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

With no annotations provided, the description carries the transparency burden. It discloses what the tool returns, that results are ranked, that trust and security scores are included, and that security flags must be surfaced transparently. It does not explicitly state non-mutating behavior or authentication needs, but the 'find' semantics make those less critical.

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, front-loads the core function, and earns each sentence by explaining inputs, outputs, and the required flag-surfacing behavior. It contains no filler or redundant restatement of the tool name.

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's moderate complexity and the presence of an output schema, the description is largely complete: it covers the input type, ranked result format, scoring criteria, and transparency expectation. It could strengthen completeness by noting how top_k and max_pricing_tier shape results or by referencing sibling tools, but these are not essential for correct invocation.

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 description coverage is 100%, so the schema already documents problem, top_k, and max_pricing_tier. The description adds value by explaining the scoring dimensions of results, but it does not add parameter-level meaning beyond the schema, so 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 states a specific verb ('return') and resource ('ranked solution recommendations'), and clearly identifies the input (user's problem in natural language) and the output fields (semantic fit score, trust/security score, flags, rationale). This distinguishes it from the sibling tools compare_tools and get_trust_report, which address comparison and trust details rather than initial discovery.

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 gives clear context for when to use the tool: whenever a user expresses a problem in natural language and needs solution recommendations. It does not explicitly describe exclusions or alternatives, but the intended trigger is evident from the first sentence.

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