Writes or replaces caption text for dataset files by mapping each file name to its caption, keeping LoRA training datasets accurately labeled.
Write captions. captions maps a file name (as shown by get_captions) to its caption text;
existing captions for those files are replaced.
| Name | Required | Description | Default |
|---|---|---|---|
| dataset | Yes | ||
| captions | Yes | ||
| caption_ext | No | txt |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety profile (readOnlyHint=false, destructiveHint=false), so the bar is lower, and the description still adds the key behavioral fact: existing captions for the named files are replaced. That overwrite semantics is precisely the kind of thing an agent needs and is not derivable from annotations. It stops short of saying whether unlisted files are left untouched or whether a partial map is atomic.
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?
Two short sentences, no filler, with the action first and the overwrite warning attached to the parameter it concerns. Nothing could be cut without losing meaning.
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?
An output schema exists so return values need no explanation, but with three undocumented parameters and a mutation that overwrites data, the description should say what `caption_ext` controls and what happens to files not listed in the map. Adequate but leaves the agent guessing on edge cases.
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 0%, so the description must carry the load, and it does well for `captions` by explaining the key/value meaning and cross-referencing get_captions' file names. `dataset` and especially `caption_ext` (default "txt") are left entirely unexplained, which is a real gap for a 3-parameter mutation.
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?
Specific verb+resource ("Write captions") and it immediately clarifies the shape of the write via the `captions` map keyed by file name. The get_captions back-reference makes the read/write pairing with its sibling clear without naming it explicitly as an alternative.
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?
Usage is only implied: the mention of `get_captions` suggests the read-then-write workflow, and "existing captions ... are replaced" hints at the risk of overwriting. There is no explicit statement of when to use this versus auto_caption_dataset, which is the obvious competing sibling for producing captions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.