Get one AI plan

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

The description adds substantial behavioral context beyond the readOnlyHint and destructiveHint annotations: the pending/generating state returns nothing yet, generation may take minutes, generated posts are ordinary drafts, failed plans carry errors, and generated plans may still have warnings. This fully informs the agent of expected transient behavior and failure modes.

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 compact but information-dense: three sentences cover the return content, polling behavior, what the posts are, how to act on them, and failure/warning semantics. Every sentence earns its place and the key use case is front-loaded.

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?

There is no output schema, but the description compensates by describing the plan's state, spend, generated posts, error field, warnings, and how to interact with the resulting publications. This is enough for an agent to call the tool correctly and interpret the result appropriately.

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 100%; both id_ai_plan and id_organization are already documented in the input schema. The description does not add parameter-specific detail, but the schema already carries the burden, so a baseline of 3 is appropriate.

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 identifies a specific resource—a single AI plan—and the exact information it returns: state, spend, generated posts, errors, and warnings. It also distinguishes itself from list_ai_plans and get_publication by focusing on one plan and its lifecycle.

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?

It explicitly states when to use this tool: poll after create_ai_plan, while the plan is pending or generating. It also directs the agent to use get_publication and update_publication for generated draft posts rather than anything here, giving clear alternatives and exclusions.

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