Skip to main content
Skills are reusable capabilities for AI agents. Install them with a single command to enhance your agent with access to procedural knowledge — in this case, everything about FLUX prompting and API integration. When you install BFL Skills, your AI coding assistant (Claude Code, Cursor, Windsurf, or any compatible tool) gains expert-level knowledge of FLUX. It knows how to write effective prompts, which model to use for each task, and how to integrate the API properly.

​
Installation

/plugin marketplace add black-forest-labs/bfl_skills
/plugin install flux-best-practices@bfl-skills

​
What Your Agent Learns

​
flux-best-practices

Prompting knowledge for all FLUX models:
  • Prompt structure — The formula that works: [Subject] + [Action] + [Style] + [Context] + [Lighting] + [Technical]
  • No negative prompts — FLUX doesn’t support them. Describe what you want, not what you don’t.
  • Lighting vocabulary — Golden hour, softbox, rim light, Rembrandt, volumetric fog, and more
  • Hex colors — Precise color control with #RRGGBB format
  • Typography — How to render text in images using quoted strings
  • Model selection — When to use FLUX.2 [klein] vs [max] vs [pro], when to use Kontext, etc.

​
bfl-api

API integration patterns:
  • Async polling — Use the polling_url from responses, implement exponential backoff
  • Rate limits — 24 concurrent requests (6 for Kontext Max), how to handle 429s
  • URL expiration — Download images within 10 minutes
  • Regional endpoints — api.eu.bfl.ai for GDPR, api.us.bfl.ai for US data residency
  • Webhooks — Production webhook setup and verification

​
Example: Before and After

Without skills, your agent might generate this prompt: 
a cat sitting
With BFL Skills, your agent writes prompts like this: 
A fluffy orange tabby cat with bright green eyes sitting regally on a vintage
velvet armchair, afternoon sunlight streaming through lace curtains creating
warm golden hour lighting, shallow depth of field with soft bokeh background,
shot on medium format camera
And when writing integration code, it knows to: 
# Use the polling_url (don't construct URLs manually)
polling_url = response.json()["polling_url"]

# Poll with exponential backoff
delay = 1
while True:
    result = requests.get(polling_url, headers={"x-key": API_KEY}).json()
    if result["status"] == "completed":
        # Download immediately — URL expires in 10 min
        image_url = result["result"]["url"]
        break
    time.sleep(delay)
    delay = min(delay * 2, 30)

​
Using with MCP

Skills and MCP serve different purposes:
SkillsMCP
What it doesTeaches your agent FLUX knowledgeLets your agent generate images directly
Use caseWriting code that uses FLUXGenerating images in conversation
You can use both together. MCP for direct image generation in Claude, Skills for writing FLUX integrations in your codebase.

​
Updating

npx skills update black-forest-labs/bfl_skills

​
Resources