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 'dHash + pHash' and 'near-duplicate detection,' which hints at the output being perceptual hashes, but it does not disclose whether the tool fetches a remote image, what happens on invalid input, whether it returns both hashes or one, or any rate limits. The description adds minimal behavioral context beyond the tool's name and title.

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 very short and front-loaded with the key terms 'pHash/dHash' and 'near-duplicate detection.' It is not bloated, but it is under-specified: the single sentence does not earn its place fully because it omits essential usage and parameter details. It is concise but at the expense of clarity.

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?

The tool has one parameter, no annotations, no schema descriptions, and a large sibling list of image-related tools (imagehash, imagerev, imagechunks, etc.). The description is too thin to let an agent select and invoke it correctly. It does not explain the input format, the output structure, or how it differs from the similarly named 'imagehash' sibling, making it incomplete for reliable use.

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 0%, and the only parameter 'q' has no description in the schema. The tool description does not explain what 'q' should contain (e.g., a URL, a file path, or base64 image data). Since the description fails to compensate for the complete lack of parameter documentation, the agent cannot reliably know how to populate the single input.

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 states a specific verb and resource: 'Image pHash/dHash: dHash + pHash for robust near-duplicate detection.' It identifies the tool as computing perceptual hashes for images, which is clear enough to distinguish it from generic image tools. However, it does not explicitly name sibling tools like imagehash or imagerev, and the phrasing is somewhat terse, leaving the exact operation (hashing an image URL vs. comparing hashes) slightly ambiguous.

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 does not mention that imagehash, imagerev, or imagechunks might be better for other image-analysis tasks, nor does it state prerequisites such as needing a publicly accessible image URL. The context signals show one optional parameter 'q' with no schema description, so the agent is left to infer that 'q' is the image query, but no explicit 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.