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Repository Legibility Review for AI Coding Agents
Get a prioritized report of repository traps that could cause AI coding agents to make the wrong changes.
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Repository Legibility Review for AI Coding Agents
Example session with this skill installed
Give a compact agent-legibility review of this snapshot: README says tax lives in pricing.ts. pricing.ts exports TAX_RATE=0.2; checkout.ts uses subtotal*1.2 directly. No other files supplied.
- Read your context and instructions
- Compiled the repository legibility review
Reviewed the supplied snapshot for AI-agent edit risks. The main concern is a checkout calculation that appears to repeat the documented tax rule.
Review Summary
Scope: supplied README statement and two code excerpts only. Scores are provisional; consumers, tests, and additional guidance were not inspected.
| Dimension | Score / 5 | Snapshot evidence |
|---|---|---|
| Discoverability | 4 | README points to pricing.ts. |
| Authority visibility | 3 | Named owner exists, but checkout embeds a similar value. |
| Context locality | 3 | Understanding the tax change requires both excerpts. |
| Impact predictability | 2 | Editing TAX_RATE would not update the shown checkout expression. |
| Intent signaling | 3 | TAX_RATE is explicit; checkout's multiplier is not. |
| Hidden knowledge | 3 | The relationship between 0.2 and 1.2 must be inferred. |
Duplicate Concepts
| Priority | Location | Issue and likely mistake | Smallest improvement |
|---|---|---|---|
| P2 | pricing.ts; checkout.ts | If both values represent the same tax policy, an agent following README could update TAX_RATE while leaving checkout unchanged. | Confirm shared meaning, then have checkout use TAX_RATE and add a calculation test. |
The README is useful counter-evidence against missing ownership. It does not explain whether checkout intentionally uses a separate rate. This finding remains conditional on that relationship.
Next steps
- Inspect the complete checkout function and relevant tests.
- Confirm whether both values represent the same tax policy before changing code.
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About this skill
An AI coding agent can edit the wrong file or miss a business rule that lives elsewhere. This review identifies those traps and gives developers a prioritized list of practical improvements before handing over more coding work.
What it does
- Finds confusing edit paths: Flags places where an agent could struggle to locate the right code.
- Checks sources of truth: Identifies competing definitions and unclear responsibility for business rules.
- Exposes hidden dependencies: Highlights conventions and linked changes that are easy to miss.
- Delivers an actionable report: Includes scores, file references, likely mistakes, and recommended fixes.
- Challenges suspected problems: Checks existing guidance and tests before treating an issue as a finding.
How it works
- Provide access to your repository and request an agent-legibility review.
- Name any common changes you want the review to focus on.
- Receive an evidence-based report with priorities and small, targeted improvements.
- Request implementation separately if you want changes made.
Works with
Repositories across frameworks. Reviews source code, tests, README files, repository guidance, configuration, and generated-code notices.
Why use this skill
It helps you address ambiguity before an agent makes an avoidable mistake. Recommendations focus on clearer edit paths and visible rules, rather than cosmetic cleanup or preferred coding styles.
Use cases
- Prepare a repository for delegated coding tasks.
- Explain rules that new coding agents might miss.
- Prioritize documentation and navigation improvements.
Known limitations
This is not a bug, security, performance, or architecture audit. Large repositories may be sampled, with the review boundary stated.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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