engage

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

Annotations indicate mutation (readOnlyHint=false) and non-destructiveness. The description adds that every candidate passes a relevance gate, max_actions is capped per account, and draft mode prevents execution. These details go beyond annotations, though the direct execution mode is only implied.

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, about 60 words, front-loaded with purpose. Every sentence adds essential information without fluff. Well-structured for quick comprehension.

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 tool has an output schema (not shown) and siblings, the description covers core behavior: actions, draft mode, caps. It does not explain return values or error handling, but these are inferred from the schema. Overall adequate for standard usage.

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%, but the description clarifies that actions is a subset of ['like', 'retweet'] with default ['like'] and that max_actions is hard-capped. However, keywords and account are not explained, and the schema lacks enums. The description adds moderate value beyond the bare 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?

The description clearly states the tool engages with tweets from keyword search using actions like or retweet. It specifies the verb 'engage' and the resource 'tweets found via keyword search', but does not explicitly differentiate from siblings like queue_engagement or reply_to_tweet.

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?

The description mentions draft mode by default and hard-capped max_actions, implying when to use (mass engagement with approval). However, it does not explicitly state when not to use or provide alternatives, leaving some reliance on inference.

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