Search operators

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

The description goes far beyond the readOnlyHint and destructiveHint annotations. It discloses that the search is 'fully offline by default', that results are 'ranked by relevance', that semantic mode 'falls back to keyword' when the LLM endpoint is unavailable, that parameter_search includes menu options, and that results include a data_version and stale_hint when the TouchDesigner major differs. This is rich behavioral detail that significantly exceeds the annotations.

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 appropriately sized for the tool's complexity. It front-loads the core purpose in the first sentence, then proceeds logically through use case, return format, optional modes, data versioning, and querying guidance. Every sentence provides unique value, and there is no redundancy or tautology. The structure is well-organized despite 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?

Despite having no output schema, the description states what the tool returns ('name, family, summary, facets and optional matching parameters') and covers edge cases such as stale_hint and semantic fallback. It also provides usage examples and trade-offs (offline vs. semantic requiring an LLM endpoint). This is a complete and self-contained explanation for a search tool with 8 parameters.

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 the baseline is 3. The description adds extra meaning by explaining how parameters interact, e.g., 'Pass semantic:true to re-rank fuzzy candidates by embedding similarity' and 'With parameter_search, matched Menu parameters include their menu options.' It also contextualizes the version and category filters. This added context justifies a 4, though it does not fully re-explain every parameter since the schema already does.

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 opens with a specific verb and resource: 'Search the embedded operator knowledge base (629 operators)' and details the search dimensions (keyword, exact name, tag, category, subcategory, parameter metadata, version compatibility). It clearly distinguishes itself from sibling search tools by focusing exclusively on the operator knowledge base, with concrete example queries like 'what sends DMX?' and 'corner pin'.

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 explicitly states when to use the tool: 'Use it to discover the right operator before creating nodes instead of guessing a type.' This gives clear context and an implicit alternative (guessing). It also provides token economy advice ('use a specific query and a small limit'), but it does not explicitly contrast with sibling search tools such as search_touchdesigner_knowledge, so it falls just short of a 5.

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