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

Annotations already declare readOnly, openWorld, and idempotent hints, so the description doesn't need to restate those. It adds valuable behavioral context by naming the external data sources (npm registry and libraries.io), describing the output (structured metrics and warnings), and noting what triggers warnings (stale or rapidly changing packages). No contradiction with annotations.

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 three well-organized sentences: purpose, data sources, input, and output. It is front-loaded with the core use case, then provides necessary details without fluff or repetition. Every sentence adds value.

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's moderate complexity and the presence of an output schema, the description covers the essential points: intended user, input, data sources, and output. It is nearly complete but lacks explicit mention of the optional 'lookbackDays' parameter and has a slight ambiguity with 'version ranges' (schema expects 'version' as a string). These small gaps prevent a perfect score.

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 low (33% with only async described). The description compensates by explaining the main parameter ('Input a list of package names and optional version ranges') and clarifying the version field's role. However, it does not mention the 'lookbackDays' parameter at all, leaving a gap in understanding for that parameter.

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 identifies the tool's purpose: tracking update velocity of open-source dependencies and assessing impact on DORA metrics. It uses a specific verb-resource combination ('track the update velocity') and distinguishes itself from related siblings like dependency_vulnerability_scan by focusing on velocity rather than vulnerabilities.

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 a clear use case (CTO assessing DORA impact) and implies when to use this tool, but does not explicitly mention alternatives or exclusion scenarios. It lacks a direct 'use this instead of X' statement, but the context is understandable and relevant for the target user.

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