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MsFixer101
by MsFixer101

search_knowledge

Search the knowledge base using semantic similarity to find relevant information. Retrieve ranked chunks with source details before creating new resources.

Instructions

Search the knowledge base using semantic similarity. Returns ranked chunks with source info. Use this to find relevant information before creating new resources.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query
node_idNoScope search to a specific node and its descendants
limitNoMax results to return (default 10)
Behavior4/5

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

Since no annotations are provided, the description must disclose behavioral traits itself. It explains that the search is semantic and returns ranked chunks with source info, indicating a read-only, retrieval operation. It does not explicitly state that no data is modified, but the context implies safety.

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 concise sentences. The first sentence defines functionality and output; the second provides usage context. No redundant or filler content, making it easy to parse quickly.

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 3 simple parameters and no output schema, the description sufficiently covers the core behavior and return type ('ranked chunks with source info'). It could be more complete by mentioning pagination or result format, but is adequate for its complexity.

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 the schema already documents all three parameters well. The description adds no extra meaning beyond the schema (e.g., no clarification on query formatting or node_id usage). 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 action ('Search'), target ('knowledge base'), method ('using semantic similarity'), and output ('Returns ranked chunks with source info'). It is distinct from sibling tools which are for browsing, fetching, or saving.

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

Usage Guidelines4/5

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

Provides explicit usage guidance: 'Use this to find relevant information before creating new resources.' This helps the agent understand when to apply the tool, though it does not mention when not to use it or list alternative tools.

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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