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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description adds value beyond structured data by disclosing the UI-label alias behavior ('color ramp' finds ShaderNodeValToRGB) and ranking of results. It doesn't introduce any hidden side effects or 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?

Two efficient sentences with no filler. The core purpose and scope are front-loaded, examples are embedded compactly, and the special UI-label behavior is appended as a valuable clarification.

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?

For a simple read-only search tool with a fully documented 2-parameter schema and an output schema, the description covers purpose, query semantics, special matching behavior, and how results relate to a sibling tool. Nothing critical is missing for correct selection and 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 coverage is 100%, so the baseline is 3, but the description enriches the query parameter's meaning by showing that matching is not only over identifiers but also over node UI labels. It also implies the query string expects human-readable terms like 'subsurf modifier' rather than raw identifiers.

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 and resource: 'Keyword search over every documented bpy identifier'. It distinguishes itself from the sibling docs_bpy_lookup by explicitly positioning itself as the search step that feeds lookup, and from docs_manual_search by limiting scope to bpy API identifiers.

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 clearly indicates this tool should be used to find bpy identifiers, and that results are meant for docs_bpy_lookup. It provides concrete query examples and notes UI-label matching behavior, but it does not explicitly state when not to use it versus the manual search tools.

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