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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds behavioral details: composite one-call, fans out across APIs, partial failures with timing (bundlephobia can take 5-30s), and graceful degradation (sources_failed lists timeouts). Return structure is also described.

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?

Description is a single paragraph but front-loads the purpose and APIs. Each sentence serves a purpose, but it could be slightly more structured with bullet points for returns. Efficient overall, earning a 4.

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 complexity (external APIs, complex return), no output schema, the description nearly covers everything: return fields, ecosystem scope, partial failure behavior, timing, and sources. Combined with excellent annotations and full schema coverage, it is highly 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 coverage is 100% with both parameters described. Description adds minimal extra value, only confirming version defaults to latest. Baseline 3 is appropriate as the schema already provides clear 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 clearly states the tool performs a composite check for adding an npm package, using deps.dev and bundlephobia. It specifies the verb 'scan' and resource 'dependency', and distinguishes from sibling tools like 'scan_competitor_ai_presence' by focusing on npm package evaluation.

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?

Explicitly says 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' Also provides when-not-to-use: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly.' This gives clear usage context and alternatives.

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