suggest_creators

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

With no annotations, the description carries the full burden and does disclose key behavior: results are ranked by views, existing brain creators are filtered out, and no write occurs without user selection. It omits how many suggestions are returned and that this likely queries an external service (latency/quota), which matters for a discovery call.

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 sentences, zero filler, with the discovery behavior front-loaded and the follow-up action second. Every clause (ranking, exclusion, user gate) earns its place.

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?

An output schema exists, so return-value explanation is unnecessary, and the description covers ranking, filtering, and the next step. The remaining gap is topic-parameter semantics and expected result volume.

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 0% for the single 'topic' parameter, so the description must compensate; it only implies the parameter by saying results are 'for a topic'. It does not say whether 'topic' is free text, must match list_topics output, or how matching/normalization works.

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 ('Find YouTube channels') plus the ranking rule ('ranked by views in search results') and a scope constraint ('excluding creators already in the brain'). This clearly separates it from siblings like add_creator (mutation) and search_brain (existing inventory).

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 explicit downstream routing: show results to the user, then call add_creator only for the ones they choose — a clear sequencing and human-confirmation rule. It does not address when *not* to use this tool (e.g. checking existing creators via search_brain/list_topics), leaving one gap.

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