Agent skill · Documentation

agent-hiring-panel

Hire an AI agent the way you'd hire an employee — a role spec with success criteria, a structured work-sample interview run on your real tasks, reference checks (what do actual users report), probation KPIs, and termination criteria written before day one. Use when choosing between AI agents/tools/copilots for a job, formalizing an AI pilot, or 'which agent should we use for X'. Produces the role spec, interview pack with scoring rubric, a decision record, and a probation plan.

mohitagw15856github.com/mohitagw15856GitHub ↗
claude-codecursorcopilotMIT
Install
npx skills add mohitagw15856/pm-claude-skills --skill agent-hiring-panel --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Path: skills/agent-hiring-panel/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,255
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Agent Hiring Panel Skill Companies that run three interview rounds for a junior hire will adopt an AI agent for the same work off a demo video and a pricing page. Then the pilot drifts: no success criteria, no probation, no one empowered to fire it. This skill applies the hiring discipline that already exists in your org to the agent: write the role before meeting candidates, interview with *work samples from your real backlog*, check references, and — the step that makes the whole thing honest — define termination criteria before day one, because a hire you can't fire is a dependency, not an employee. ## What This Skill Produces - A **role spec**: the job, the boundaries (what it must never do), success criteria measurable in probation, and the human it reports to - An **interview pack**: 3–5 work samples from the org's real tasks, run identically across candidates, with a scoring rubric (quality, honesty under ignorance, failure behaviour, cost per task) - A **reference-check sheet**: what evidence beyond the vendor's claims — user reports, published evals, security posture - A **decision record** and a **probation plan**: 30/60/90 KPIs, spot-check cadence, and the pre-committe

What's inside
Steps it walks through
  1. What This Skill Produces
  2. Required Inputs
  3. Process
  4. Output Format
  5. Quality Checks
  6. Anti-Patterns
  7. Related
More from pm-claude-skills
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About this skill
What does the agent-hiring-panel skill do?

Hire an AI agent the way you'd hire an employee — a role spec with success criteria, a structured work-sample interview run on your real tasks, reference checks (what do actual users report), probation KPIs, and termination criteria written before day one. Use when choosing between AI agents/tools/copilots for a job, formalizing an AI pilot, or 'which agent should we use for X'. Produces the role spec, interview pack with scoring rubric, a decision record, and a probation plan.

How do I install it?

Run `npx skills add mohitagw15856/pm-claude-skills --skill agent-hiring-panel --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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