find_duplicates

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

With no annotations, the description carries the full burden. It describes a scanning action that likely does not modify data (finds, not deletes), but it does not explicitly state whether the tool is read-only or what side effects (e.g., performance impact) might occur. The behavioral disclosure is adequate but incomplete.

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 two sentences with no wasted words. It front-loads the verb and resource and immediately provides additional detail about what duplicates are found and their impact. Every sentence serves a purpose.

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 no output schema, the description does not explain what the tool returns (e.g., list of duplicates, count, file paths). For a simple scanning tool, this omission leaves the agent unsure about the output format. However, the input schema is fully covered.

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 tool has no parameters, so schema coverage is 100%. The description adds meaning by explaining the tool's purpose and what it finds, which is valuable beyond the empty schema. Baseline is 4 for zero parameters.

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 scans for duplicate content across Claude Code conversations, including conversations, images, and documents. It explains the purpose of freeing up storage and context space, distinguishing it from sibling tools like scan_image_issues or search_conversations.

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 explicit guidance on when to use this tool versus alternatives such as clean_claude_directory or scan_image_issues. The description implies it should be used to identify duplicates for cleanup, but it does not provide exclusions or context about when to prefer this tool over similar sibling tools.

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