stability-ai-v2

Stability AI — Gerador de Imagens Profissional

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/stability-ai from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Stability AI — Gerador de Imagens Profissional

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Quando Usar Esta Skill Vs Ai-Studio-Image, 1. Modos De Operacao, 2. Exemplos De Uso, Geracao Basica (Sd 3.5 Large), Qualidade Maxima (Ultra).

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• When the user mentions "stability ai" or related topics
• When the user mentions "stable diffusion" or related topics
• When the user mentions "sd3.5" or related topics
• When the user mentions "gerar arte" or related topics
• When the user mentions "gerar ilustracao" or related topics
• When the user mentions "image to image" or related topics

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Criar conta em platform.stability.ai (gratuito)
2. Copiar API Key do dashboard
3. Colar no .env: STABILITYAPIKEY=sk-sua-chave-aqui
4. pip install -r scripts/requirements.txt
5. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
6. Read the overview and provenance files before loading any copied upstream support files.
7. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.

Imported Workflow Notes

Imported: Setup Rapido

1. Criar conta em platform.stability.ai (gratuito)
2. Copiar API Key do dashboard
3. Colar no .env: STABILITY_API_KEY=sk-sua-chave-aqui
4. pip install -r scripts/requirements.txt

Detalhes completos em references/setup-guide.md.

Imported: Overview

Geracao de imagens via Stability AI (SD3.5, Ultra, Core). Text-to-image, img2img, inpainting, upscale, remove-bg, search-replace. 15 estilos artisticos.

Imported: How It Works

Skill para gerar imagens artisticas e fotorrealistas usando a Stability AI API. Gratuito com Community License (sem limite para uso pessoal/pequenas empresas).

Examples

Example 1: Ask for the upstream workflow directly

Use @stability-ai-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @stability-ai-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @stability-ai-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @stability-ai-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Provide clear, specific context about your project and requirements
• Review all suggestions before applying them to production code
• Combine with other complementary skills for comprehensive analysis
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.

Imported Operating Notes

Imported: Best Practices

• Provide clear, specific context about your project and requirements
• Review all suggestions before applying them to production code
• Combine with other complementary skills for comprehensive analysis

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/stability-ai, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

• api-reference.md
• prompt-engineering.md
• setup-guide.md
• config.py
• generate.py
• requirements.txt
• styles.py

Imported Reference Notes

Imported: Quando Usar Esta Skill Vs Ai-Studio-Image

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