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

With no annotations, the description carries the behavioral burden and discloses important traits: data comes from OSV.dev, output shape is JSON with severity/advisory details, and usage costs $0.003 USDC via x402. It does not describe rate limits or error behavior, but the key operational facts are present.

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 compact and front-loaded: use case, inputs, outputs, data source, example, and price are each handled in one clause. Every sentence contributes to correct invocation.

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 three-parameter read query with no output schema and no annotations, the description supplies the missing return-value overview, data provenance, cost, ecosystem coverage, and a concrete example. Nothing essential for calling the tool correctly appears absent.

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 package, version, and ecosystem semantics. The description repeats the input names and adds ecosystem examples plus a sample query, but adds only limited meaning beyond the structured schema.

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 states a specific verb and resource: check whether an exact package version is vulnerable before installing or upgrading. It names the focused query and immediately clarifies the intended dependency-checking scenario, making the tool distinguishable from unrelated sibling tools.

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?

It gives clear context for when to use the tool: 'before installing or upgrading' to check a dependency. It does not name when-not-to-use cases or alternatives, but no obvious sibling tool covers vulnerability checking.

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