check_interactions

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. While it mentions what the tool returns (risk level, FDA adverse event data, CYP450 conflicts), it lacks critical behavioral details such as whether this is a read-only operation, potential side effects of incorrect use, data sources, or limitations in handling misspellings. For a safety-critical tool with zero annotation coverage, this is a significant gap.

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, followed by output details and usage guidelines in just two sentences. Every sentence earns its place by providing essential information without redundancy or unnecessary elaboration.

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 complexity of a safety-checking tool with no annotations and no output schema, the description is moderately complete. It covers purpose, outputs, and usage context but lacks details on behavioral traits, error handling, or response format. This is adequate for basic use but leaves gaps for reliable agent operation.

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 100%, so the schema already fully documents both parameters (supplements and medications). The description does not add any additional meaning or context beyond what the schema provides (e.g., it doesn't clarify parameter interactions or usage examples). Baseline 3 is appropriate when 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: 'Check if supplements are safe with medications' with specific outputs (risk level, FDA adverse event data, CYP450 conflicts). It uses a precise verb ('Check') and identifies the resources involved (supplements and medications), making it distinct from sibling tools like 'explain_interaction' or 'get_compound_info'.

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 explicitly states when to use this tool: 'Use when user mentions supplements + meds.' This provides clear, actionable guidance for the AI agent on the appropriate context for invoking this tool versus alternatives, though it doesn't name specific sibling tools as alternatives.

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