Analyze a single dependency version change

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly describes what the tool returns (structured upgrade analysis with specific components), the scope (single package, two versions), and supported ecosystems (npm and pypi). It doesn't mention rate limits, authentication needs, or error conditions, but provides substantial behavioral context.

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 efficiently structured with two sentences: the first explains what the tool does and returns, the second provides usage guidelines and sibling differentiation. Every sentence adds value with zero waste, and it's appropriately front-loaded with the core functionality.

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 tool with no annotations and no output schema, the description provides substantial context about behavior, scope, and usage. It covers what the analysis includes, when to use it, and the alternative tool. The main gap is lack of information about output format/structure, but given the detailed description of analysis components, this is reasonably complete.

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 documents all four parameters thoroughly. The description adds minimal parameter-specific information beyond what's in the schema (mentions 'from -> to' and example packages like 'react', 'axios', 'lodash'), but doesn't provide additional syntax or format details. Baseline 3 is appropriate when 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 analyzes a single dependency version change with specific outputs (semver classification, release notes summary, breaking changes, security advisories, migration guide links, recommendation). It explicitly distinguishes from the sibling tool analyze_packages_bulk by specifying 'single dependency' vs 'many packages at once or a Dependabot batch'.

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 explicit guidance on when to use this tool ('when the user asks about a specific package upgrade') with concrete examples, and when to use the alternative ('For analyzing many packages at once or a Dependabot batch, use analyze_packages_bulk instead'). This gives clear context for tool selection.

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