Agent skill

Agentic Readiness

by CodeAlive-AI in CodeAlive-AI/ai-driven-development

Audit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode.

MITAuto-check passedAgent Workflows

Install Agentic Readiness

skills CLI
$ npx skills add CodeAlive-AI/ai-driven-development --skill agentic-readiness -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install CodeAlive-AI/ai-driven-development agentic-readiness --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/CodeAlive-AI/ai-driven-development.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/agentic-readiness .claude/skills/agentic-readiness && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agentic-readiness
GitHub stars
157
Token cost
~1.2k tokens
SKILL.md length
562 words
Files
8 (incl. scripts, references)
Skills in repo
22
Repo updated
First seen
Licence
MIT

At a glance

Audit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode.

  • Works in 2 steps: Read the repository's existing… → Run from the repository root
  • Reviewing AGENTS.md
  • SKILL.md covers Audit workflow, Report shape, Implementation workflow and Large and multi-repository…
  • Runs Python scripts from its folder; calls python

What it does

Agentic Readiness is an agent skill from CodeAlive-AI/ai-driven-development. Audit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode. Use when reviewing AGENTS.md or CLAUDE.md quality and discovery, instruction routing in monorepos or meta-repos, agent settings, MCP configuration, skills, subagents, context budgets, or repository organization for coding agents.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/best-practices.md` and `references/checklist.md`).

It sits in Agent Workflows, covering Agent instruction files, Monorepo tooling and Context engineering. It works with Model Context Protocol. The repository describes itself as: Practices, protocols, and skills for AI-driven software development. Skills and safety hooks for Claude Code, Codex, OpenCode, Cursor, Antigravity, and any agent supporting the… The licence is MIT.

When your agent uses it

  • Reviewing AGENTS.md
  • CLAUDE.md quality and discovery
  • Instruction routing in monorepos
  • MCP configuration

Example prompts

  • “/agentic-readiness”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. Read the repository's existing instruction chain before inspecting other files.
  2. Run from the repository root

What it can do on your machine

Read from SKILL.md and the folder at commit 25b7b1d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agentic Readiness loads about 1.2k tokens when it runs, and up to ~6.4k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 562 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from CodeAlive-AI/ai-driven-development at commit 25b7b1d, republished under its MIT licence (© CodeAlive-AI). 562 words, ~1,153 tokens.

Download SKILL.mdSave it as .claude/skills/agentic-readiness/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
agentic-readiness
description
Audit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode. Use when reviewing AGENTS.md or CLAUDE.md quality and discovery, instruction routing in monorepos or meta-repos, agent settings, MCP configuration, skills, subagents, context budgets, or repository organization for coding agents.

Agentic Readiness

Default to audit-only. Present findings and wait for approval unless the user explicitly asks to implement changes.

Audit workflow

  1. Read the repository's existing instruction chain before inspecting other files.
  2. Run from the repository root:
bash
python scripts/audit_repo.py --root .

Add --include-user-scope only when the user explicitly wants personal Codex, Claude Code, and OpenCode configuration included. Never inspect credential stores or print secret values.

  1. Inspect the JSON report and verify findings against the actual build files, scripts, and repository layout. The script detects structural risks; it cannot prove that documented commands or architecture are current.
  2. Read the references needed for the task:
    • instruction-files.md for AGENTS.md/CLAUDE.md ownership, discovery, routing, compatibility, and CodeAlive lessons learned.
    • rubric.md for scoring and priority definitions.
    • checklist.md for the full cross-agent audit.
    • best-practices.md for settings, workflows, context, and safety beyond instruction files.
  3. Report evidence before recommendations.
Verify required commands and hooks actually work

For required build/test/lint commands and hooks, confirm they execute the intended check in the current environment. A configuration entry, hook file, or successful commit alone is not proof: a missing runner such as lefthook can leave checks unexecuted. Use a safe local invocation or an existing test fixture; do not commit, push, deploy, or perform a destructive action merely to test a hook. For a blocking hook, verify that an allowed fixture passes and a violating fixture is rejected. Confirm test commands ran the intended tests rather than finding zero or skipping them. Report what ran and its result; label anything not exercised as not verified, distinguishing it from a confirmed failure. Consider existing CI coverage when assessing the impact of a local gap.

Report shape

Keep the report concise:

  • Executive summary: readiness, strongest area, main failure mode, first action.
  • Repository profile: scale, languages/frameworks, Git/worktree shape.
  • Instruction topology: canonical file, compatibility shim, nested routing, active-chain caveats, context-budget risks.
  • Agent surfaces: Codex/Codex App, Claude Code, and OpenCode settings, MCP, skills, and subagents actually present.
  • Issues: P0 through P3 with file paths and evidence.
  • Recommendations: concrete edits and verification commands.

Do not penalize a repository for omitting agent-specific configuration it does not need. Do flag a claimed cross-agent setup that one of the named agents cannot discover.

Show full SKILL.md (200 more words)Show less

Implementation workflow

When the user asks to apply changes:

  1. Confirm the requested scope from the conversation; do not ask again when it is already explicit.
  2. Preserve one source of truth. Prefer root AGENTS.md plus a regular CLAUDE.md containing @AGENTS.md when the same rules should serve all three agents.
  3. Put scoped rules near their target paths. Add routing indexes only where they prevent real discovery mistakes.
  4. Keep generated directories, dependencies, caches, secondary worktrees, and unrelated subtrees out of routing tables.
  5. Turn non-negotiable rules into hooks, linters, or CI checks; instruction files are guidance, not enforcement.
  6. Show the diff, rerun the audit and tests, then explain any remaining intentional gaps.

Large and multi-repository workspaces

For more than 3,000 tracked files, emphasize navigation, bounded routing, focused verification, and retrieval support rather than copying documentation into startup context.

For a directory containing multiple child Git repositories, treat each child as an independent instruction root. Codex builds its instruction chain once per run/session, so changing a command's working directory does not load the child repository's files. Recommend an explicit meta-repository routing rule and verify each child from a fresh session or by reading its chain before the first operation.

© CodeAlive-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references) in skills/agentic-readiness of CodeAlive-AI/ai-driven-development.

  • SKILL.md
  • agents/openai.yaml
  • references/best-practices.md
  • references/checklist.md
  • references/instruction-files.md
  • references/rubric.md
  • scripts/audit_repo.py
  • scripts/test_audit_repo.py

Open the folder on GitHubat commit 25b7b1d

Compare with similar skills

Agentic Readiness next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agentic Readiness compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agentic Readiness this skillCodeAlive-AI/ai-driven-development157—~1.2kAutomated safety check: PassMIT
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Claude Code Masteryborghei/Claude-Skills881—~1.9kAutomated safety check: PassMIT
Claude Docs Consultantcentminmod/my-claude-code-setup2.7k—~959Automated safety check: PassMIT
Cc Dev Agentsangrokjung/claude-forge850—~771Automated safety check: PassMIT
Dotagents Standardgetknit/knit131—~4.1kAutomated safety check: PassMIT

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Categories

Questions about Agentic Readiness

What does Agentic Readiness do?

Audit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode. Agentic Readiness is an agent skill from CodeAlive-AI/ai-driven-development. Audit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode.

When should I use Agentic Readiness?

Agentic Readiness fits situations like: reviewing AGENTS.md; CLAUDE.md quality and discovery; instruction routing in monorepos; MCP configuration.

How do I install Agentic Readiness in Claude Code?

Run `npx skills add CodeAlive-AI/ai-driven-development --skill agentic-readiness -a claude-code`. Or copy the skill folder (skills/agentic-readiness in CodeAlive-AI/ai-driven-development) into .claude/skills/agentic-readiness in your project. Claude Code loads it when a task matches its description.

How do I install Agentic Readiness in Codex?

Run `npx skills add CodeAlive-AI/ai-driven-development --skill agentic-readiness -a codex`. Or copy the skill folder (skills/agentic-readiness in CodeAlive-AI/ai-driven-development) into .agents/skills/agentic-readiness in your project. Codex loads it when a task matches its description.

Can I use Agentic Readiness in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CodeAlive-AI/ai-driven-development --skill agentic-readiness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agentic-readiness, .gemini/skills/agentic-readiness, .github/skills/agentic-readiness and .opencode/skills/agentic-readiness in your project.

What does Agentic Readiness need to run?

Going by SKILL.md and its folder, Agentic Readiness needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Agentic Readiness access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Agentic Readiness safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Agentic Readiness use?

Agentic Readiness is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agentic Readiness use?

About 1.2k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.2k tokens, read only when the agent opens those files.

What are the alternatives to Agentic Readiness?

Skills that share tags, products or a category with Agentic Readiness: Claude Code Mastery Squad (ohmyjahh/xquads-squads, 276 stars), Claude Code Mastery (borghei/Claude-Skills, 881 stars), Claude Docs Consultant (centminmod/my-claude-code-setup, 2.7k stars) and Cc Dev Agent (sangrokjung/claude-forge, 850 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agentic Readiness?

CodeAlive-AI (a GitHub organization) maintains it in CodeAlive-AI/ai-driven-development, which has 157 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 6, 2026.

Source: CodeAlive-AI/ai-driven-development on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.