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pracht docs

Read a pracht docs page

docs_read
Read-onlyIdempotent

Return one page of the pracht documentation as Markdown, or only one section of it. page accepts a path (/docs/capabilities), a slug (capabilities, recipes/auth), or a page URL. A whole-page read lists the page's anchors in sections. An unknown page or section answers found: false with the closest matches.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "page": "<page>"
    },
    "name": "docs_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageYesPage path, slug, or URL, e.g. /docs/capabilities.
sectionNoHeading anchor from docs_search or `sections`, e.g. remote-mcp-tools-for-agents-without-a-browser. Empty or omitted reads the whole page.

Output Schema

NameRequiredDescriptionDefault
urlYes
pageYes
foundYes
titleYes
messageYes
sectionYes
markdownYes
sectionsYes
truncatedYes
suggestionsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent, non-destructive behaviour, so the description's job is lighter. It still adds real value by disclosing whole-page reads list anchors in `sections` and that unknown pages or sections return found: false with closest matches – error semantics an agent would otherwise have to discover by failing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the return type, then input forms, then failure behaviour. No filler or repetition of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described, and the description still covers the key edge cases: section vs whole page, anchor discovery, and not-found fallback. The main omission is guidance on selecting this tool against its siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already documents both `page` forms and `section` empty/omitted behaviour. The description restates those accepted formats with a couple of examples (slug like recipes/auth) but adds no new constraints or formats beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Return one page of the pracht documentation as Markdown, or only one section of it") and scopes it to single-page retrieval, which separates it from a listing or search tool. Sibling differentiation is implied by the reference to docs_search as the anchor source rather than stated outright.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the workflow (get anchors from docs_search or `sections`, then read one section) but never says when to pick this tool over docs_search or docs_list. Usage is inferable from the input semantics rather than spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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