oncofiles

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 states the tool performs 'AI enhancement' but doesn't specify what that entails beyond 'summary + tags'—e.g., whether it's a read-only operation, if it modifies documents, requires permissions, has rate limits, or what happens on errors. For a tool that likely involves AI processing and document updates, this lack of detail is a significant gap, though it's not contradictory.

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 front-loaded with the core purpose in the first sentence, followed by conditional usage and parameter details in a structured 'Args:' section. Every sentence adds value without redundancy, making it efficient and easy to parse. It's appropriately sized for the tool's complexity.

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 has an output schema (which likely covers return values), the description doesn't need to explain outputs. However, with no annotations and a single parameter, it adequately covers purpose and usage but lacks behavioral details (e.g., side effects, error handling). For an AI enhancement tool, this leaves gaps in understanding how it interacts with documents, making it minimally complete but not fully informative.

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 meaningful context for the single parameter 'document_ids': it explains that it's 'comma-separated document IDs to enhance' and clarifies the default behavior when omitted ('enhances all unprocessed'). Since schema description coverage is 0% (the schema only defines the type without descriptions), this compensates well, providing clear semantics beyond the bare schema. With 0 parameters effectively documented in the schema, the description does a good job, but could note format specifics (e.g., ID examples).

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: 'Run AI enhancement (summary + tags) on documents.' It specifies the verb ('Run AI enhancement'), resource ('documents'), and what the enhancement includes ('summary + tags'). However, it doesn't explicitly distinguish this tool from potential siblings like 'analyze_labs' or 'qa_analysis', which might also involve AI processing, so it doesn't reach the highest score.

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 clear context for when to use the tool: 'If document_ids is omitted, processes all documents that haven't been enhanced yet.' This gives explicit guidance on the default behavior. However, it doesn't mention when not to use it or name alternatives among the sibling tools (e.g., 'extract_document_metadata' might be related), so it falls short of a perfect score.

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