check_similarity

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

With no annotations, the description bears full burden for behavioral disclosure. It states it returns a 'plagiarism risk assessment' but does not explain how the metrics are combined, any limitations, or side effects. The behavior is only partially described.

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 fairly concise but includes an Args section that simply restates parameter names with trivial descriptions, adding little value. The first sentence is clear and front-loaded.

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?

There is no output schema, so the description should detail the return format. It only vaguely mentions 'plagiarism risk assessment'. The optional api_key parameter is not explained, leaving the agent to guess its purpose.

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 repeats the parameter names with minimal elaboration ('First text', 'Second text to compare against') but does not explain the optional api_key parameter or its purpose. Since schema coverage is 0%, more detail is needed.

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 compares two texts using specific metrics (Jaccard, cosine, trigram overlap) and returns a plagiarism risk assessment. This distinguishes it from sibling tools like analyze_tone or build_outline.

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?

No guidance is provided about when to use this tool versus alternatives or when not to use it. The sibling tools are not mentioned, and no usage context is given.

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