Search Companies (Natural Language)

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering safety and idempotency. The description adds valuable behavioral context beyond annotations: it explains the AI-powered natural language understanding, pagination behavior with cursors, and the limited return format (URNs requiring harmonic_get_company for details). No contradiction with annotations exists.

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 well-structured with clear sections (What it does, Example queries, Returns, Next Steps) and efficiently conveys information. However, the JSON return example is somewhat redundant since there's no output schema, and the 'Returns' section repeats similar information in two formats, slightly reducing conciseness.

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 complexity (natural language search with 5 parameters), rich annotations (covering safety and idempotency), and lack of output schema, the description is highly complete. It explains the tool's purpose, usage, behavioral traits, return format, and integration with other tools, providing all necessary context for an AI agent to use it effectively.

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 fully documents all 5 parameters. The description adds minimal parameter semantics beyond the schema—it provides example queries that illustrate the 'query' parameter usage but doesn't explain parameter interactions or additional context. This meets the baseline 3 when schema does the heavy lifting.

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 explicitly states 'Search for companies using natural language queries' with the specific verb 'search' and resource 'companies', clearly distinguishing it from sibling tools like harmonic_lookup_company (which appears to be a direct lookup) and harmonic_find_similar_companies (which likely operates on existing companies). The 'primary entry point for discovering companies' phrase further establishes its distinct role.

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 guidance on when to use this tool ('primary entry point for discovering companies') and what to do next ('Use harmonic_get_company for full company details'). It distinguishes from alternatives by emphasizing natural language queries versus more specific lookup tools in the sibling list, though it doesn't explicitly name when NOT to use it.

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