agentleFS
ElasticKnown publisherelastic/elastic-docs-skills/skills/review/docs-frontmatter-audit/SKILL.md

docs-frontmatter-audit

Skill72 starsChanged 5 months agoApache-2.0View on GitHub

Audit Elastic documentation files for frontmatter completeness and correctness. Checks products, description, and navigation_title fields across a directory. Use when the user asks to audit docs metadata, check frontmatter quality before publishing, or validate a batch of files, or when a docs review runs.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 4 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use these configuration defaults unless the user provides overrides.

    line 35
  2. Distinctive:

    Check each file for the following elements:

    line 44
  3. Very specific:

    No Jinja2 substitution variables ({{kib}}, {{es}}, {{esql}} — these aren't parsed in frontmatter)

    line 64
  4. Distinctive:

    No label prefixes ("Reference -", "Tutorial -", "Guide -")

    line 65
  5. Very specific:

    Check if the H1 title exceeds ~50 characters.

    line 71
  6. Distinctive:

    If present, don't flag or suggest changes.

    line 79

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. Elasticsearch B.V. licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. -->

You are a frontmatter auditor for Elastic documentation. Your job is to check all markdown files in a given scope for frontmatter completeness and correctness, then produce a structured report.

Inputs

$ARGUMENTS is a file path or directory to audit. If empty, ask the user what to audit.

Use these configuration defaults unless the user provides overrides. Ask for confirmation only when the target scope makes the required keys or products ambiguous:

SettingDefaultDescription
Required products(none)Which product IDs must appear (e.g., kibana)
Additional products allowedyesWhether extra product IDs beyond the required ones are acceptable

Required frontmatter elements

Check each file for the following elements:

1. products (mandatory)

Must include the configured required product IDs. May include additional products. In docs-content, the canonical frontmatter field is products, with id entries. If fetched contributor docs mention product singular, treat that as a source inconsistency and follow the canonical products shape used by docs-builder and current docs-content pages.

products:
  - id: kibana

Flag files missing this element or missing required products. Don't remove existing additional products. Flag product singular as likely incorrect unless the local repository explicitly uses that schema.

2. description (mandatory)

Validate against these rules:

  • Present and non-empty
  • Around 150 characters (recommended by docs-builder); flag anything over 200 characters as too long
  • Complete sentence (not a fragment or label)
  • No Jinja2 substitution variables ({{kib}}, {{es}}, {{esql}} — these aren't parsed in frontmatter)
  • No label prefixes ("Reference -", "Tutorial -", "Guide -")
  • Clear, user-facing summary of the page content
  • Quoted if it contains punctuation or characters that could be misread by YAML, including colons

3. navigation_title (recommended)

Check if the H1 title exceeds ~50 characters. If so, flag that a navigation_title should be added.

navigation_title: "Configure ML alerts"

4. mapped_pages (preserve)

If present, don't flag or suggest changes. If absent, don't suggest adding it.

Execution

  1. Glob for all .md files in the specified scope
  2. Read the frontmatter of each file
  3. Validate each element against the rules above
  4. Read the H1 title to check length for navigation_title
  5. Compile the report

Report format

## Frontmatter audit: <scope>

**Configuration:**
- Required products: kibana
- Files scanned: N

### Issues found

#### Missing `products`
| File | Issue |
|------|-------|
| path/to/file.md | Missing `kibana` product |

#### Invalid or missing `description`
| File | Issue |
|------|-------|
| path/to/file.md | Missing description |
| path/to/other.md | Contains Jinja2 variables |
| path/to/third.md | Exceeds 200 characters (247 chars); descriptions should usually be around 150 characters |

#### Missing `navigation_title`
| File | H1 length |
|------|-----------|
| path/to/file.md | 63 chars |

### Summary

- ✅ N files passed all checks
- ❌ N files have issues
  - N missing products
  - N invalid/missing description
  - N missing navigation_title (recommended)

Group issues by type, not by file, so users can batch-fix related problems. Only include sections that have issues.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.