Search operators

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

Annotations only indicate readOnly and non-destructive. The description adds critical behavioral details: offline operation, semantic re-ranking dependency, fallback behavior, stale_hint and data_version in results. No contradictions.

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 effectively front-loaded with the core purpose, each sentence adds unique value, and it's concise (~150 words) without redundancy.

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 8 parameters and no output schema, the description covers usage context, parameter interactions (e.g., version and category filters), edge cases (LLM fallback, stale hint), and token economy. It is complete for an agent to use 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?

With 100% schema coverage, baseline is 3. The description adds semantic context beyond schema: explains search mode behavior, semantic opt-in, and version/category filtering purpose. However, most parameter descriptions in schema are already clear.

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 clearly states the tool searches the embedded operator knowledge base, lists search dimensions (keyword, exact name, tag, category, etc.), and distinguishes from siblings like search_python_api by specifying the resource (operators) and scope (629 operators offline).

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?

It provides explicit when-to-use advice: 'Use it to discover the right operator before creating nodes instead of guessing a type'. It also offers token economy tips. However, it lacks explicit when-not-to-use guidance, though the sibling context implies alternatives.

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