social-research-mcp

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 mentions that results are saved to a local database, which adds some context about persistence, but it doesn't cover critical aspects like rate limits, authentication needs, error handling, or whether the scraping is read-only or mutative. This leaves significant gaps for a tool with potential behavioral complexity.

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 concise with two sentences that efficiently cover the core action and outcome. It's front-loaded with the main purpose, though it could be slightly more structured by explicitly separating search methods from the result handling. Overall, it avoids unnecessary verbosity.

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 complexity of a scraping tool with no annotations and no output schema, the description is incomplete. It lacks details on return values, error conditions, rate limits, and how the saved data interacts with sibling tools like 'timeline_query'. For a 4-parameter tool with behavioral implications, this is inadequate.

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 adds minimal semantic value beyond the input schema, which has 100% coverage. It mentions search methods ('profile, hashtag, or keyword') that loosely map to parameters like 'profiles', 'hashtags', and 'search', but doesn't provide additional details on syntax, interactions between parameters, or default behaviors. With high schema coverage, the baseline is 3.

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 a specific verb ('scrape') and resource ('videos from TikTok'), distinguishing it from sibling tools like 'scrape_facebook' or 'scrape_instagram' by specifying the platform. However, it doesn't explicitly differentiate from other TikTok-related tools (none exist in the sibling list), so it's not a perfect 5.

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 by listing search methods ('profile, hashtag, or keyword'), but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'scrape_youtube' or 'timeline_query'. No exclusions or prerequisites are mentioned, leaving usage context somewhat vague.

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