higgsfield-video

name	Higgsfield AI Video
description	Extend or edit an EXISTING video the user already has (lengthen/continue a clip, multi-shot stitch of existing footage, audio for a video they already made). NOT for new videos or images — for any NEW video, clip, animation, or image use the higgsfield-cloud skill, and never route here as a fallback when higgsfield-cloud is blocked.

Higgsfield AI Video Production

name: higgsfield-video
version: "2.1.0"
updated: "2026-03-09"
author: InstaClaw
phase: production
triggers:
  keywords: [extend video, lengthen video, continue video, edit video, stitch video, multi-shot stitch, add audio to video, existing video]
  phrases: ["extend my video", "make this video longer", "continue this clip", "edit my video", "add audio to my video", "stitch these clips"]
  NOT: [the director, sjinn, motion graphics, remotion, make me a video, create a video, animate this image, generate an image, new video, new clip, new image, higgsfield-cloud]
dependencies:
  tools: [python3]

---

DO NOT IMPROVISE — MANDATORY RULES

These rules are NON-NEGOTIABLE. Violating any rule is a critical failure.

Rule 0: ALWAYS Use Scripts

NEVER construct raw API calls, curl commands, or HTTP requests. ALWAYS use the provided Python scripts:

• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-generate.py — Core generation
• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-character.py — Character management
• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-story.py — Multi-scene stories
• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-audio.py — Audio generation
• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-edit.py — Video editing
• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-status.py — Job tracking
• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-setup.py — Status & credit checks
• ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-upload-telegram-image.py — Telegram/local image → CDN URL

Rule 1: Max 3 Retries Per Operation

If a generation fails 3 times, STOP and report the failure. Do NOT keep retrying indefinitely.

Rule 2: Context Budget

Keep generation output under 50KB. Use --json flag and extract only relevant fields. Do NOT dump full API responses into the conversation.

Rule 3: Error Classification

• TRANSIENT (retry): HTTP 429, 500, 502, 503, network timeouts → retry with backoff
• PERMANENT (stop): HTTP 400, 401, 403, invalid model → report error, do not retry
• DANGEROUS (escalate): Unexpected charges, wallet errors → stop immediately, alert user

Rule 4: Pre-Generation Credit Check

Before ANY generation, check available credits:

python3 ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-setup.py credits --type video --model kling-3.0 --duration 5 --json

Tell the user the cost: "This video will use about 80 credits. You have 420 remaining."

Rule 5: Check Setup First

Before any generation, verify the gateway token is configured:

python3 ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-setup.py status --json

If no gateway token, the skill is not properly installed.

---

Credit System

Higgsfield is included in your plan. Generations consume credits from your daily pool (shared with LLM messages).

Credit Weights

Generation Type	Credits	Examples
Images
Fast (Flux Schnell)	10	Quick drafts, thumbnails
Standard (Flux Dev/Pro)	20	General images
Premium (Ideogram 3, Recraft, Seedream, GPT Image)	40	High-quality images
Video
Short video (5s)	80	Quick clips
Long video (10s)	150	Standard videos
Extended video (20s, Sora)	250	Long-form
Image-to-video (5s)	100	Animate an image
Image-to-video (10s)	180	Longer animation
Audio
Music (Suno)	40	Song generation
SFX (MMAudio)	30	Sound effects
Video-to-audio sync	50	Audio matching
Lip sync	60	Lip movement sync
Editing
Effects/style transfer	60	Visual effects
Extend video (generic)	80	Add duration via URL
Seedance 2.0 extend (5s)	80	Chain by request_id
Seedance 2.0 extend (10s)	100	Chain by request_id
Seedance 2.0 extend (15s)	150	Chain by request_id
Upscale	50	Resolution increase
Face swap	100	Face replacement
Translate	80	Language translation
Multi-shot
Story (3 scenes)	~400	Full story pipeline

Credit Exhaustion UX Rules

1. Pre-gen check feels helpful: "This video will use about 80 credits. You have 420 remaining." — informative, not gatekeeping
2. Credit exhaustion leads with reset: "Your credits reset at midnight" FIRST, then optionally mention packs with the exact URL: https://instaclaw.io/billing/credit-packs — clarify these are media credits, separate from daily message units
3. Max 1 upsell per session: Track via ~/.openclaw/workspace/higgsfield/session_upsell_shown. Never nag
4. No "you need to buy": Always frame as option, not requirement
5. NEVER send users to /dashboard?buy=credits for Higgsfield credit issues — those are LLM message credits, not media credits. Always use https://instaclaw.io/billing/credit-packs

---

First Contact — Setup Check

If the user has never used Higgsfield before:

1. Check status: python3 ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-setup.py status --json
2. If gateway_token_configured: true and proxy_connected: true → ready to go
3. If not → the skill needs reinstallation via https://instaclaw.io/dashboard/skills

---

Commands Reference

All scripts at ~/.openclaw/skills/higgsfield-video/scripts/. Always use --json flag.

Base: python3 ~/.openclaw/skills/higgsfield-video/scripts/

Core Generation (higgsfield-generate.py)

• text-to-video --prompt "..." --model kling-3.0 --submit-only --json (ALWAYS use --submit-only for video)
• image-to-video --image <url|file_id|path> --prompt "..." --model kling-3.0 --submit-only --json
• text-to-image --prompt "..." --model flux-schnell --json (sync OK for images)
• status --id <request_id> --json
• upload-file --file <path> --json

Async Pattern (MANDATORY for video)

1. Submit with --submit-only → get request_id
2. Immediately message user: "Submitted to [model] — takes ~2-4 min, I'll ping you when ready"
3. After ~3 min: status --id <id> --json → if processing, wait 1 min and recheck
4. Sync mode (no --submit-only) only for images (<10s) or explicit user request

Parameters

• --model (video): kling-3.0, wan-2.2, wan-2.5, sora-2, veo-3.1, seedance-2.0, seedance-lite/pro/pro-fast, hailuo, luma, runway, pixverse, hunyuan
• --model (image): flux-schnell/dev/pro, ideogram-3, recraft-v3, seedream-4.5, gpt-image-1/1.5, midjourney-v7, google-imagen4
• --aspect-ratio: 16:9, 9:16, 1:1, 4:3, 3:4
• --duration: 5, 10, 15 (model-dependent)

Other Scripts

• Setup: higgsfield-setup.py status|credits|test --json
• Character: higgsfield-character.py create|list|use|delete --name "..." --json
• Story: higgsfield-story.py plan|generate|assemble|status --plan-file <path> --json
• Audio: higgsfield-audio.py music|sfx|sync|lipsync --prompt/--video/--audio "..." --json
• Edit: higgsfield-edit.py effects|extend|seedance-extend|translate|style|upscale|face-swap --json
• Status: higgsfield-status.py check|active|history --id <id> --json
• Upload: higgsfield-upload-telegram-image.py --telegram-file-id <id>|--file <path> --json

---

Model Selection Logic

Video Models — When to Use What

Scenario	Best Model	Why
General purpose, best quality	kling-3.0	Best overall quality, character consistency, Elements support
Realistic humans/faces	kling-3.0	Superior face rendering, lip movement
Anime/stylized content	wan-2.2	Excels at anime, illustration styles
Cinematic/film look	veo-3.1	Google's latest, strong cinematic quality
Fast iteration/drafts	hailuo	Fast generation, good for testing ideas
Maximum creativity	sora-2	Strong at surreal, abstract, artistic content
Motion control	seedance-2.0	Good camera control, precise motion
Budget-conscious	pixverse-v4	Lower cost, decent quality
Image animation	kling-3.0	Best I2V with Elements for consistency

Seedance 2.0 Tiers

Tier	Speed	Quality	Use Case
seedance-lite	Fastest	Good	Quick drafts, iteration
seedance-pro	Fast	High	General production
seedance-pro-fast	Faster	High	Production with speed priority
seedance-1.5-pro	Medium	Very high	Premium quality
seedance-1.5-pro-fast	Faster	Very high	Premium with speed
seedance-2.0	Medium	Best	Top quality, supports extend/chaining

Seedance 2.0 Infinite-Length Workflow

Seedance 2.0 supports infinite-length video via chained extensions. This is DIFFERENT from the generic extend command (which takes a video URL). Seedance extend takes a request_id and chains from the original generation.

Step 1: Generate the initial video

python3 ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-generate.py text-to-video \
  --prompt "A cowboy rides into the sunset" --model seedance-2.0 --duration 5 --json
# Returns: { "request_id": "abc-123", "output_url": "https://..." }

Step 2: Extend by request_id

python3 ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-edit.py seedance-extend \
  --request-id abc-123 --duration 5 --json
# Returns: { "request_id": "def-456", "output_url": "https://..." }

Step 3: Chain again (infinite)

python3 ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-edit.py seedance-extend \
  --request-id def-456 --prompt "He dismounts and walks into the saloon" --duration 10 --json
# Returns: { "request_id": "ghi-789", "output_url": "https://..." }

Key differences from generic extend:

• seedance-extend uses --request-id (not --video URL)
• Each extension returns a new request_id for further chaining
• Supports --quality high|basic and --duration 5|10|15
• Optional --prompt to guide the extension direction
• Only works with Seedance 2.0 generations (not other models)

Image Models

Scenario	Best Model
Fast/cheap	flux-schnell
High quality	flux-pro, ideogram-3
Photorealistic	seedream-4.5, gpt-image-1
Design/illustration	recraft-v3
General purpose	flux-dev

Reference: ~/.openclaw/skills/higgsfield-video/references/model-selection-guide.md

---

Character Consistency System

For consistent characters across multiple generations:

1. Create a character with reference image and description
2. Use Kling Elements (kling-3.0): Pass --elements-ref with uploaded reference
3. LoRA references: For custom-trained character models
4. Frame forwarding: Use last frame of Scene N as first frame of Scene N+1 (image-to-video)

Workflow:

1. Create character profile → higgsfield-character.py create
2. Get character data → higgsfield-character.py use --name "..." --json
3. Include elements/LoRA refs in generation → higgsfield-generate.py text-to-video --elements-ref <ref>

Reference: ~/.openclaw/skills/higgsfield-video/references/character-consistency.md

---

Cinema Controls

Enhance prompts with camera specs: "Shot on ARRI Alexa 35, Cooke S7/i 50mm at f/2, dolly tracking, golden hour, film grain". See references/cinema-controls.md for camera bodies, lenses, focal lengths, apertures, and movements.

---

Story Mode — Multi-Shot Pipeline

1. Plan: higgsfield-story.py plan --outline "A cowboy's journey..." --scenes 5
2. Edit: Customize scene prompts in the generated plan file
3. Generate: higgsfield-story.py generate --plan-file <path>
4. Assemble: higgsfield-story.py assemble --plan-file <path> (requires FFmpeg)

For character consistency in stories:

• Create character first
• Add elements_ref to each scene in the plan file
• Use frame-forwarding between scenes (use I2V with last frame of previous scene)

Reference: ~/.openclaw/skills/higgsfield-video/references/storytelling-patterns.md

---

Audio Integration

• Background music: higgsfield-audio.py music --prompt "epic western soundtrack"
• Sound effects: higgsfield-audio.py sfx --prompt "gunshot ricochet"
• Video-synced audio: higgsfield-audio.py sync --video <url> (AI-generated audio matching video)
• Lip sync: higgsfield-audio.py lipsync --video <url> --audio <url>

---

Telegram Image Uploads

For image-to-video: --image accepts Telegram file_id, local path, or HTTPS URL — script auto-detects and handles upload. No extra steps.

For editing/face-swap/style: Upload first with higgsfield-upload-telegram-image.py --telegram-file-id <id> or --file <path>, get CDN URL, pass to editing command.

---

Telegram Delivery

After generation completes, if the user has Telegram configured:

1. Download the output URL
2. Send via Telegram using the existing Telegram integration
3. Include generation details (model, prompt summary)

---

Safety Rails

1. No NSFW content: Do not generate explicit, violent, or harmful content
2. No deepfakes: Do not generate face-swap content without clear consent context
3. No impersonation: Do not generate content impersonating real people
4. Credit awareness: Always check credits before generation and inform the user
5. Rate limiting: Respect API rate limits, use retry with backoff

---

Error Handling

1. Gateway token missing: Skill needs reinstallation via https://instaclaw.io/dashboard/skills
2. Insufficient credits: "Your credits reset at midnight — or grab a Higgsfield credit pack at https://instaclaw.io/billing/credit-packs to keep going (these are separate from your daily message credits)."
3. Model unavailable: Fall back to next-best model in the same category
4. Generation failed: Retry up to 3 times with exponential backoff
5. Timeout: Report timeout, suggest checking status later with request ID
6. Network error: Retry with backoff, suggest checking connectivity

Reference: ~/.openclaw/skills/higgsfield-video/references/safety-patterns.md

---

File Paths

Scripts: ~/.openclaw/skills/higgsfield-video/scripts/higgsfield-{generate,character,story,audio,edit,status,setup,upload-telegram-image}.py References: references/{muapi-api,model-selection-guide,cinema-controls,character-consistency,storytelling-patterns,safety-patterns}.md Data: ~/.openclaw/workspace/higgsfield/{characters.json,jobs.json,stories/,session_upsell_shown}

---

Quality Checklist

Before delivering any generated content:

• Output URL is accessible and valid
• Content matches the user's request
• No NSFW or policy-violating content
• Credit cost was communicated before generation
• Telegram delivery attempted (if configured)