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okf-mcp

by mfdaves
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JavaScript
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list_concepts

Read-onlyIdempotent

Retrieve compact OKF concept summaries filtered by bundle, type, tag, or text query to find relevant knowledge entries.

Instructions

List compact OKF concept summaries with optional bundle, type, tag, and text filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoLimit results to concepts containing this tag.
typeNoLimit results to this exact concept type.
limitNoMaximum number of concepts to return.
queryNoOptional all-term text query matched against concept metadata and content; maximum 16 terms.
bundleNoLimit results to this bundle id.
detailNoCompact returns only URI, title, type, and description; full includes navigation metadata and signals.compact
offsetNoNumber of matching concepts to skip before returning results.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.9.1
    • addedInput schema / properties / detail
      Added value: +{
+  "default": "compact",
+  "description": "Compact returns only URI, title, type, and description; full includes navigation metadata and signals.",
+  "enum": [
+    "compact",
+    "full"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / query / description
      Previous value: -"Optional text matched against concept metadata and content."New value: +"Optional all-term text query matched against concept metadata and content; maximum 16 terms."
    • addedInput schema / properties / query / maxLength
      Added value: +512
  2. First observedv0.3.3

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds minimal behavioral context beyond what annotations provide, such as the fact that results are compact summaries, but it does not disclose pagination behavior or any edge cases. Given the baseline from annotations, a 3 is appropriate.

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 a single, tightly written sentence with no filler words. It front-loads the core purpose and then lists the optional filters, achieving maximum clarity with minimal text.

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

Completeness3/5

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

The description is adequate for a list tool with fully documented schemas and annotations, but it does not state pagination behavior, sorting, or any error cases. Given the 7 parameters and absence of an output schema, a slightly richer description could help, but the current one is sufficient for an agent familiar with the schema. A 3 reflects this balance.

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%, so all 7 parameters are already documented in the schema. The description only summarizes these filters without adding new semantics or syntax details. Since the schema handles the heavy lifting, the description adds no significant value beyond what is structured, aligning with the baseline of 3.

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?

The description states a specific action (List) and resource (OKF concept summaries) and mentions the available filters. It is clear and distinct, though it does not explicitly differentiate from siblings like search_concepts or get_concept, but the purpose is self-evident.

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 through the filters (bundle, type, tag, text), but it does not explicitly state when to use this tool versus alternatives such as search_concepts or get_concept. There is no mention of exclusions or preferred conditions, leaving the agent to infer usage from the filter list.

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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