Suggest prompt candidates for any topic

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

No annotations are provided, so the description carries the full burden and does so richly: it discloses the cost model (≈1 design + 1 LangGPT + 1 preview call per candidate, ≈6 calls for 4 candidates), that live previews are produced by the real model on the sample message, and that previews can be turned off. This is exactly the kind of operational context an agent needs before calling.

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 imperative 'START HERE' is front-loaded and every sentence carries information (candidate types, what each includes, cost). It is dense and slightly long, but there is little redundant filler; the cost and routing details earn their space.

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?

With no output schema, the description must explain the return shape, and it does: each candidate carries when-to-use, expected effect, and a live sample reply, and the agent is told to present them as a numbered menu. Combined with cost disclosure, an agent has everything needed to call and use this correctly despite the 8-parameter surface.

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 63%, so the schema documents most parameters, but the description adds meaning beyond it: '2-4 candidates' maps to count, 'previews can be turned off' maps to preview, and 'live sample reply ... on the same first message' explains sampleInput. It does not clarify language, strategy, or previewChars, leaving modest gaps.

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?

States a precise verb and output (returns 2-4 genuinely different ready-to-use prompt candidates) and frames itself as the entry point ('START HERE for any new topic'), which distinguishes it from siblings that optimize or evaluate an already-chosen prompt. An agent can tell immediately what it produces without opening the schema.

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?

Explicitly tells when to use it ('START HERE for any new topic') and names the follow-on tools (optimize_prompt_via_api / auto_optimize_prompt / evaluate_prompt_preview) to invoke on the chosen candidate, plus instructs the agent to present a numbered menu and let the user pick. This is actionable routing, not vague guidance.

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