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. While it mentions what statistics are returned, it doesn't describe important behavioral aspects like whether this is a read-only operation, whether it requires authentication, rate limits, pagination behavior, or what happens when no data matches the filters. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 perfectly concise - a single sentence that efficiently communicates the core purpose and enumerates the specific statistics returned. Every element earns its place, with no wasted words or redundant information.

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 (aggregation across multiple metrics), no annotations, no output schema, and 3 parameters, the description is minimally adequate. It explains what statistics are returned but doesn't cover behavioral aspects, usage context, or output format details. The high schema coverage helps, but for a statistical tool with no output schema, more context about the return structure would be beneficial.

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 description doesn't mention any parameters, while the input schema has 3 parameters with 100% description coverage. The schema already documents platforms (with enum values), date_from, and date_to. The description's mention of 'by platform' and implied date filtering aligns with the parameters but adds no additional semantic context beyond what the schema provides, meeting the baseline for high schema coverage.

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 aggregate statistics from your timeline' with specific metrics listed (total posts by platform, avg engagement, most active authors, top hashtags). It uses a specific verb ('Get') and resource ('aggregate statistics from your timeline'), but doesn't explicitly distinguish it from sibling tools like timeline_query, timeline_search, or timeline_trends, which likely have overlapping domains.

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. With siblings like timeline_query, timeline_search, and timeline_trends available, there's no indication of when this statistical aggregation tool is preferred over those other timeline-related tools or when it should be avoided.

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