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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world). The description adds behavior beyond that: selection rotates families and keeps loud reactions rare 'the way a believable feed does,' and it explicitly states 'Costs no credits' – meaningful operational context.

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?

Front-loaded with what it does, then usage, then routing and cost. The ten-family enumeration is dense but serves selection; only minor tightening is possible.

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 an output schema exists, return values needn't be explained, and the description covers cost, selection logic, and downstream wiring. Adequate for a read-only suggestion tool, with no significant gaps.

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 baseline is 3, but the description adds relational meaning: mood 'overrides purpose,' purpose defaults to feature_reveal when the user has an app, and exclude exists so 'the next post feels like a different day.' That is more than restating the schema.

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: 'Ready clip prompts from ClipUGC's reaction library,' with concrete scope (about forty silent reactions in ten families). An agent can distinguish this from suggest_hooks/suggest_influencers and knows exactly what artifact it produces (copy-ready prompts with the mouth closed).

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?

Explains how to drive it (ask for count + purpose, or a single mood) and routes the output forward ('Pass a key as reaction to create_clip, or several to create_clips'). It gives clear context but never states when NOT to use it or contrasts it against sibling suggestion tools.

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