check_package

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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds valuable context beyond that: response size (~2k tokens), machine-readable format, and a concrete return shape. It doesn't contradict annotations and enriches the behavioral profile.

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 highly efficient: three short sentences encapsulate what the tool does, when to use it, and what it returns. It is front-loaded with the most important information and contains zero filler.

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?

For a read-only reporting tool with strong annotations, the description covers the essential context: return type, token size, and key fields. It omits some details (e.g., scoring scale), but the absence of an output schema is mitigated by the explicit return structure. Adequate for the tool's complexity.

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 67%, which is moderate. The description does not add new meaning for the parameters beyond what the schema already defines (e.g., package name, version, ecosystem). However, the return structure implicitly clarifies the semantics of the package parameter. This is adequate but not outstanding.

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 uses a specific verb and resource ('Full machine-readable JSON report') and clearly distinguishes from get_package_prompt by contrasting the two use cases. It also lists the return fields, making the tool's scope unmistakable.

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?

Explicit 'USE WHEN' clause identifies the intended scenario (programmatic parsing for CI gating, UI, sub-field extraction) and provides a direct alternative ('Otherwise prefer get_package_prompt'). This is a model of clear usage guidance.

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