Knowledge Master

Overview Schema Source Related Servers Discussions Admin

search

Find relevant information from a knowledge base using natural language queries. Returns content chunks with source and graph context including author, repo, and related documents.

Instructions

Semantic search across the knowledge base. Returns relevant chunks with source info and graph context (author, repo, related docs).

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": "search"
  }
}

Input Schema

Name	Required	Description
`query`	Yes	Natural language search query
`top_k`	No	Number of results
`source_type`	No	Filter by source type
`use_graph`	No	Include graph context (author, repo relationships)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 18, 2026

TDQS

A3.5/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It mentions that results include 'graph context' and source info, but does not disclose whether the tool is read-only, has rate limits, or requires authentication. The behavior is implied as safe but not explicit.

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

Conciseness4/5

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

The description is concise with one sentence explaining the tool and a second sentence on output. It avoids redundancy and front-loads the core purpose efficiently.

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?

For a search tool with no output schema, the description adequately explains the return type: 'relevant chunks with source info and graph context'. It covers the essential behavioral context for a primarily read-like operation.

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%, so the description need not add much. However, it adds context about 'semantic' search but does not elaborate on parameters like 'query' format, 'top_k' behavior, or 'source_type' filtering. The baseline of 3 is appropriate.

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 clearly states it performs 'semantic search across the knowledge base' with a specific verb and resource. It also describes the output as 'relevant chunks with source info and graph context', which helps differentiate it from sibling tools like 'blast_radius' or 'check_conventions'.

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 for finding information via semantic search, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., when to use 'search' vs 'blast_radius' or 'get_status'). No when-not-to-use caveats are included.

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

Deploy Server