List AI plans

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

The description adds substantial behavior beyond the readOnlyHint and destructiveHint annotations: newest-first ordering, meaning of each plan state, archived plans never mixing with active ones, and the server-side environment flag controlling creation of plans. It even explains the AI-credit cost rationale. This is rich, honest behavioral context that annotations alone do not convey.

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 then delivers state semantics, archived handling, and environment-related guidance. Every sentence earns its place, though the final two sentences about create_ai_plan and MCP configuration are tangential to listing. Still, they are valuable for debugging a missing sibling tool, so the length is justified.

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 list tool with an output schema, the description covers the important context: default listing behavior, state meanings, archived separation, and a conditional note about plan creation. It does not need to explain return values because an output schema exists. The pagination parameters are already visible in the schema. The description is complete enough for an agent to call this tool correctly in most scenarios.

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 already documents archived and id_organization with descriptions, leaving limit and offset only with type/min/max. The description reinforces archived behavior ('pass archived true for those') but adds little meaning for pagination parameters. Since schema coverage is only 50%, the description partially compensates but does not fully explain every parameter, so a baseline-adjacent score 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 opens with a specific verb and resource: 'The AI-generated publication plans of an organization, newest first.' It clearly identifies the object as AI-generated plans, distinguishes them from regular publications present in siblings, and provides an ordering guarantee. The states are also enumerated, leaving no ambiguity about what is listed.

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 context for the archived mode: 'Archived plans are a separate listing, never mixed in: pass archived true for those.' It also explains when create_ai_plan will be absent and instructs how to guide the user, which helps with tool selection. It does not explicitly name alternatives like get_ai_plan for retrieving a single plan, but the list-vs-get distinction is implied by the tool name.

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