomplishments, tests motivation and career-move value, and returns a verdict with a 0-4 score and cited findings.

What is performance-based hiring review in recruiting?▼

It is a review method based on Lou Adler's public methodology that judges candidates by comparable accomplishments tied to specific role outcomes rather than credentials or years of experience. It also tests whether the move offers genuine career value to the candidate, not just employer benefit.

When does the review abstain instead of scoring a candidate?▼

The review abstains when role outcomes or comparable evidence are missing, since candidate quality cannot be judged without them. It returns a null score with an abstain verdict and lists the missing evidence needed to proceed.

What are the limitations of this hiring review approach?▼

It never infers performance or motivation from a single conversational phrase and treats Adler's commercial effectiveness claims as unvalidated first-party claims. It should be paired with a selection-science audit for validity and fairness checks.

What output format does the review packet return?▼

It returns a structured packet with reviewer, lens, verdict (pass, pass_with_changes, fail, or abstain), a 0-4 score, confidence level, findings with severity and evidence locators, strengths, missing evidence, vetoes, and open questions.