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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond that: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed lists timeouts while the rest still returns. It also discloses the composite fan-out behavior, which is critical for understanding latency and failure modes.

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 dense but every sentence earns its place. It front-loads the core purpose and use case, then proceeds through return values, ecosystem scope, and failure handling in logical order. Despite its length, it avoids fluff and maintains a tight, information-rich structure.

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?

No output schema is provided, yet the description compensates by enumerating return fields: summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and recent alternative versions. It also covers timing (5-30s), partial failures, and ecosystem limitations. For a composite tool with this complexity, the description is complete enough for an agent to set expectations correctly.

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 coverage is 100%, so the baseline is 3. The description adds value by clarifying that 'package' accepts scoped packages like '@types/node' and that 'version' defaults to the latest published version. It also implicitly ties the version parameter to the 'recent alternative versions' output, giving more context than the schema alone. Not quite a 5 because the description doesn't elaborate on all edge cases, but it does add meaningful semantics.

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, actionable statement: "Composite 'should I add this npm package to my project' check in ONE call." It clearly names the resources (deps.dev, bundlephobia) and distinguishes this from sibling tools by focusing on npm package evaluation. It's unambiguous what the tool does and how it differs from general research 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?

The description explicitly says when to use it: "Use whenever an agent asks 'is X safe / popular / small' or 'what does adding lodash cost me'." It also provides an exclusion: "NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly," which guides the agent toward an alternative. This is clear, actionable guidance with alternatives covered.

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