Human handoff queue: quote / follow / like / cold reply as one-tap links

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

Annotations include readOnlyHint: false and destructiveHint: false, which the description is consistent with. It adds substantial behavioral context: the reconcile mechanism (detecting completion via owned reads), the algorithmic impact (quote posts as originals, follows creating mutuals), and the action-specific behaviors (done/drop mark manually). This goes beyond the annotations to explain side effects and automation logic.

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?

The description is well-organized with bullet-style sub-actions and a separate 'Why this matters' section. It front-loads the main purpose in the first sentence, then details each action. It is moderately long but every part adds value—the algorithmic reasoning helps the agent decide when to call this tool. No wasted words, though some redundancy with the schema enum values exists.

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 complexity (8 parameters, 5 action types, no output schema), the description provides a strong overall picture: it explains the workflow, the reconcile logic, the algorithmic importance, and the division of responsibility. It doesn't specify the return format or error handling, but for a queue-management tool with these annotations and schema hints, it is sufficient for an agent to know how to invoke it and what to expect.

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?

The input schema covers only 50% of parameters with descriptions (id, why, text, target_username have descriptions; kind, action, include_done, target_post_id lack textual descriptions). The description compensates by clarifying the role of these parameters in the context of each action (e.g., text as drafted post/reply text, target_username as author handle required for follow, id for done/drop). It also explains the 'kind' enum values and their algorithmic significance, adding meaning beyond the raw 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's purpose: 'Manage the queue of actions only a human can do on a pay-per-use account.' It enumerates specific sub-actions (add, list, done/drop, reconcile) with concrete semantics, and distinguishes itself from siblings by focusing on the human handoff queue for restricted actions.

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 explains when to use the tool: for actions that require human intervention due to platform restrictions (X removed follows, likes, quote-posts, un-summoned replies). It states 'The agent drafts; the human taps,' clearly indicating the division of labor. It does not explicitly list alternative tools for when not to use it, but the platform restriction context makes the appropriate usage obvious.

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