Manticore Search MCP

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

With no annotations provided, the description carries the full burden. It successfully discloses the return format ('markdown text'), the filtering behavior ('returns only matching sections'), and the context line logic for the before/after parameters. It does not explicitly declare read-only/safety properties or error handling, but 'Fetch' implies a safe read operation.

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

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

Appropriately structured with clear sections (implied Args, Returns, Examples) using Google-style docstring formatting. Every sentence earns its place: the opening defines purpose, the Args section explains parameters, Returns clarifies output format, and Examples demonstrate concrete usage. No waste.

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

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

Given 4 parameters with 0% schema coverage and an output schema existing, the description is complete. It documents all parameters, explains the return type (leaving detailed schema to the output_schema), provides usage examples, and establishes ecosystem context with sibling tools. No gaps remain for this complexity level.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, requiring the description to fully compensate. It excellently documents all 4 parameters: file_path includes a concrete example ('Searching/KNN.md'), content explains the filtering semantic, and before/after clarify they represent line counts with default values. This fully compensates for the schema deficiency.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific verb and resource ('Fetch documentation from Manticore Search manual'). It effectively distinguishes from sibling tools by explicitly referencing list_documentation() as a prerequisite discovery mechanism, establishing the workflow relationship between the two.

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

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

Explicitly states when to use this tool versus its sibling: 'Use list_documentation() first to discover available files.' This provides clear prerequisite guidance. The examples further clarify usage patterns showing both filtered and unfiltered invocation patterns.

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