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ChatCrystal

ChatCrystal

by ZengLiangYi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

search_knowledge

Find relevant notes from your AI conversation knowledge base using semantic search, with results ranked by relevance.

Instructions

Semantic search across your AI conversation knowledge base. Returns matching notes ranked by relevance.

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_knowledge"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of results
queryYesSearch query text

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.5

TDQS

A3.5/5.0
Behavior3/5

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

The description mentions it returns notes ranked by relevance, indicating a read and search behavior, but lacks details on pagination, result format, no-result behavior, or any side effects. With no annotations, more disclosure would be beneficial.

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 concise with two sentences, front-loading the core purpose. There is no unnecessary text, making it efficient for an AI agent to parse.

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 simple tool with two parameters and no output schema, the description covers the main functionality but omits details on the return format of notes and edge cases. It is adequate but not fully comprehensive.

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?

The input schema already provides descriptions for both parameters (query and limit). The tool description adds no additional meaning beyond what the schema states, thus baseline 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 tool performs semantic search across a knowledge base and returns ranked notes. It distinguishes itself from siblings like list_notes (general listing) and get_note (retrieving a specific note) by specifying the search nature and ranking.

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?

No guidance is provided on when to use this tool versus alternatives such as list_notes or recall_for_task. The description only states what it does without contextual recommendations.

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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