Use AgenticFlow's built-in features and account credits first — before adding external API keys (BYOK). Use this skill whenever the user asks about image generation without API keys, wants to use their existing credits, asks about built-in vs BYOK, or mentions agenticflow_generate_image, web_search, web_retrieval, or credit-efficient workflows. BYOK is only for extension when unsatisfied or explicitly requested.
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
Use AgenticFlow's built-in features and account credits first — before adding external API keys (BYOK). Use this skill whenever the user asks about image generation without API keys, wants to use their existing credits, asks about built-in vs BYOK, or mentions agenticflow_generate_image, web_search, web_retrieval, or credit-efficient workflows. BYOK is only for extension when unsatisfied or explicitly requested.
compatibility
Claude Code, Claude Desktop, Codex, Cursor, Gemini CLI
Primary Philosophy: Use your existing account credits with built-in features Extension Path: BYOK (Bring Your Own Key) only if unsatisfied or explicitly requested Goal: Spend your available credits first, upgrade only when needed
When NOT to use this skill
If the user explicitly wants to use external API keys (BYOK) like DALL-E, Stable Diffusion, or OpenAI, use agenticflow-mcp skill instead. If they need specific model recommendations or want to compare available models, use agenticflow-llm-models skill. This skill is for users who want to maximize their existing account credits first.
Orient first
af bootstrap --json
From the response, extract:
auth.workspace_id — your workspace identifier
models[] — available models that consume credits (source of truth, don't hardcode)
agents[] — existing agents to avoid duplication
_links.workspace — surface this URL to the user right away: "Your workspace is at <_links.workspace> — open it anytime to see what I'm building."
If data_fresh: false in the response, the backend is degraded — do not mutate. Fix auth/network before proceeding.
Primary Philosophy: Credits-First
DEFAULT: Use Your Existing Credits
When using this skill, the DEFAULT approach is:
Start with a blueprint — af agent init --blueprint <id> (never create from scratch if a blueprint exists)
Use built-in nodes that consume your existing account credits
Blueprint first, custom agent second. If the user needs image generation, use af agent init --blueprint content-creator. If they need research, use af agent init --blueprint research-assistant. Only create a custom agent with af agent create --body '...' if no blueprint fits the use case.
EXTENSION: BYOK Only When Needed
Only consider BYOK (external API keys) if:
You're NOT satisfied with built-in results
User explicitly requests specific providers (DALL-E, SD, etc.)
You need to extend beyond built-in capabilities
TL;DR — Built-In First, Extend Later
Phase 1: Use These (Your Existing Credits)
Node Type
Category
Typical Credits/Run
Status
agenticflow_generate_image
Image
10-30
PRIMARY - Use this first
llm / pml_llm
Text
1-40
Built-in, use freely
web_search
Research
1-5
Built-in, use freely
web_retrieval
Research
1-5
Built-in, use freely
Phase 2: Extension (Only If Unsatisfied)
Node Type
Why Extend
Requires
generate_image + DALL-E
Better photorealism
BYOK - OpenAI API key
generate_image + Stable Diffusion
More artistic control
BYOK - SD API key
openai_* nodes
Specific OpenAI features
BYOK - OpenAI API key
The Decision Framework (Inspect Before Extend)
The Golden Rule: Never jump to BYOK as the first option. Always try built-in first.
BEFORE Using Any External API Key, Ask:
1. Did I try the built-in version first? (agenticflow_generate_image)
└─ If NO → Use built-in first
2. Am I satisfied with the built-in results?
└─ If YES → Stick with built-in, save external costs
3. Does the user EXPLICITLY request a specific provider?
└─ If NO → Stay with built-in
4. Is the unsatisfactory result a blocker?
└─ If NO → Accept and iterate with prompts
└─ If YES → Consider BYOK extension
Verified Built-In Features (Use Your Credits)
Rung 0-2: Workflow Blueprints (Start Here)
# DEFAULT: These use YOUR credits only, no setup needed
af workflow init --blueprint llm-hello --json # ~1-5 credits
af workflow init --blueprint llm-chain --json # ~2-10 credits
af workflow init --blueprint summarize-url --json # ~3-15 credits
af workflow init --blueprint api-summary --json # ~3-15 credits
Rung 3: Agent Blueprints (Credits-First)
When a user needs image generation or research, always prefer blueprints over custom agents. Blueprints are pre-configured with the right built-in nodes.
# DEFAULT: These agents use YOUR existing credits
af agent init --blueprint research-assistant --json # web_search, web_retrieval
af agent init --blueprint content-creator --json # agenticflow_generate_image
af agent init --blueprint api-helper --json # api_call, string_to_json
Only create custom agents if no blueprint fits the user's use case.
Always preview with --dry-run first:
af agent init --blueprint content-creator --dry-run --json
af agent init --blueprint content-creator --json
Rung 6: Workforce Blueprints (Credits-First)
# DEFAULT: Multi-agent using YOUR credits only
af workforce init --blueprint research-pair --json # web_search + web_retrieval
af workforce init --blueprint content-duo --json # verify: uses YOUR credits
af workforce init --blueprint api-pipeline --json # api_call
af workforce init --blueprint fact-check-loop --json # web_retrieval
af workforce init --blueprint parallel-research --json # web_search
Extension Path: When to Consider BYOK
Scenario 1: User Explicitly Requests
User says:"I want this specific image from DALL-E 3"
Action:
# User explicitly requested DALL-E# → Load agenticflow-mcp skill for BYOK connection setup# → Go to UI → Connections → Add OpenAI API key# → Use generate_image with provider=dall-e
When the user needs BYOK, load the agenticflow-mcp skill for detailed connection setup instructions.
Scenario 2: Unsatisfactory Results
After 3 iterations with built-in:"Image quality isn't good enough for this use case"
Action:
# Try improving prompts first# If still unsatisfied → Load agenticflow-mcp skill for BYOK upgrade
Scenario 3: Feature Not Available Built-In
Need:"GPT-4 vision analysis" (not available in built-in)
Action:
# Feature genuinely requires external provider# → Add API key for that specific feature only
Managing Your Credit Spending
Credit-Efficient Workflow (Credits-First)
Step 1: Low-cost validation
# Use cheap LLM to validate concept
af workflow init --blueprint llm-hello --json
# ~1-5 credits to test the idea
Step 2: Built-in generation
# Use agenticflow_generate_image for actual output
af agent run --agent-id <content-creator> --message "Create image..."# ~10-30 credits
Step 3: Evaluate results
Satisfied? → Done! Stick with built-in.
Not satisfied? → Ask: iterate prompts OR extend to BYOK?
Step 4: Extension (only if justified)
# Only if built-in truly insufficient# Add connection in UI, use external provider# Factor in external API costs + AgenticFlow credits
Cost Comparison Example
Approach
Image Cost
External Cost
Total
Built-in (agenticflow)
20 credits
$0
Just credits
BYOK (DALL-E)
20 credits
~$0.02-0.04
Credits + API cost
BYOK (SD API)
20 credits
~$0.01-0.02
Credits + API cost
Recommendation: Only pay extra if built-in truly insufficient.
Prompt Engineering Before BYOK
Try These Before Upgrading
Built-in image quality not good?
# Try better prompts first:
"High resolution, detailed, professional photography style,
8k, sharp focus, studio lighting..."
# Try different aspect ratios
# Try negative prompts
# Try multiple generations and pick best
Still not satisfied after 3-5 prompt iterations?
→ Then consider BYOK extension.
The ANTI-Patterns (Don't Do This)
Wrong Approach
User: "I need an image"
→ Immediately: "Let me set up DALL-E API key"
Correct Approach
User: "I need an image"
→ "I'll use your existing credits with built-in generation first.
If you're not satisfied with results, we can upgrade to DALL-E."
→ Generate with agenticflow_generate_image
→ Evaluate: Satisfied? Done. Not satisfied? Discuss extension.
Verifying Credits-Only Operation
Confirm You're Using Built-In
# Check workflow nodes (should be agenticflow_* or built-ins)
af workflow get --workflow-id <id> --json | jq '.nodes[].type'# SAFE types (your credits only):# agenticflow_generate_image# llm, pml_llm# web_search, web_retrieval# EXTENSION types (verify before using):# generate_image (check provider setting)# openai_generate_image (BYOK required)
Check Before Creating
# ALWAYS inspect before deploying
af schema agent --field mcp_clients --json
af agent init --blueprint <id> --dry-run --json
Smoke Test After Deploy
# Verify built-in features work with your credits
af agent run --agent-id <id> --message "Generate a simple test image" --json
# Expect: status "completed" and actual credit consumption (not external API call)
Cleanup
Resources consume credits while running. Delete test deploys:
af agent delete --agent-id <id> --json
af workforce delete --workforce-id <id> --json
Both return {"schema":"agenticflow.delete.v1","deleted":true,"id":"...","resource":"..."} on success.
Summary: The Credits-First Checklist
When user asks for anything:
Try built-in first (agenticflow_generate_image, llm, web_search)
Use YOUR existing credits (check af bootstrap --json)
Iterate with prompts before considering alternatives
Evaluate satisfaction after built-in results
Only if unsatisfied OR explicit request → Discuss BYOK extension
Never default to BYOK as first option
Quick Reference: Default vs Extension
Request
DEFAULT (Credits-First)
Extension (BYOK)
"Generate image"
agenticflow_generate_image
Only if unsatisfied → DALL-E/SD
"Write blog post"
llm node
Only if need GPT-4 specifically
"Research topic"
web_search + web_retrieval
Only if need specific APIs
"Create video"
create_video (verify)
Only if need advanced editing
"Any task"
Built-in blueprints
Only for specific provider features
Related Skills
Load This Skill
When You Need
agenticflow-agent (official)
Single agent operations
agenticflow-workforce (official)
Multi-agent orchestration
agenticflow-mcp (official)
Extension: External connections
agenticflow-llm-models
Model selection and comparison
THIS SKILL
Credits-first philosophy
Flow: This skill → Try built-in → (if unsatisfied) → agenticflow-mcp for BYOK setup
On errors
Every API error returns a consistent envelope with an actionable hint:
