world-model-mcp

query_fact

Query a knowledge graph to retrieve facts, rules, or procedures about code entities like APIs, functions, and classes, with optional filters for entity and content type.

Instructions

Query the knowledge graph for facts about entities (APIs, functions, classes, etc.)

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": {
      "query": "<query>"
    },
    "name": "query_fact"
  }
}

Input Schema

Name	Required	Description
`query`	Yes	The search query (e.g., 'User.findByEmail', 'JWT authentication')
`context`	No	Additional context for the query
`entity_type`	No	Optional filter by entity type
`content_type`	No	Optional filter by content_type. Use 'procedure' to explicitly summon procedures (which are excluded from auto-injection by design).

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.12.0Jul 6, 2026

addedInput schema / properties / content_type

Added value: +{
+  "description": "Optional filter by content_type. Use 'procedure' to explicitly summon procedures (which are excluded from auto-injection by design).",
+  "enum": [
+    "rule",
+    "fact",
+    "procedure"
+  ],
+  "type": "string"
+}

First observedv0.7.3May 27, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It doesn't state whether the tool is read-only, what the response format is, or that it can retrieve 'rules' and 'procedures' despite being named 'facts'. The term 'facts' may mislead users into thinking only fact-type content is returned, leaving important behavior undisclosed.

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, well-structured sentence that is front-loaded with the action and resource. Every word contributes to the core purpose without fluff or repetition. It is appropriately concise.

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?

For a general-purpose query tool with no output schema and no annotations, the description is minimal but adequate. It does not explain return values, pagination, or how to decide between this and related sibling tools. The ambiguous scope of 'facts' (vs rules/procedures) is a notable gap, but the schema partially covers this via content_type descriptions.

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?

Input schema coverage is 100% with descriptive text for all parameters, so the baseline is 3. The tool description adds no parameter-level meaning beyond what the schema already provides; it only reiterates the general entity focus. The description does not compensate or enhance the schema's parameter docs.

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 uses a clear verb ('Query') and resource ('knowledge graph') and specifies the object ('facts about entities'). It lists example entity types (APIs, functions, classes) which conveys scope. However, it doesn't distinguish itself from sibling tools like search_global that might also search the knowledge graph, so it lacks explicit differentiation.

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

Usage Guidelines2/5

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

There is no guidance in the description about when to use this tool versus alternatives. The only usage hint ('Use "procedure" to explicitly summon procedures...') appears in the schema's content_type parameter, not the tool description, and it is parameter-level rather than tool-level. No when-not-to-use or alternative tool references are provided.

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