Check whether your repo is ready for coding agents

01

Readiness is more than an instructions file

An AGENTS.md or CLAUDE.md helps, but it is not the whole question. A repo is agent-ready when an agent can understand the goal, find the right context, make a change, tell when it made a wrong turn, and leave enough trace for the next run to continue from real project context.

02

What the AI-readiness score covers

Guard turns 'can agents work here safely?' into a score with concrete reasons behind it. The same output becomes a practical AI readiness checklist your team can improve:

• Product context: what the system is for and what users need from it
• Technical context: architecture, boundaries, conventions, and load-bearing areas
• Operational context: how work moves from task to review to release
• Machine checks: a simple way for agents to know when they broke something
• Handoff memory: decisions, requirements, and rules that accumulate between sessions

03

Agents need feedback they can trust

Good agentic development has feedback. The agent should not have to guess whether a change is correct, and a human should not have to inspect every file to find out. Guard checks whether the repo gives agents a clear way to discover when they broke behavior, ignored a rule, missed a requirement, or drifted away from the product intent.

04

When agents have to guess, they drift

Agents copy what they can see. If the repo has three patterns for the same job, stale rules, or unclear ownership boundaries, the next AI change can make the drift worse. Guard surfaces the gaps that push agents toward guessing instead of following the system.

05

Context that agents can actually use

Good context is not a pile of documents. It is organized enough for an agent to find the relevant goal, requirement, rule, or verification path at the right moment. Guard checks whether the repo gives agents a map, or whether they drown in noise before the real task begins.

06

Agent docs, rules, and guardrails

Guard checks the files and practices that keep agentic development under control:

• AGENTS.md, CLAUDE.md, Cursor rules, and equivalent repo instructions
• Requirements that explain what done means and how to check it
• Guardrails that tell agents what not to break or bypass
• A repo structure agents can navigate without wasting context

07

The real test is the second agent run

A repo can look ready after one successful prompt. The harder question is whether another agent, or the same agent next week, can understand why the last change was made, which user behavior matters, and how to continue without re-learning the whole system from scratch.

08

Output: issues and PRs that improve readiness

Readiness gaps come back as concrete GitHub issues with rationale. When a fix is bounded and useful, Guard can open a pull request that adds missing instructions, tests, or structure for human review.