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okf-mcp

okf-mcp

by teomarcdhio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_concept

Retrieve a concept document's full content and metadata by ID to access structured knowledge from an OKF bundle.

Instructions

Retrieve a full concept document by its ID.

Returns the concept's frontmatter metadata and its markdown body.

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": {
      "concept_id": "<concept_id>"
    },
    "name": "get_concept"
  }
}

Input Schema

NameRequiredDescriptionDefault
concept_idYesPath relative to bundle root, without the .md extension. Examples: "tables/orders", "memory/my_note", "metrics/wau"

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It does disclose the return behavior: 'Returns the concept's frontmatter metadata and its markdown body,' giving the agent a clear expectation of the response format. However, it does not address what happens if the ID is invalid or not found, which is a minor gap.

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 two succinct sentences. The first sentence states the core action, and the second provides valuable detail about the return payload. No filler or redundant information is present.

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 simple get-by-ID tool with a single fully documented parameter and an output schema present, the description is complete. It covers the purpose and the nature of the returned content, while the schema handles parameter details and the output schema covers return structure. No additional context is needed.

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 description coverage is 100%, with the concept_id parameter already documented as a path relative to bundle root with examples. The tool description adds no additional parameter semantics, so per the baseline for high coverage, a score of 3 is appropriate.

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 clearly states the action: 'Retrieve a full concept document by its ID.' It identifies the specific resource (concept document) and method (by ID), which differentiates it from siblings like search_concepts and list_concepts. This is a specific verb+resource pair with no ambiguity.

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 usage when you have a concept ID ('by its ID'), but it does not explicitly say when to use this tool versus alternatives like search_concepts or list_concepts. There are no explicit exclusions or mentions of alternative tools for different scenarios, leaving usage guidance to be inferred.

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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