social-research-mcp

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the query is 'structured' and lists filterable fields, but doesn't describe what the tool returns (format, structure), whether it's paginated, rate limits, authentication requirements, or error conditions. For a query tool with 7 parameters, this leaves significant behavioral 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 appropriately concise with two clear parts: the core function and the filtering capabilities. The 'no AI needed' clause adds useful context. However, it could be more front-loaded by starting with the primary purpose before listing filters.

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?

For a query tool with 7 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what results look like, how they're structured, whether there's pagination, or what happens when no results match. The 'no AI needed' hint is helpful but insufficient for full contextual understanding.

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 7 parameters thoroughly. The description adds minimal value beyond the schema by listing the same filterable fields in natural language. No additional syntax, format details, or constraints beyond what the schema provides.

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 performs a 'structured query against the timeline database' with specific filtering capabilities (platform, date, engagement, author, hashtags). It distinguishes from AI-based analysis tools by stating 'no AI needed', but doesn't explicitly differentiate from sibling timeline tools like timeline_search or timeline_stats.

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. It mentions 'no AI needed' which might imply not to use it for analysis, but doesn't specify when to choose timeline_query over timeline_search, timeline_stats, or timeline_trends among the sibling tools.

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