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

Annotations already declare openWorldHint=true, idempotentHint=true and non-destructive, so the safety profile is covered. The description adds nothing beyond them: it doesn't say that results depend on stored/override preferences, that analyzing is a networked, potentially slow operation, or what the produced 'criteria' look like.

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?

One front-loaded sentence with no waste, but it is thin enough that it omits the return value and statefulness the tool actually has.

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?

This is a 6-parameter tool with durable conversation state, preference modes and no output schema, yet the description says nothing about what it returns (derived criteria? a list_id?) or how conversation_id affects follow-ups. For this complexity the description is materially incomplete.

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 83%, so the schema already documents uid, bearer_token, conversation_id, preferences_mode and agent_preferences. The description only hints that the input is a set of example creators, adding no detail on handles limits or preference modes; 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?

States a specific verb (Analyze) and resource (example Instagram creators) plus the intent of the output (derive criteria). It implicitly distinguishes itself from discover_creators by positioning itself as the upstream 'seed' step, but never names that sibling explicitly.

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?

'before sourcing similar creators' gives a clear sequencing cue that tells the agent this is a pre-sourcing step rather than the sourcing tool itself. No explicit exclusions or named alternatives, which keeps it at a 4 rather than a 5.

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