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

Annotations only provide readOnlyHint and openWorldHint, so the description adds value by detailing response contents: facets, confidence, corroboration score, full provenance, and entity-level provenance. It does not contradict annotations and provides more behavioral context than required.

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 and front-loaded with the core purpose, followed by response details, usage guidance, and inputs. The phrase 'the Gapup moat' is slightly non-functional but does not significantly detract from 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 strong output schema, annotations, and simple parameter set, this description is complete: it explains the purpose, response structure, prerequisites, and exact usage scenario. It leaves no critical gap for an agent to decide whether and how to invoke the tool.

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% with each parameter described in detail (entity_id, entity_type, async). The description only repeats 'Inputs: an entity id and its type' without adding new semantic meaning beyond what the schema already states, so the baseline 3 applies.

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 identifies the tool as returning an 'enriched tag profile' for a content entity, with a specific verb ('Return') and resource. It distinguishes itself from sibling tools by emphasizing facets, confidence, corroboration, and provenance for fine-grained characterisation, which is unique among content-related siblings like content_catalog or content_similar.

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?

Explicitly states when to use: 'when an agent has a franchise or work id (from content_catalog) and needs a fine-grained, machine-readable, verifiable characterisation for matching, recommendation, contextual targeting or analysis.' No exclusions or alternative names are given, but the context is clear and actionable.

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