post_prompt_suggestion

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

Despite no annotations, the description fully discloses behavioral traits: it queues for review, requires reasoning, and differentiates behavior between gated and loop modes. This is comprehensive for a queueing operation, though it lacks details on error states or auth requirements.

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 concise with four sentences, front-loading the core purpose. Every sentence adds essential information, and there is no fluff. The structure is logical: purpose, reasoning requirement, mode-specific instructions.

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 no output schema and moderate complexity (two modes, queueing), the description covers the key behaviors and flow. It could mention what happens in gated mode if user rejects, but for an agent the provided information is sufficient to use the tool correctly.

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 75% (3 of 4 parameters have descriptions). The description adds value by specifying the expected structure of the 'reasoning' parameter (test cases, change, expectation). For other parameters, it doesn't add much beyond the schema, but the overall guidance compensates.

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 purpose: queueing a revised system prompt for user review. It uses a specific verb 'queue' and resource 'prompt', and distinguishes from siblings like 'apply_suggestion' and 'set_system_prompt' by mentioning the two operational modes.

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 explicit guidance on when to use it: in gated mode (start_optimization_session) vs. loop mode (loop_optimization, loop_regression). It also tells the agent to call 'apply_suggestion' immediately after in loop mode, and mandates reasoning structure, which helps the agent understand proper usage.

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