list_prompts

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by stating the return type (paginated summary with specific fields: id, name, slug, model, status) and mentioning filters, which goes beyond 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 only two sentences long. It front-loads the main action and filters, then explains the output and usage. Every sentence contributes meaning, with no redundant or filler content.

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 output schema exists, the description does not need to detail return values. It adequately summarizes the output fields and connects to sibling tools. The annotations provide relevant metadata (read-only, idempotent, open-world). The description is complete for the tool's complexity.

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%, so the parameters are well-documented. The description adds context by grouping the optional filters (collection, workspace, search) and explaining the output's purpose (choosing a prompt_id). This provides additional meaning beyond the schema alone.

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 function: 'List prompts across the workspace' with optional filters. It distinguishes from siblings like 'get_prompt' by specifying that it returns a summary for selecting a prompt ID, and it mentions related tools (get_prompt, update_prompt, render_prompt).

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 this tool: to choose a prompt_id before calling get_prompt, update_prompt, or render_prompt. It also lists the available filters (collection, workspace, search). It does not explicitly state when not to use it, but the context is clear.

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