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Caption (any backend)

sdnext_caption_dispatch

Generate captions or tags from an image by choosing a caption backend—OpenCLIP, tagger, VLM, or analyze—returning a unified response tailored to your task.

Instructions

Unified caption dispatch (SD.Next /sdapi/v1/caption) — pick backend: "openclip" | "tagger" | "vlm" | "analyze". Returns a unified response (caption/tags/answer depending on backend).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo
imageYesBase64-encoded image (raw base64, data: URL, or "upload:<id>" ref).
modelNo
top_kNo
top_pNo
promptNo
systemNo
analyzeNo
backendYesCaption backend to use.
prefillNo
max_tagsNo
questionNoVLM task, e.g. "Short Caption", "Normal Caption", "Long Caption", "Use Prompt".
do_sampleNo
num_beamsNo
thresholdNo
blip_modelNo
clip_modelNo
max_tokensNo
sort_alphaNo
use_spacesNo
show_scoresNo
temperatureNo
exclude_tagsNo
keep_prefillNo
keep_thinkingNo
thinking_modeNo
include_ratingNo
escape_bracketsNo
include_annotatedNo
character_thresholdNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions that the response is 'unified' and depends on the backend, but says nothing about safety, side effects, prerequisites, or error conditions. This leaves significant ambiguity for an agent deciding whether to call this tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, consisting of two short sentences that convey the dispatch functionality, the list of backends, and the nature of the response. Every word adds value, and it is easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 30 parameters, no output schema, and no annotations, the description is severely under-specified. It explains the basic dispatch concept but fails to detail parameter usage, backend-specific behavior, or operational details, making it incomplete for an agent to use correctly in most scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 10% (3 of 30 parameters documented), and the description does not compensate. It merely restates the backend enum values already present in the schema and notes the response depends on the backend, without explaining any of the other 27 parameters that remain undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a 'unified caption dispatch' and lists the four backends ('openclip', 'tagger', 'vlm', 'analyze') and response types, making the tool's purpose immediately apparent. However, it does not explicitly contrast itself with sibling tools like sdnext_caption or sdnext_tagger, so it does not earn a 5 for sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'pick backend' implies when to use this tool (when you want to select a specific captioning backend), but there is no explicit guidance on when to use this dispatcher versus the individual sibling captioning tools, nor any when-not-to-use conditions or alternative recommendations.

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

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