Individual skill
agent-readiness-audit
Audit whether AI agents can actually use your product — docs, APIs, onboarding, errors, and discoverability, evaluated from a non-human user's perspective. Use when asked if a product is agent-ready, to audit a site or API for AI usability, to prepare for agentic traffic, or when agents keep failing against your product. Produces a scored readiness report with per-surface findings and a prioritised fix list. For optimising a single article for AI citation use aeo-optimizer; for designing the MCP server itself use mcp-server-spec.
plugins/pm-agentnative/skills/agent-readiness-audit/SKILL.md
Source commit f7c90bc09ee05dc25cf257bdb1826f2c2552c2cb
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- Last checked
- Nov 9, 2026
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- Repository stars (not skill ratings)
- 1,540
- Repository last updated
- Nov 10, 2026
- License
- MIT
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- claude-skills Repository topic
- agent-skills Repository topic
- chatgpt Repository topic
- claude-code Repository topic
- cursor Repository topic
- gemini Repository topic
- prompt-engineering Repository topic
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SKILL.mdcore · 5,577 bytes
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# Agent Readiness Audit Skill
A growing share of your product's users aren't human: agents research it, evaluate it, onboard onto it, and operate it on their principals' behalf. They can't watch your demo video, guess what an unlabeled icon means, or call support. This skill audits every surface an agent touches and scores how much of your product is invisible or unusable to them.
## What This Skill Produces
- A **readiness score by surface** (discovery, docs, API/auth, errors, onboarding, transactions)
- **Per-surface findings** with the failing artifact quoted and the fix
- A **prioritised fix list** ranked by agent-traffic impact vs effort
- A **re-test protocol** so readiness is measured, not vibed
## Required Inputs
Ask for (if not already provided):