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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral context beyond that: results are limited to 3, they are the most recent drafts, and they include author info and LinkedIn extension data. This gives the agent a clear expectation of the tool's output and scope without contradicting the annotations.

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 three sentences with no filler. It front-loads the core purpose and scope, then briefly describes the result shape, then gives a concise downstream workflow. Every sentence earns its place.

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 simple read-only listing tool with one optional parameter and no output schema, the description is complete: it explains what is listed, the cap of 3 results, what data is included, and what to do next. Annotations already cover the safety profile, so nothing critical is missing.

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 100%, with a single optional workspaceId that already has a clear description ('Defaults to the API key's workspace'). The tool description mentions 'for a workspace' but adds no new parameter-level semantics; the schema carries the full burden, so the baseline score 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 clearly states a specific verb and resource: 'List the latest AI-generated content post suggestions (draft posts tagged 'ai-generated') for a workspace.' It distinguishes this tool from generic content listing tools by emphasizing AI-generated drafts, the 'up to 3 most recent' limit, and the author/LinkedIn extension data returned.

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 provides clear context: it is the entry point for AI-generated suggestions, followed by edit, schedule, or submit-for-approval actions. It names the immediate downstream tools (campaignstack_update_content_post, campaignstack_schedule_content_post, campaignstack_submit_content_for_approval), but it does not explicitly contrast with sibling list tools like campaignstack_list_content_posts.

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