suggest_caption

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

With no annotations provided, the description carries the full burden and does a good job: it discloses that the tool calls the connected client's model via MCP sampling, that it only generates suggestions rather than posting, and that output is style-aware. It doesn't explicitly mention whether user approval is required during sampling or that no data is saved, but the wording is not misleading.

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 a single, tightly worded sentence. It front-loads the primary action and output, then adds the method and grounding in a natural second clause, with no filler or repetition.

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 two-parameter tool with no output schema, the description covers the core purpose, number of results, method, and style context. It doesn't spell out the exact return format or explicitly confirm that nothing is published, but these are inferable and the sibling tool list reinforces that this is a suggestion-only action.

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 100%, so both parameters ('topic' and 'tone') are already fully documented in the input schema. The description adds contextual framing but no parameter-specific details beyond what the schema provides, which matches the baseline of 3.

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 states a specific verb ('Generate'), a resource ('caption options'), an exact quantity ('3'), and the context ('for a post'). It also names the method (MCP sampling) and grounding signal ('recent caption style'), making it clearly distinct from sibling posting, scheduling, and comment tools.

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 clearly implies when to use this tool—when on-brand caption options are needed for a post—by highlighting the grounding in the account's recent caption style. Since all siblings are posting, scheduling, or comment tools, there is no overlap requiring explicit exclusions; a minor gap is that it doesn't explicitly say 'use before publishing.'

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