mcp-astgl-knowledge

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns 'the best matching answer with source URL and related articles', which gives some output context, but lacks details on error handling, rate limits, authentication needs, or how 'best matching' is determined. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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?

The description is a single, well-structured sentence that efficiently conveys the core functionality and output. It's front-loaded with the main purpose and avoids unnecessary details. However, it could be slightly more concise by integrating the output details more seamlessly.

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 the tool's moderate complexity (single parameter, no output schema, no annotations), the description is minimally adequate. It covers the purpose and output format but lacks usage guidelines, behavioral details, and differentiation from siblings. With no output schema, it should ideally explain return values more thoroughly, though it does mention 'source URL and related articles'.

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 input schema has 100% description coverage, with the 'question' parameter fully documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples of effective questions or formatting tips). Baseline score of 3 is appropriate since the schema does the heavy lifting.

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 tool's purpose: 'Get a direct answer to a question about MCP servers, local AI, or AI automation from ASTGL's knowledge base.' It specifies the verb ('Get'), resource ('direct answer'), and scope ('about MCP servers, local AI, or AI automation'), but doesn't explicitly differentiate from sibling tools like 'list_topics' or 'search_articles' beyond mentioning it returns 'the best matching answer'.

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?

The description provides no guidance on when to use this tool versus alternatives like 'list_topics' or 'search_articles'. It mentions the tool returns 'the best matching answer with source URL and related articles', but doesn't specify scenarios where this is preferable over other search or listing tools. No exclusions or prerequisites are stated.

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