Query Docs Library Metadata

OrganizationPopular

TanStack

query-docs-library-metadata

Retrieve machine-readable context with tanstack libraries, tanstack doc, tanstack search-docs, tanstack create --list-add-ons --json, and --addon-details for agent-safe discovery and preflight validation.

Overview

Publisher	TanStack
Repository	`cli`
Skill name	`query-docs-library-metadata`
Stars	1.3K
Forks	184
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

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 TanStack on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/TanStack/cli/tree/main/packages/cli/skills/query-docs-library-metadata

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/TanStack/cli.git /tmp/cli
mkdir -p .claude/skills
cp -r /tmp/cli/packages/cli/skills/query-docs-library-metadata .claude/skills/query-docs-library-metadata

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Query Docs Library Metadata 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 Query Docs Library Metadata 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 Query Docs Library Metadata 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.

Query Docs And Library Metadata

Use this skill to collect authoritative context before code generation or integration selection.

Setup

bash
npx @tanstack/cli libraries --json

Core Patterns

Resolve valid library ids before doc fetch

bash
npx @tanstack/cli libraries --json

Fetch a specific docs page with explicit version

bash
# Syntax: tanstack doc <library-id> <path> [--docs-version <version>]
npx @tanstack/cli doc router framework/react/guide/routing
npx @tanstack/cli doc router framework/react/guide/routing --docs-version latest

Search docs for implementation targets

bash
npx @tanstack/cli search-docs "server functions" --library start --json

Common Mistakes

HIGH Use invalid library id/version/path for doc fetch

Wrong:

bash
# Wrong: --library and --version are not flags on doc; path must not include /docs/ prefix
npx @tanstack/cli doc --library router --version latest --path /docs/framework/react/guide/routing

Correct:

bash
# Step 1: resolve a valid library id
npx @tanstack/cli libraries --json
# Step 2: fetch using positional args — library id then doc path (no /docs/ prefix)
npx @tanstack/cli doc router framework/react/guide/routing

doc takes <library> and <path> as positional arguments (not flags), and the path must not include a leading /docs/ segment. Use --docs-version (not --version) to pin a specific version.

Source: packages/cli/src/cli.ts:746

MEDIUM Rely on deprecated create alias for discovery

Wrong:

bash
npx create-tsrouter-app --list-add-ons

Correct:

bash
npx @tanstack/cli create --list-add-ons --json

Legacy alias workflows can produce confusing outputs that do not match current CLI discovery behavior. Fixed in newer versions, but agents trained on older examples may still generate this pattern.

Source: https://github.com/TanStack/cli/issues/93

HIGH Tension: Single-command convenience vs integration precision

This domain's patterns conflict with create-app-scaffold and choose-ecosystem-integrations. Skipping discovery to run one-shot scaffold commands tends to lock in plausible defaults that miss architecture constraints.

See also: create-app-scaffold/SKILL.md § Common Mistakes

References

Discovery command output schemas

Bundled files

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

references/discovery-command-output-schemas.md3 KB

Frequently asked questions

What does the Query Docs Library Metadata AI skill do?

Why use Query Docs Library Metadata on TypingMind?

Because you install it once and use it with any model. Query Docs Library Metadata 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 Query Docs Library Metadata in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TanStack/cli/tree/main/packages/cli/skills/query-docs-library-metadata. 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 Query Docs Library Metadata?

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 Query Docs Library Metadata?

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

Is the Query Docs Library Metadata AI skill free?

Yes. It is published on GitHub by TanStack under the MIT 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Query Docs And Library Metadata

Setup

Core Patterns

Resolve valid library ids before doc fetch

Fetch a specific docs page with explicit version

Search docs for implementation targets

Common Mistakes

HIGH Use invalid library id/version/path for doc fetch

MEDIUM Rely on deprecated create alias for discovery

HIGH Tension: Single-command convenience vs integration precision

References

Bundled files

Frequently asked questions

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