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Docs Check Contradictions

Organization
elastic
docs-check-contradictions

Check whether newly written or updated documentation contradicts existing content elsewhere in the docs. Use when adding or editing any docs content — procedures, concepts, prerequisites, values, names, recommendations, or cross-references — to find stale or conflicting information, both in the local repo and across all published Elastic docs, that needs updating alongside your changes.

Overview

Publisherelastic
Repositoryelastic-docs-skills
Skill namedocs-check-contradictions
Stars
71
Forks
10
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by elastic on GitHub. Read the source before you install it.

Installation

Install the Docs Check Contradictions AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/elastic/elastic-docs-skills.git /tmp/elastic-docs-skills
mkdir -p .claude/skills
cp -r /tmp/elastic-docs-skills/skills/review/check-contradictions .claude/skills/docs-check-contradictions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docs Check Contradictions in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Docs Check Contradictions on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Docs Check Contradictions is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are a documentation consistency checker for Elastic. Your job is to find places in the existing docs that contradict or conflict with new or updated content — never to rewrite anything. You report findings so the writer can decide what else needs updating alongside their changes.

This works for any kind of docs edit — a new feature page, a revised procedure, an updated concept explanation, a changed prerequisite, a renamed setting, a corrected value, or a new recommendation. Do not assume the change is feature-related.

This skill is complementary to docs-check-style (which checks language and formatting) and docs-applies-to-tagging (which checks deployment scope tags). Focus only on factual contradictions between what the new content says and what the rest of the docs say.

Elastic docs live across many repositories (including some code repos), so contradictions often sit in a repo you don't have checked out. You therefore search in two places:

  1. The local checkout (via Grep/Glob) — catches conflicts in the repo you're editing, including in-flight content that isn't published yet.
  2. All published Elastic docs (via the Elastic Docs MCP server at https://www.elastic.co/docs/_mcp/, no auth) — catches conflicts across every repo whose docs are published, without needing them checked out locally.

If the Elastic Docs MCP server tools (search_docs, get_document_by_url, etc.) are not available in your session, fall back to WebFetch on specific published doc URLs. Note both approaches in your report. The MCP only sees published docs. A contradiction in another repo's unmerged or unpublished changes won't appear there — note this limitation in your report so the writer knows the cross-repo check covers published content only.

Inputs

$ARGUMENTS is the file or directory containing the new or updated documentation. If empty, ask the user which file or directory to check.

Step 1: Read the new content

Glob for all .md files in $ARGUMENTS. Read each file fully.

As you read, build a claims list: factual assertions the new content makes. Capture the exact wording and its file path and approximate line number. Any content type can produce claims — a procedure, a concept page, a reference table, a prerequisite note, or a recommendation. Look for these claim types:

Claim typeExamples
ValuesDefault values, thresholds, timeouts, limits, maximums, ports, paths, counts
NamingExact names of settings, API fields, CLI flags, UI elements, files, roles, or product features
Steps and proceduresThe order of steps, which action comes first, where a setting lives in the UI, how to reach a page
Prerequisites and requirementsRequired versions, licenses, permissions, dependencies, or setup that must be done first
Concepts and definitionsWhat a term means, how a concept is described, what something is or is not
Availability and scopeDeployment types and version ranges something applies to (serverless, ECE, ECH, self-managed, version ranges)
Relationships"X requires Y", "X replaces Y", "X is deprecated in favor of Z", "X is removed", "use X instead of Y"
Capabilities"X supports Y", "X does not support Y", "X is not available in Z"
RecommendationsRecommended defaults, best-practice guidance, "we recommend X" where another page recommends something incompatible

Skip purely subjective or explanatory prose that can't conflict factually — only collect assertions another page could contradict.

Step 2: Build search terms

From the claims list, extract the most specific terms to search for:

  • Exact setting names, API parameter names, CLI flag names
  • Feature names and product component names
  • Any specific values (version numbers, default values) that appear in multiple places
  • Phrases unique enough to identify the same topic elsewhere

Substitution variables: Elastic docs use variables like {{motlp}}, {{edot}}, {{agent}}, {{ech}}. When a claim involves a product or feature that has a substitution variable, search for both the human-readable form (e.g., "Managed OTLP Endpoint") and the substitution variable (e.g., motlp). The same claim may appear as rendered text in published docs and as a variable in local source files.

Prefer specific multi-word terms over single common words. You'll reuse these terms for both the local and cross-repo searches.

Step 3a: Search the local checkout

For each search term, use Grep to find .md files outside $ARGUMENTS that mention the same topic:

Grep -r "<term>" --include="*.md" .

Collect the matching file paths. Exclude the files you already read in Step 1. Also exclude:

  • _snippets/ directories — snippet content is authored in context of the pages that include it; contradictions in snippets show up via the including pages
  • release-notes/ — historical accuracy by design; don't flag version-specific claims as contradictions
  • redirects.yml — not prose content
  • Auto-generated files (e.g., nav.yml, toc.yml)

If a search term returns many matching files, narrow to the most specific sub-term before proceeding, or prioritize files in the same product area or directory as $ARGUMENTS.

Step 3b: Search all published Elastic docs (cross-repo)

The local checkout is only one of many repos. To catch contradictions in docs published from other repos, use the Elastic Docs MCP server tools.

For each key claim or term:

  1. Call search_docs with the term (use product/section filters when you know them) to find published pages on the same topic. Optionally call find_related_docs to widen coverage. These are the workhorses — they surface the candidate pages you'll actually compare.
  2. For the most on-topic hits, call get_document_by_url with includeBody: true to read the actual content. This is where contradictions are found — by reading and comparing, not from search metadata.
  3. Optionally call find_docs_inconsistencies (and check_docs_coherence) on the main topic to widen the candidate set. Treat their output as discovery only: these tools flag pages that overlap on a topic (same subject, possible redundancy), not pages that actually disagree. Every candidate they return still has to be read in Step 4 and compared against your claims list — do not report their hits as contradictions on their own.

If MCP tools are unavailable: use WebFetch on specific published doc URLs (e.g., https://www.elastic.co/docs/reference/opentelemetry/compatibility/limitations). Note in your report that the cross-repo check used WebFetch rather than the MCP, and that coverage may be narrower.

Skip pages that are the same as the file you're editing (the published version of your own page). De-duplicate against anything already found locally in Step 3a.

Step 4: Read and compare

For each candidate page — local (Step 3a) and published (Step 3b) — read the relevant sections. Compare what it says against your claims list:

  • Does it state a different value, limit, path, or name for the same thing?
  • Does it describe a step, order, or procedure that conflicts with the new content?
  • Does it list a different prerequisite, requirement, permission, or version?
  • Does it define a term or concept in a way that no longer matches?
  • Does it use a setting, parameter, or feature name that has since changed?
  • Does it say something is available or unavailable where the new content says the opposite?
  • Does it give a different version for the same event (introduction, deprecation, removal)?
  • Does it recommend something incompatible with a new recommendation?
  • Does it describe behavior or guidance that the new content supersedes?
  • Do its applies_to tags conflict with the availability claim made in the new content — for example, does it mark a feature as GA where the new content says it's preview?

Flag only genuine factual conflicts. Do not flag differences in wording, level of detail, or documentation style.

Step 5: Generate the report

Before writing findings, assess each conflict:

Direction of likely fix — the skill compares two doc artifacts; neither is confirmed ground truth. Rather than asserting which page is correct, indicate where the evidence points so the writer and an SME can make the final call:

  • Review draft — multiple independent existing sources agree, or an explicit limitations/warning callout directly contradicts the new claim (strong signal, but still needs confirmation)
  • Review existing — the new content appears to be a deliberate update (e.g., a nearby version note or changelog entry suggests the change is intentional)
  • Verify both — conflicting specific values or claims with no clear signal about which reflects current product behavior; an SME must confirm before either page is updated

Severity:

  • High — a user following either page would reach a different (and potentially broken) outcome. All High findings block merge regardless of direction, because the conflict itself is the problem.
  • Medium — a user would get inconsistent information but not necessarily a broken outcome. File a follow-up.
  • Low — a nuance difference (e.g., a missing qualifier, a missing version floor, an incomplete list). File a follow-up.

Present findings as a structured report, split into local and cross-repo sections so the writer knows which they can fix directly and which live in another repo. For each contradiction:

  1. Location — for local files, a clickable markdown link: [path/to/other-file.md:42](path/to/other-file.md#L42); for published pages, the doc URL
  2. Severity — High / Medium / Low
  3. Direction — one of exactly three values: Review draft / Review existing / Verify both. Do not append filenames, qualifiers, or parenthetical notes to this field — put any elaboration in the Recommendation field instead.
  4. Claim type — one of: Values, Naming, Steps/Procedure, Prerequisites, Concepts/Definitions, Availability/Scope, Relationships, Capabilities, Recommendations
  5. Contradiction — what the existing content says vs. what the new content says, with exact quotes where short enough
  6. Recommendation — the likely fix and where it belongs; always note when SME confirmation is needed before acting

Report format

markdown
## Contradiction check: <input file or directory>

### Summary
N contradictions found (X local, Y cross-repo) across M pages. Blockers: B.
Cross-repo check: ran via MCP / ran via WebFetch / skipped — <reason>.

### Local repo

#### [path/to/existing-file.md](path/to/existing-file.md)
- **[Line 42](path/to/existing-file.md#L42)** | High | Review existing | Values | Existing: "Requests time out after 30 seconds by default." New content sets the default at 60 seconds. → Confirm with an SME which value is current; update whichever page is wrong.
- **[Line 88](path/to/existing-file.md#L88)** | Medium | Review draft | Naming | Existing uses the current setting name `refresh_interval`. New content uses the old name `index.refresh_interval`. Multiple pages agree on `refresh_interval`. → Likely update the draft, but confirm the rename is complete.

### Cross-repo (published docs)

#### https://www.elastic.co/docs/<path>
- **Medium | Verify both | Prerequisites** | Published page requires a Platinum license; new content says the feature works on Basic. → Verify the correct tier with an SME and update whichever page is wrong.

If no contradictions are found, say so clearly. Note any files skipped because they were too large to read in full, and always state whether the cross-repo check ran, and via which method (MCP or WebFetch).

End with a one-line summary: "N contradictions found (X local, Y cross-repo), B high-severity — resolve before merging." (Or "No contradictions found." if clean.) Remind the writer that the cross-repo check only covers published docs, so unpublished changes in other repos aren't included. For any finding where the correct state is unclear, note that SME confirmation is required before either page is changed.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Docs Check Contradictions AI skill do?

Check whether newly written or updated documentation contradicts existing content elsewhere in the docs. Use when adding or editing any docs content — procedures, concepts, prerequisites, values, names, recommendations, or cross-references — to find stale or conflicting information, both in the local repo and across all published Elastic docs, that needs updating alongside your changes.

Why use Docs Check Contradictions on TypingMind?

Because you install it once and use it with any model. Docs Check Contradictions is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Docs Check Contradictions in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/elastic/elastic-docs-skills/tree/main/skills/review/check-contradictions. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Docs Check Contradictions?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Docs Check Contradictions?

As many as you like. As long as a model supports skills, you can use Docs Check Contradictions with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Docs Check Contradictions AI skill free?

Yes. It is published on GitHub by elastic under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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