.agents/skills/legibility--enhancer/SKILL.md
Collaboratively walks a human through creating high-quality AGENTS.md files throughout a codebase, implementing progressive disclosure architecture. Use when creating or updating AGENTS.md files, onboarding a repository to agent-first practices, or remediating findings from legibility--auditor. Do not use when evaluating existing documentation coverage (use legibility--auditor) or when creating agent skills (use meta--skill-creator).
npx skillsauth add patterninc/code-mint legibility--enhancerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Walk through the process of creating high-quality AGENTS.md files with a human collaborator. AI-generated AGENTS.md files created without human input miss implicit assumptions and UX intent — the most valuable parts. This skill ensures those assumptions become explicit.
If a legibility audit report exists at .agents/reports/legibility--auditor-audit.md, read it first and prioritize directories flagged as missing AGENTS.md files. If no report exists, begin with Step 1.
Use a workshop pattern, not a questionnaire dump.
docs/framework.md: never ask a question if the answer can be reasonably inferred from repository structure, standard tooling, or existing docs.If the working scope is not the git repository root (monorepo or package-only onboarding), read the repository root README.md and any README.md files on the path from the repo root to the scope before drafting. Use them to capture repo-wide deploy, release, CI, and environment workflows that apply to this package. Fold relevant commands into the scoped root AGENTS.md, or add explicit references (for example: "Deploy: see repository root README.md, section …") so an agent working only in the scope still has an actionable path.
Before writing anything, inspect the repository and draft your best provisional answers for:
Then present that draft to the human and ask for corrections, not just raw restatement. Example:
Here is my draft read of the repo: [summary]. I still need your help with the parts the code cannot tell me confidently, especially UX intent, hidden constraints, and which related repositories actually matter in day-to-day work. What is inaccurate or missing?
After that draft review, work with the human to answer any unresolved questions:
What is this repository's primary purpose?
What is the tech stack (languages, frameworks, databases, infrastructure)?
What are the exact commands to build, test, lint, and run the project?
What are the major modules/directories and what does each do?
Are there any project-wide conventions (naming, file organization, dependency direction)?
Are there companion repositories the agent needs to know about? Especially:
{repo-name}-tf for Terraform)Proactive discovery: If a VCS host CLI is available (e.g., gh for GitHub, glab for GitLab), search for companion repos automatically. GitHub example:
# Detect the current repo's GitHub org and name
REPO_SLUG=$(gh repo view --json nameWithOwner -q '.nameWithOwner')
ORG=$(echo "$REPO_SLUG" | cut -d/ -f1)
REPO_NAME=$(echo "$REPO_SLUG" | cut -d/ -f2)
# Search for IaC and companion repos by naming convention
gh repo list "$ORG" --limit 100 --json name,url \
--jq ".[] | select(.name | test(\"${REPO_NAME}\")) | \"\(.name) \(.url)\""
Present any matches to the user and ask which are relevant.
Follow the template in references/agents-md-guide.md. Include:
Before finalizing the file, show the human a concise draft of:
Ask the human what should be corrected, trimmed, or moved out of the root file. Favor concise, high-signal output over exhaustive inventory.
Use this standard decision rubric:
AGENTS.md when the directory has two or more of these signals:
This is the hardest and most valuable part. Ask the human collaborator:
Encourage narrative answers and concrete examples. If the human is unsure, ask for one real incident, one failure mode, or one "easy way to break this module" story instead of pushing for abstract wording.
Document the answers directly in the subdirectory AGENTS.md under a "UX Intent" heading, but first compress them into a short draft summary and confirm it with the human.
After drafting a subdirectory file, ask:
Here is the 5-line version I would give to a new engineer or agent working in this module. What is wrong, missing, or too generic?
Revise until the summary reflects real module behavior rather than template filler.
Subdirectory AGENTS.md files override parent files — they do not merge. An agent working in a subdirectory will only see the nearest AGENTS.md file. This means:
Authoring vs runtime: When creating or updating scoped AGENTS.md files, use parent and repository-root README files to populate scoped content (commands, links, short summaries). At runtime, the nearest AGENTS.md still wins; the authoring step is how you bring parent README facts into scope so the scoped file stays self-contained.
.agents/reports/completed/legibility--auditor-audit-{YYYY-MM-DD}.md.docs/onboarding-checklist.md and .agents/code-mint-status.json with the current navigate outcome status and date. Optionally update docs/skills-status.md if the repository keeps the compatibility view.See references/agents-md-guide.md for root and subdirectory AGENTS.md templates with examples.
development
Best practices and template for creating new agent skills in the code-mint framework. Use when creating a new skill, authoring SKILL.md files, or structuring skill directories. Do not use when editing an existing skill's logic (edit directly instead) or when creating AGENTS.md files (use legibility--enhancer).
development
Step-by-step playbook that transforms a repository for AI-first development. It scopes the repository, runs read-only audits, maintains an outcome-driven checklist, guides collaborative improvements, and verifies the results with evidence. Use when onboarding a new repository, when a user says "set up this repo for agents," or when starting a harness engineering transformation. Do not use when the repo is already onboarded and the goal is to run a single specific skill.
development
Audits a repository's documentation coverage and agent-readiness by evaluating AGENTS.md placement, progressive disclosure quality, and UX intent documentation. Use when evaluating repository structure, auditing documentation coverage, assessing agent-readiness, or onboarding a codebase to agent-first practices. Do not use when creating or editing AGENTS.md files directly (use legibility--enhancer instead).
development
Collaborates with a product owner, TPM, or engineer to refine vague requests into high-quality work tickets optimized for agent one-shot execution. Use when writing tickets, refining requirements, reviewing feature requests, or when a stakeholder submits a new task. Do not use when debugging an existing issue (use autonomy--sre-agent) or when auditing codebase readiness (use legibility--auditor).