List AI plans

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

Beyond the readOnlyHint/destructiveHint annotations, the description discloses important behavior: result ordering, the meaning of each state, that archived plans are a separate listing, and that AI plan creation may be disabled based on server configuration. This gives the agent concrete expectations and even a user-facing troubleshooting instruction.

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 front-loaded with the core purpose and ordering, then adds state semantics, archived behavior, and the environment caveat. Each sentence adds distinct value and none is redundant with the settings or schema. The length is justified by the useful operational context it provides.

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?

For a read-only list tool with an output schema present, the description covers ordering, state values, archived behavior, pagination implications via limit/offset, and the organizational scope. No critical behavioral gap remains for an agent deciding whether and how to call it.

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 schema documents archived and id_organization; the description adds meaning by explaining that archived selects a separate listing and that plans belong to an organization. Limit and offset have no descriptive text in the schema and are not addressed in the description, though they are standard pagination parameters. With 50% schema coverage, the description partially compensates but not fully.

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 states a specific verb ('list') and resource ('AI-generated publication plans of an organization') and immediately adds scope ('newest first'). It also defines the plan states, making the returned data understandable. The tool is clearly distinguishable from singular get_ai_plan and get_ai_plan_results by name and scope.

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 gives clear practical guidance: archived plans are never mixed with active ones and require 'archived: true'. It also explains why create_ai_plan may be absent and what the user should do, which is useful context. It does not explicitly contrast with sibling read tools like get_ai_plan, so exclusions are not fully spelled out.

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