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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open world), so the bar is lower. The description still adds real value by disclosing partial-failure behavior — 'Evidence remains available when generation is partial or fails' — and by characterizing the sources (TikTok/Instagram posts plus grounded web). It omits rate limits, latency, and auth expectations that the schema only hints at via bearer_token.

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?

Three sentences, front-loaded with the verb and output shape, then sequencing, then the resilience note. Dense but each sentence carries distinct information. The trailing resilience sentence is the least essential, keeping it just under top marks.

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 9-parameter research tool with no output schema, the description does the important work: it describes the return shape (1-5 trends with proof links, observations, usage guidance) and the failure semantics. With all parameters schema-documented, the remaining gap is minor — nothing on latency or how conversation_id follow-ups behave beyond the schema field.

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 every parameter is already documented in structured form and the baseline is 3. The description adds no syntax or format guidance beyond what the schema states; the '1-5 validated trends' phrasing also risks being read as the limit parameter, which actually governs collected posts (default 12).

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?

States a specific verb and resource ('Collect ... posts and grounded web sources', 'return 1-5 validated trends') and names the concrete artifacts returned: proof links, observations, safe usages. It also distinguishes itself from the nearest sibling by naming ideate_ugc_content, so an agent can route without opening schemas.

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?

Gives an explicit ordering rule: 'Use before ideate_ugc_content for trend-aware ideas.' That is a clear when-to-use signal tied to a named sibling. It stops short of stating when NOT to use it or pointing to adjacent alternatives (e.g. analyze_seed_creators, research_company) for already-known topics.

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