Skip to main content
Glama

Control-guided Generation

sdnext_control

Generate images with control-guided pipelines using ControlNet, T2I-Adapter, or IP-Adapter units. Returns generated images and preprocessor output maps for precise structural or style control.

Instructions

Run the control-guided pipeline (SD.Next /sdapi/v1/control) with one or more control units (controlnet / t2i adapter / xs / lite / reference / ip). Returns generated images plus preprocessor output maps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xyzNo
faceNo
seedNoRandom seed (-1 = random).
stepsNoSampling steps.
widthNoImage width in pixels.
heightNoImage height in pixels.
n_iterNoNumber of iterations (batches).
promptYesPositive prompt. Supports <wildcards> and [style:name] syntax.
stylesNoStyle names to apply (from sdnext_list_styles).
tilingNoUse VAE tiling (saves VRAM, may degrade quality).
cfg_endNoLegacy CFG end step fraction.
subseedNoSecondary seed (-1 = random).
cfg_trueNoTrue CFG scale (SD3/Flux style).
hr_scaleNoHigh-res fix scale factor.
save_dirNo
vae_typeNoVAE type: "Full" or "Tiled".
cfg_scaleNoLegacy CFG scale (guidance_scale when guidance_name=CFG).
clip_skipNoCLIP skip value.
enable_hrNoEnable high-res fix (two-pass generation).
unit_typeNoRequest-level default unit type.
batch_sizeNoNumber of images per iteration.
ip_adapterNo
cfg_rescaleNoLegacy CFG rescale.
hr_resize_xNoHigh-res fix target width.
hr_resize_yNoHigh-res fix target height.
hr_upscalerNoUpscaler for high-res fix.
save_imagesNoSave images to disk.
script_argsNoScript arguments, positional order matching script args.
script_nameNoScript to run (from sdnext_list_scripts).
send_imagesNoReturn base64 images in response (default true).
cfg_adaptiveNoAdaptive CFG (0-1).
sampler_nameNoSampler name (from sdnext_list_samplers), e.g. "euler_a", "dpmpp_2m_sde".
control_unitsYesControl units (see sdnext_txt2img control_units).
guidance_nameNoModular guidance type (e.g. "Default", "CFGZero", "APG").
guidance_stopNoGuidance stop step fraction (0-1).
guidance_scaleNoModular guidance scale (new SD.Next guidance system).
guidance_startNoGuidance start step fraction (0-1).
hr_sampler_nameNoSampler for high-res fix ("Same as primary" by default).
negative_promptNoNegative prompt.
alwayson_scriptsNoAlways-on script args keyed by script name.
do_not_save_gridNoDo not save grid image.
guidance_rescaleNoGuidance rescale (0-1).
subseed_strengthNoHow much to use the subseed (0-1).
seed_resize_from_hNoResize from height for seed adjustment (-1 = disabled).
seed_resize_from_wNoResize from width for seed adjustment (-1 = disabled).
do_not_save_samplesNoDo not save samples to disk.
sd_model_checkpointNoCheckpoint model name or filename to use (from sdnext_list_checkpoints).
hr_second_pass_stepsNoSteps for second pass (0 = full steps).
hr_denoising_strengthNoHigh-res fix denoising strength (0-1).
Behavior2/5

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

No annotations are present, so the description bears the full transparency burden. It discloses that the tool returns images and preprocessor maps, but gives no context about compute costs, whether images are saved to disk despite the save_images flag, or potential side effects. One sentence is too thin for a generation endpoint with 49 parameters.

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 a single front-loaded sentence that states the action, endpoint, key requirement, and return value with no wasted words.

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 49-parameter tool with no output schema and no annotations, the description is not contextually complete: it omits usage guidance relative to sdnext_txt2img, any explanation of control_units structure (despite that being the required nested object), and default behaviors (e.g. whether images are returned/saved). The rich schema descriptions mitigate but do not replace missing high-level context.

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

Parameters4/5

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

Schema coverage is high (92%), so the baseline is 3; the description adds real value by enumerating what kinds of control units are supported (controlnet / t2i adapter / xs / lite / reference / ip), which the control_units schema entry only crosses-references. However, it adds no semantics for the remaining 48 parameters.

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

Purpose5/5

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

The description opens with an action verb ('Run'), identifies the exact endpoint (/sdapi/v1/control), names the key input concept (control units), lists supported types, and states expected outputs. This clearly differentiates it from sibling tools like sdnext_txt2img and sdnext_img2img.

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 'with one or more control units' and the listed types imply this is the tool to use for ControlNet/adapter-guided generation, but it never explicitly contrasts it with sdnext_txt2img, explains prerequisites, or says when not to use it. No alternative tools are named.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Congenital/sdnext_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server