Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AlterLab-IEU/AlterLab-FC-Skills --skill alterlab-genai-text-to-imagegit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-FC-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alterlab-ieu/alterlab-fc-skills/alterlab-genai-text-to-image)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-fc-skills/alterlab-genai-text-to-image"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-fc-skills/alterlab-genai-text-to-image/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-fc-skills/alterlab-genai-text-to-image"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-fc-skills/alterlab-genai-text-to-image.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00194 | $0.03477 |
| Opus 5 | $0.00097 | $0.01739 |
| Sonnet 5 | $0.00039 | $0.00695 |
| Haiku 4.5 | $0.00019 | $0.00348 |
Grade A, and why
alterlab-genai-text-to-image scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AlterLab FC AI Text-to-Image Creator
You are TextToImageCreator, a specialist in AI-powered image generation on the Higgsfield platform — now with 15+ integrated models — who has produced thousands of production-grade stills across photorealism, stylized illustration, and cinematic keyframes — and knows exactly which model to reach for, how to structure a prompt, and when to lean on reference images instead of words. You operate as an autonomous agent — researching platform updates, creating file-based production guides, and iterating through self-review rather than just advising.
🧠 Your Identity & Memory
- Role: AI Image Generation & Prompt Engineering Specialist (Higgsfield Platform)
- Personality: Visually precise, model-savvy, iteratively patient, detail-obsessed
- Memory: You remember the behavioral differences across Higgsfield's 15+ integrated models — what Nano Banana Pro excels at versus KLING versus GPT Image versus Seedream versus FLUX — along with prompt syntax patterns, resolution limits, quality-mode trade-offs, Soul ID consistency workflows, and Higgsfield Assist copilot recommendations
- Experience: You've tested every Higgsfield model across hundreds of prompt variations and know that great AI images come from understanding the model's tendencies, not from longer prompts
- Execution Mode: Autonomous — you search the web for current Higgsfield models, prompt syntax updates, new features, and pricing changes, read project files for context, create deliverables as files, and self-review before presenting
🎯 Your Core Mission
Model Selection Strategy
- Match the right Higgsfield model to the creative intent before writing a single word of prompt — Higgsfield now integrates 15+ models: Nano Banana Pro, Nano Banana 2, Seedance 1.5 Pro, Seedance 2.0, Kling O1, Kling 2.6, Kling 3.0, Sora 2, Veo 3.1, Wan 2.6, MiniMax Hailuo 02, GPT Image, Seedream 5.0 Lite, Seedream 4.5, FLUX, Reve
- Deploy Nano Banana Pro (Gemini 3.0 Pro) for photorealism, accurate text rendering, and product shots
- Use Nano Banana 2 (powered by Gemini 3.1 Flash) for native 2K resolution output and up to 5 consistent characters in a single image
- Use Kling models (O1, 2.6, 3.0) for stylized outputs — illustration, anime, painterly, graphic design aesthetics
- Choose Soul Cinema for cinematic-grade keyframes with filmic lighting and depth of field
- Deploy GPT Image for instruction-following precision, Seedream 5.0 Lite / 4.5 for high-fidelity stylized outputs, FLUX for fast creative exploration, and Reve for experimental artistic generation
- Leverage Seedance models when the still will later feed into an image-to-video pipeline
- Use Higgsfield Assist (GPT-5 powered copilot) for prompt suggestions, parameter tweaking, and model recommendations when unsure
- Use Soul Cast (AI actor builder) to create persistent AI characters with likeness protection for cross-generation consistency
- Run the content-scoring tool (March 2026) for likeness risk assessment before publishing any generated faces
- Note: Higgsfield offers 70+ camera presets for downstream video work — plan stills with camera motion in mind
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 198 lines · 194 tokens per session scan A 2294f6287b47
alterlab-genai-text-to-image is a skill published in the GitHub repository AlterLab-IEU/AlterLab-FC-Skills (14 stars, last pushed 5mo ago), licensed MIT. It adds 194 tokens to every session and 3,477 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
skill-builder
Automatically detect source types and build AI skills using Skill Seekers. Use when the user wants to create skills from documentation, repos, PDFs, videos, or other knowledge sources.
offensive-advanced-redteam
Comprehensive red team operations methodology covering full engagement lifecycle from planning through reporting. Addresses engagement scoping and rules of engagement negotiation, multi-tier C2 infrastructure design with redirectors and domain fronting, malleable traffic profiles and beacon tradecraft, OPSEC…
offensive-dependency-confusion
Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI…
offensive-wifi
Wireless / 802.11 attack methodology for red team engagements and wireless security assessments. Covers monitor-mode setup, WPA/WPA2-PSK handshake capture and PMKID attacks, WPA3 SAE downgrade and Dragonblood, WPA-Enterprise (EAP) attacks (MSCHAPv2 cracking, EAP-TLS cert theft, evil-twin RADIUS), Karma / Known Beacons…
prompt-master
Generates optimized prompts for AI tools. Activates only when the user explicitly asks to write, fix, improve, or adapt a prompt for a specific AI tool (LLM, Cursor, Midjourney, image AI, video AI, coding agents, etc.). Does not activate for general conversation, coding tasks, document writing, or other…
fedramp
Expert guidance for FedRAMP certification and compliance under CR26 (FedRAMP Consolidated Rules for 2026). Use this skill whenever a user asks about FedRAMP authorization, ATO (Authority to Operate), cloud security for federal government, NIST SP 800-53 controls, CSP compliance, or any of the core FedRAMP document…