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get_page

Fetch a single wiki page from the key's workspace.

Args: category: One of entities | concepts | people | decisions | sources | flows | infrastructure | tickets. name: Page slug (without .md extension), as returned by list_pages / search_wiki.

Returns {category, name, content}content is the full markdown body including YAML frontmatter. Returns {error: "..."} if the page doesn't exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
categoryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden, and it discharges it by documenting the exact return shape ({category, name, content}), the content format (full markdown including YAML frontmatter), and the error behavior for missing pages. It does not explicitly state that this is read-only, but 'Fetch' plus return semantics make that a reasonable inference.

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?

The description is compact, front-loaded with the operation, then organized into Args and Returns sections. Every sentence contributes necessary information, with no filler or repetition of the schema.

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

Completeness5/5

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

For a two-argument fetch operation with no annotations, the description covers purpose, parameter values, input requirements, output format, and error behavior. The only absent context (e.g., permissions or rate limits) is not material for this tool's complexity.

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

Parameters5/5

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

Schema coverage is 0%, but the description fully compensates: category is given an explicit enum list and name is defined as a page slug without .md extension and provenance. The parameter meanings are clearer here than they would be in most machine-readable schemas.

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

Purpose5/5

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

The description opens with a specific verb and object: 'Fetch a single wiki page from the key's workspace.' It clearly signals a single-item retrieve operation, distinguishing it from list/search/query siblings. The category and name arguments and return context make the purpose unambiguous.

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

Usage Guidelines4/5

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

The description implies the correct usage context by requiring a name 'as returned by list_pages / search_wiki', which tells an agent what must happen before calling get_page. It does not explicitly enumerate when to choose this tool over the siblings or when not to use it, so it stops short of full exclusion guidance.

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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