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Agent skill

Review Agents Md

by dominik1001 in dominik1001/caldav-mcp

Reviews an AGENTS.md or CLAUDE.md file against best practices and reports concrete fixes.

MITAuto-check passedAgent Workflows

Install Review Agents Md

skills CLI
$ npx skills add dominik1001/caldav-mcp --skill review-agents-md -a claude-code

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

GitHub CLI
$ gh skill install dominik1001/caldav-mcp review-agents-md --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/dominik1001/caldav-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/review-agents-md .claude/skills/review-agents-md && 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
review-agents-md
GitHub stars
103
Token cost
~1.2k tokens
SKILL.md length
617 words
Files
1
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Reviews an AGENTS.md or CLAUDE.md file against best practices and reports concrete fixes.

  • Works in 4 steps: Read the target file (default:… → Evaluate against each rubric below. For… → Report findings grouped by severity: Cut… → …
  • The user asks to review
  • SKILL.md covers Workflow, Rubric and Output format
  • Calls make

What it does

Review Agents Md is an agent skill from dominik1001/caldav-mcp. Reviews an AGENTS.md or CLAUDE.md file against best practices and reports concrete fixes. Use when the user asks to review, audit, lint, or improve an AGENTS.md / CLAUDE.md / context file, or says "review my agents file".

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Agent instruction files and Linting and formatting. It works with Model Context Protocol and TypeScript. The repository describes itself as: 🗓️ A CalDAV Model Context Protocol (MCP) server to expose calendar operations as tools for AI assistants. The licence is MIT.

When your agent uses it

  • The user asks to review
  • Improve an AGENTS.md / CLAUDE.md / context file
  • Says review my agents file

Example prompts

  • “review my agents file”
  • “Use the review-agents-md skill to review an AGENTS.md or CLAUDE.md file against best practices and reports concrete fixes”
  • “/review-agents-md”

Workflow steps

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

  1. Read the target file (default: AGENTS.md, then CLAUDE.md at repo root). If both exist, review both.
  2. Evaluate against each rubric below. For every issue, quote the offending lines and propose a concrete rewrite — not just a critique.
  3. Report findings grouped by severity: Cut (delete), Rewrite (fix in place), Add (missing required content).
  4. End with a one-line verdict: total lines now vs. proposed, and whether the tech stack is mentioned.

What it can do on your machine

Read from SKILL.md and the folder at commit 725de72. 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

    Shell commands in SKILL.md call:

    • make

    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

Review Agents Md loads about 1.2k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 617 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from dominik1001/caldav-mcp at commit 725de72, republished under its MIT licence (© dominik1001). 617 words, ~1,228 tokens.

Download SKILL.mdSave it as .claude/skills/review-agents-md/SKILL.md (or your agent's skills folder).
name
review-agents-md
description
Reviews an AGENTS.md or CLAUDE.md file against best practices and reports concrete fixes. Use when the user asks to review, audit, lint, or improve an AGENTS.md / CLAUDE.md / context file, or says "review my agents file".

The meta-principle: a context file earns its tokens. Every line must tell the agent something it can't infer from the code, the formatter, or the linter. If a line could be deleted without the agent getting worse, delete it.

Workflow

  1. Read the target file (default: AGENTS.md, then CLAUDE.md at repo root). If both exist, review both.
  2. Evaluate against each rubric below. For every issue, quote the offending lines and propose a concrete rewrite — not just a critique.
  3. Report findings grouped by severity: Cut (delete), Rewrite (fix in place), Add (missing required content).
  4. End with a one-line verdict: total lines now vs. proposed, and whether the tech stack is mentioned.

Do not auto-edit the file unless the user asks. Surface the diff first.

Rubric

Length & signal density

Good: Short and load-bearing. Every line is non-obvious and would change agent behavior if removed. Bad: Long preambles, restated obvious facts ("we use TypeScript"), or generic engineering advice. Flag any file over ~200 lines as suspect and identify the lowest-signal sections to cut.

Non-obvious content only

Good: Conventions, architecture choices, tooling quirks ("we use bun, not node"; "migrations run via make db-migrate, not the ORM CLI"). Bad: Anything derivable from package.json, Cargo.toml, file extensions, or a five-second skim of the repo. Cut it.

Tech stack is mentioned

Good: The language/runtime/framework choices the agent would otherwise guess wrong are mentioned somewhere in the file (e.g., "Bun 1.x runtime, not Node"; "Postgres 16 + Drizzle, not Prisma"). A dedicated ## Tech Stack section is fine but not required — a one-liner near the top works too. Bad: No mention at all of the non-obvious stack choices, so the agent has to infer them from manifests. If missing, propose a short addition drafted from the repo's manifests.

Auto-generated content

Good: Hand-written, curated. Bad: Looks /init-generated — boilerplate headings, file-tree dumps, restatement of package.json scripts. Auto-generated context files measurably reduce success rates. Recommend deletion and replacement with a hand-written file.

Outdated docs

Good: Current. References match the code. Bad: Mentions removed files, renamed commands, deprecated workflows. The agent reads these anyway and gets misled. Flag specific stale references and recommend deletion from the repo, not just from the context file.

Show full SKILL.md (255 more words)Show less
Don't redocument the formatter / linter

Good: Silent on style — prettier, eslint, rustfmt, ruff enforce it. Bad: "Use 2-space indent", "prefer single quotes", "no unused imports". Cut. If a rule isn't enforced by tooling, recommend adding the rule to the tooling instead of to the context file.

Procedural workflows live elsewhere

Good: Recurring multi-step tasks (release, migration, deploy) live in slash commands or skills. AGENTS.md points to them by name. Bad: Numbered step-by-step procedures embedded in AGENTS.md itself. Recommend extracting each procedure into .claude/commands/<name>.md or a skill, and replacing the section with a one-line pointer.

Decision tables for genuine choices

Good: When 2–3 valid approaches exist, a small table with columns like Situation / Use / Why. Bad: Prose that lists options without telling the agent which to pick when. Convert to a table.

Pair every "don't" with a "do"

Good: "Don't add new endpoints to legacy/api.ts — add them to routes/v2/ and register in routes/index.ts." Bad: "Don't touch the legacy module." A bare prohibition makes the agent over-explore looking for the allowed path. Flag every unpaired "don't" / "never" / "avoid" and propose the missing "do".

Progressive disclosure

Good: The always-loaded root file is small. Path- or task-specific guidance lives in nested AGENTS.md files (e.g., services/billing/AGENTS.md), slash commands, or skills, surfaced only when relevant. Bad: One mega-file with sections that only apply to one subdirectory or one rare task. Identify those sections and recommend moving them to a nested file or a skill.

Output format

Structure the review as:

## Cut (N lines)
- L12–18: <quote>. Reason: <which rubric>. Replacement: <none / shorter line>.

## Rewrite
- L34: <quote>. Issue: bare "don't". Proposed: <do-form>.

## Add
- Tech stack not mentioned. Proposed addition (one-liner or section):
  <draft>

## Verdict
Before: 187 lines. After proposed edits: ~60 lines. Tech stack mentioned: no → added.

Be specific. Quote line numbers. Propose replacement text, not just labels.

© dominik1001, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/review-agents-md of dominik1001/caldav-mcp.

Open the folder on GitHubat commit 725de72

Compare with similar skills

Review Agents Md 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.

Review Agents Md compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Review Agents Md this skilldominik1001/caldav-mcp103—~1.2kAutomated safety check: PassMIT
Agnixagent-sh/agnix445—~874Automated safety check: PassApache-2.0
Clawmemyoloshii/ClawMem210—~7.5kAutomated safety check: PassMIT
Agnixagent-sh/agnix445—~563Automated safety check: PassApache-2.0
Bringupjenissimo/bottleship152—~2.9kAutomated safety check: PassApache-2.0
Zed Configwcygan/dotfiles194—~930Automated safety check: PassNone

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Works with

Categories

Questions about Review Agents Md

What does Review Agents Md do?

Reviews an AGENTS.md or CLAUDE.md file against best practices and reports concrete fixes. Review Agents Md is an agent skill from dominik1001/caldav-mcp.md file against best practices and reports concrete fixes.

When should I use Review Agents Md?

Review Agents Md fits situations like: the user asks to review; improve an AGENTS.md / CLAUDE.md / context file; says review my agents file.

How do I install Review Agents Md in Claude Code?

Run `npx skills add dominik1001/caldav-mcp --skill review-agents-md -a claude-code`. Or copy the skill folder (.agents/skills/review-agents-md in dominik1001/caldav-mcp) into .claude/skills/review-agents-md in your project. Claude Code loads it when a task matches its description.

How do I install Review Agents Md in Codex?

Run `npx skills add dominik1001/caldav-mcp --skill review-agents-md -a codex`. Or copy the skill folder (.agents/skills/review-agents-md in dominik1001/caldav-mcp) into .agents/skills/review-agents-md in your project. Codex loads it when a task matches its description.

Can I use Review Agents Md 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 dominik1001/caldav-mcp --skill review-agents-md -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-agents-md, .gemini/skills/review-agents-md, .github/skills/review-agents-md and .opencode/skills/review-agents-md in your project.

What does Review Agents Md need to run?

Going by SKILL.md and its folder, Review Agents Md needs the command-line tools its instructions call (make).

Does Review Agents Md 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 Review Agents Md 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. Review the folder before installing.

What licence does Review Agents Md use?

Review Agents Md 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 Review Agents Md use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Review Agents Md?

Skills that share tags, products or a category with Review Agents Md: Agnix (agent-sh/agnix, 445 stars), Clawmem (yoloshii/ClawMem, 210 stars), Agnix (agent-sh/agnix, 445 stars) and Bringup (jenissimo/bottleship, 152 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Agents Md?

dominik1001 (a GitHub user) maintains it in dominik1001/caldav-mcp, which has 103 GitHub stars. The repository was last updated on October 5, 2026.

Source: dominik1001/caldav-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.