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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds meaningful behavioral context by explaining that results are filtered to tools with 'active structured runtime evidence' and that it returns 'observed status, run counts, setup, permissions, and evidence links rather than popularity alone.' This goes beyond the annotations without contradicting them.

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 two sentences with no filler. The first sentence states the action and resource, and the second sentence summarizes the returned fields and the core differentiator. It is front-loaded and every clause earns its place.

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 that all parameters are optional and covered by the schema, annotations cover read-only/open-world behavior, and an output schema exists, the description is largely complete. It communicates the core value proposition and return composition, though it does not detail sorting, pagination, or default filter behavior, which are relatively minor gaps.

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 input schema has 100% description coverage for all four optional parameters, including enum values for type and runtimeStatus. The description provides a high-level context by mentioning 'observed status' and evidence-backed filtering, but it does not add detailed parameter semantics beyond what the schema already explains. Baseline 3 is appropriate.

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 begins with a specific verb and resource: 'Search Skills, MCP servers, Agents, APIs, and tools' and adds the key differentiator 'that have active structured runtime evidence.' This clearly distinguishes the tool from sibling search tools like search_signals, which likely search content rather than execution evidence.

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 implies when to use this tool: when the user wants evidence-backed runtime results rather than popularity-based results. It does not explicitly name alternatives like search_signals or state when not to use them, but the focus on 'observed status, run counts, setup, permissions, and evidence links' gives clear selection context.

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