osidemedia/higgsfield-assist
> Use when the user asks about Higgsfield Assist (the built-in GPT-5 copilot), how to use the platform's native AI assistant, credit optimization strategies, plan selection, how to get more from fewer credits, or platform efficiency tips.
npx skills add https://github.com/OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-assist
Location: higgsfield.ai/chat
Higgsfield Assist is a GPT-5 powered creative copilot built directly into the platform.
It's separate from Claude — it lives inside Higgsfield's interface and is trained specifically
on Higgsfield's tools, workflows, and generation patterns.
| Use Assist for | Use this Claude skill for |
|----------------|--------------------------|
| Quick prompt generation within the platform | Building complex multi-shot workflows |
| Platform navigation questions | Structuring long-form projects |
| Viral/trend suggestions (platform-current) | Systematic MCSLA prompt construction |
| Real-time platform feature questions | Genre recipe templates and troubleshooting |
| Rapid iteration inside the Higgsfield UI | Understanding the underlying principles |
Best workflow: Use this Claude skill to plan and structure → use Higgsfield Assist
for final in-platform prompt refinement and quick generation.
| Plan | Monthly credits | Cost | Best for |
|------|----------------|------|----------|
| Free | 25 | $0 | Testing only |
| Basic | 150 | $6/mo (annual) | Hobby / light use |
| Pro | 700 | $27/mo (annual) | Regular creators |
| Ultimate | 1,500 | $55/mo (annual) | Daily production |
Commercial rights: Basic and above.
Watermarks: Free tier only.
Priority processing: Pro and above.
> Plan names, prices, and credit allowances above are hand-maintained and not
> verifiable from the API catalog (last reviewed 2026-07-06, not re-verified
> against the live UI) — check higgsfield.ai/pricing before quoting them.
*Model roster reviewed against the 2026-07-05 catalog snapshot; tier placements are hand-maintained — verify live before quoting.*
Low cost: Seedance 2.0 Fast / Mini, standard image generation, Nano Banana 2 Lite
Medium cost: Kling 2.6 (legacy), Kling 3.0 Turbo, Wan 2.5/2.6/2.7, Minimax Hailuo 2.3, standard I2V
High cost: Kling 3.0 (pro/4K modes), Seedance 2.0 at 1080p/4K, Veo 3 / 3.1, Cinema Studio
Apps: Vary widely — one-click apps are generally efficient
> "Seedance Pro" is a legacy UI label — not in the API catalog (2026-07-05);
> its budget slot is now Seedance 2.0 Fast / Mini. Sora 2 is UI-only (confirmed in the UI 2026-07-06) — not in
> the API catalog as of 2026-07-05; verify in the live UI before recommending.
**Before quoting any credit estimate for multi-shot work, run the generation
ledger and cite the numbers:**
python3 ../../scripts/higgsfield_memory.py ratio <project> --credits
python3 ../../scripts/higgsfield_memory.py budget <project> --shots <manifest.json>
ratio gives empirical takes-per-kept per shot type, with thestructural-vs-stochastic rejection split (high structural% = rewrite the
prompt, don't re-roll; high stochastic% = priced re-roll territory).
budget multiplies a planned shot manifest by those ratios → expectedgenerations + credit estimate with a stated confidence level.
low-n (under 5 logged generations) —the tool flags them; respect the flag.
documented default planning ratios — **2–3:1 simple shots, 4–6:1 complex
shots — labeled as defaults, not data.** The budget command does this
labeling automatically; keep the label when you relay the estimate.
one command (../higgsfield-recall/SKILL.md § Log the Generation Result).
1. Generating video before perfecting the image
The single biggest waste. If your Hero Frame (base image) isn't right, every
animated version will be wrong too.
Fix: Spend extra time on image generation (low cost) → animate once (higher cost)
2. Long prompts that fight each other
Over-specified prompts create conflicting instructions, forcing multiple regenerations.
Fix: Under-specialize on elements you don't care about. Specify only what matters.
3. Changing multiple variables between generations
If you change the prompt, the model, AND the camera in one go, you can't learn what fixed what.
Fix: Change one thing at a time. Systematic iteration is faster than random retries.
4. Using premium tiers (Kling 3.0 pro/4K, Seedance 2.0 4K, Veo 3.1) for simple shots
Premium models for simple single-character, single-camera shots.
Fix: Reserve premium models for scenes that genuinely need their capabilities.
Kling 3.0 Turbo or Kling 2.6 (legacy) handles most character drama at lower cost —
and on Kling 3.0, sound: off gives a silent video at lower credits (per the
live spec). Seedance has the same switch (generate_audio: false).
5. Not using Apps for tasks Apps are built for
Face swap, product placement, style transfer — doing these manually via prompt
takes more credits than the App designed for that task.
Fix: Check the Apps library first. If an App covers your use case, use it.
This is the single highest-leverage credit optimization technique:
Step 1: Generate 5–10 image variations (very low credit cost)
→ Find the one that's closest to your vision
Step 2: Refine that one image with inpainting/editing (low cost)
→ Get it exactly right
Step 3: Animate ONCE from the perfect Hero Frame (medium-high cost)
→ First animation attempt is already working with a strong foundation
Result: You spend more on cheap image credits, far less on expensive video credits.
The credit math almost always favors this approach.
Tight budget (Basic plan — 150 credits):
Pro" is a legacy UI label — not in the API catalog)
Mid budget (Pro plan — 700 credits):
(Sora 2 is UI-only, confirmed present in the UI 2026-07-06 — not in the API catalog; UI
live UI before recommending it)
High volume (Ultimate — 1,500 credits):
generate native audio (generate_audio, default on for 2.0), Kling 3.0 and
2.6 have a sound switch, Veo 3.1 Lite has generate_audio. Pick by scene
fit, then toggle audio — don't pick the model for the audio.
Use presets before writing from scratch
Higgsfield's presets (visual styles, motion presets, Cinema Studio genres) encode
a lot of quality that's hard to replicate with text alone. Always start with a
preset as a base, then customize.
Check the Community gallery before generating
Before burning credits on a new style or effect you haven't tried, find a community
example that uses it. See what actually works before committing.
Use Assist for quick decisions
"Should I use Kling 3.0 or Seedance 2.0 for this?" → ask Assist in 5 seconds rather
than generating two test clips.
Save successful prompts
When a generation works well, save the complete prompt immediately. Higgsfield
doesn't have a native prompt library — you need your own. A simple text file
organized by genre works well.
Chain Apps with video for social content
Generate a base clip with Kling 2.6, then feed it through an App (Transitions,
Style Snap, Urban Cuts) for the final social-ready version. Two steps, total cost
is still lower than generating a "perfect" clip from scratch.
Batch similar shots together
If you're using the same Soul ID character in 5 different scenes, generate them in
the same session. The Hero Frame warm-up time is essentially zero if you're
using the same Reference Anchor.
Week 1 — Image foundation (Basic plan)
Week 2 — Simple video (Basic plan)
Week 3 — Cinema Studio (Pro plan)
Week 4+ — Full production (Pro or Ultimate)
higgsfield-models — Detailed model comparison beyond what Assist provideshiggsfield-prompt — MCSLA formula for structured prompt buildinghiggsfield-apps — Apps Assist can recommendhiggsfield-pipeline — Full production workflowsTake osidemedia/higgsfield-assist from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.