social-research-mcp

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the requirement for OPENAI_API_KEY, which is useful context, but fails to describe other behavioral traits such as rate limits, authentication needs beyond the API key, what happens if no results are found, or the format of returned results. For a search tool with no annotation coverage, this leaves significant gaps.

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 extremely concise with only two sentences, front-loading the core purpose and key requirement. Every sentence earns its place by providing essential information without redundancy or fluff, making it easy for an AI agent to parse quickly.

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 complexity (semantic search with 5 parameters) and no annotations or output schema, the description is incomplete. It covers the purpose and API key requirement but lacks details on behavioral traits, result format, and error handling. However, the high schema coverage mitigates some gaps, making it minimally adequate but with clear room for improvement.

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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by emphasizing the semantic nature of the 'query' parameter, but it doesn't provide additional syntax, format details, or usage examples. Baseline 3 is appropriate when 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 with specific verbs ('semantic search') and resources ('timeline database', 'posts'), distinguishing it from sibling tools like timeline_query (likely keyword-based) or timeline_stats/trends (analytics-focused). It explicitly mentions AI embeddings and meaning-based search, which clarifies its unique functionality.

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 implies usage for semantic search across timeline posts but doesn't explicitly state when to use this tool versus alternatives like timeline_query (which might be for keyword search) or the various scrape_* tools. It mentions the requirement for OPENAI_API_KEY, which provides some context, but lacks clear guidance on scenarios where this tool is preferred over siblings.

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