generate_caption

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

Despite having no annotations, the description discloses an important behavioral detail: the tool costs 1 AI credit. It also sets expectations that output is tone-aware and produced by AI, which adds useful information beyond a generic tool name.

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 compact and front-loaded: it states the main function first, then optional inputs, then cost. There is no wasted phrasing or redundant repetition of schema details.

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?

The description is adequate for a simple generative tool with all optional parameters, and the credit cost is clearly noted. Gaps remain around char_limit and workspace_id semantics, expected output shape, and how it differs from the similar sibling rewrite_for_platforms.

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 description maps current_caption to draft text and platforms to target platforms, which adds intent beyond the raw schema. However, it does not explain char_limit or workspace_id, and schema description coverage is 0%, so the description only partially compensates for undocumented parameters.

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 verb and resource: generate or improve a social media caption with AI. It is easy to identify the tool's main purpose, though it does not explicitly distinguish itself from the sibling tool rewrite_for_platforms.

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 usage context: use this when you need an AI caption generated or improved, optionally passing draft text and target platforms for tone-aware output. It does not mention exclusions or alternative tools, but the primary use case is clear.

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