Slander 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 that the tool 'Uses AI to produce creative, context-aware queries,' which adds some context about the method. However, it doesn't disclose other behavioral traits such as rate limits, error handling, or what the output looks like (e.g., format, examples). For a tool with zero annotation coverage, this leaves significant gaps in understanding its operation.

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 sized with two sentences that efficiently convey the tool's purpose and method. It's front-loaded with the main function and avoids unnecessary details. However, it could be slightly more structured by explicitly separating usage guidelines or output expectations, but overall, it's concise with minimal waste.

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 (AI-driven query generation) and lack of annotations and output schema, the description is somewhat complete but has gaps. It explains what the tool does and how it works (using AI), but doesn't cover output format or behavioral aspects like limitations. For a tool with no structured output information, more detail on expected results would improve completeness.

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 'target' parameter well-documented as 'Name of character to search for (e.g., 'LeBron James', 'Darth Vader').' The description adds minimal value beyond this, mentioning 'target character' but not providing additional syntax or format details. With high schema coverage, the baseline score of 3 is appropriate, as 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: 'Generate effective Twitter search queries for finding slander, roasts, jokes, and memes about a target character.' It specifies the verb ('generate'), resource ('Twitter search queries'), and scope ('slander, roasts, jokes, and memes about a target character'). However, it doesn't explicitly differentiate from sibling tools like 'fetch_posts' or 'rank_posts', which likely handle different aspects of content retrieval or ranking.

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 the tool's function but doesn't specify prerequisites, exclusions, or compare it to sibling tools like 'fetch_posts' or 'rank_posts'. There's implied usage for creating search queries, but no explicit when/when-not instructions or alternatives are stated.

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