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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds valuable behavioral context beyond annotations: the fan-out/merging behavior, PyPI's 400 not_supported error, and result normalization details (npm relevance score, Docker isOfficial). This fully discloses operational traits.

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 three sentences long, front-loaded with the core action, and every sentence contains distinct, necessary information (registry behavior, pypi fallback, result format). No wasted words; it earns its length.

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?

The tool has no output schema, but the description compensates by describing the normalized PackageSummary result structure and per-registry additions. The description covers error behavior, alternatives, and fan-out semantics, making it fully self-contained for an agent to invoke 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 baseline is 3. The description adds meaning to 'registry' by explaining the 'all' fan-out and the pypi error, and clarifies that q searches for matching packages. While the schema already documents enums and limits, the description provides operational context that the schema cannot.

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 uses a specific verb ('Search') and resource ('registry for packages') with a clear parameter ('q'). It distinguishes itself from sibling get_* tools by focusing on search rather than direct retrieval, and explicitly clarifies registry-scoped vs. cross-registry behavior.

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 when-to-use guidance: it explains when registry=all is appropriate (fan out to three registries), and explicitly warns against using registry=pypi, directing users to get_package instead. This is a clear exclusion and alternative, which is exceptional guidance.

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