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

With no annotations provided, the description carries the full burden, and it does so thoroughly. It discloses the full output shape: advisory IDs, aliases, summaries, severity details, fix versions or 'no fix published', dates, and a summary. It also explicitly cautions that absence from OSV is not proof of safety, which is a meaningful behavioral limitation for an AI agent to understand.

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 a single dense paragraph that front-loads the primary action and scope, then systematically lists input constraints, output contents, and a caveat. Every sentence contributes either to call construction or expectation setting, with no filler or repeated schema content.

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 has no output schema unreplaced, no annotations, and one nontrivial nested parameter, the description is unusually complete. It explains exactly what will be returned per packageeb, what the aggregate summary includes, what the input limits are, and how to interpret the results. An agent has everything needed to invoke this tool correctly and understand its limitations.

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?

The description adds important semantics beyond the input schema by bounding calls to 1-50 packages and emphasizing exact versions rather than ranges. It also enumerates the supported ecosystems, which helps an agent construct valid requests. The schema already documents per-field details like name format and the 'exact version' requirement, so the description supplements rather than replaces that information.

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 opens with a specific verb and resource: 'Look up the known vulnerabilities affecting exact package versions in the public OSV database.' It names the supported ecosystems and clearly distinguishes that this is an evidence-gathering tool, not an advice-giving one. This leaves no ambiguity about what the tool does.

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 clearly conveys usage constraints: callers must specify exact versions, can check 1 to 50 packages per call, and should treat results as evidence only. It also states a key limitation—absence from OSV does not prove safety. It does not name alternative tools or explicit when-not-to-use conditions, but no siblings are provided and the context is otherwise clear.

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