菜单
Use when the user asks to generate images via the Luma AI API (Dream Machine / Photon); collects a prompt and options interactively, then calls the API using the bundled script. Requires LUMA_API_KEY — will prompt the user if missing.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | luma-imagegen |
| description | Use when the user asks to generate images via the Luma AI API (Dream Machine / Photon); collects a prompt and options interactively, then calls the API using the bundled script. Requires LUMA_API_KEY — will prompt the user if missing. |
| author | lumalabs |
Generates images using the Luma AI Photon model (Dream Machine API). Handles API key detection, interactive prompt collection, parameter selection, async polling, and final image download — all via the bundled scripts/luma_imagegen.py CLI.
modify_image_refLUMA_API_KEY in environment. If missing, guide the user (see below).scripts/luma_imagegen.py with the collected parameters.state: completed.output/luma/.Before any API call, check for the key:
python3 ${CLAUDE_SKILL_DIR}/scripts/luma_imagegen.py --check-key
If LUMA_API_KEY is missing:
.env file or export it in their shell:
export LUMA_API_KEY=your_key_here
--check-key command to verify.Ask these questions before running the generation:
16:9): "What aspect ratio? Options: 1:1, 3:4, 4:3, 9:16, 16:9 (default), 9:21, 21:9"photon-1): "Use photon-1 (higher quality) or photon-flash-1 (faster and cheaper)?"Only ask what's needed — skip questions the user has already answered in their message.
python3 ${CLAUDE_SKILL_DIR}/scripts/luma_imagegen.py \
--prompt "YOUR AUGMENTED PROMPT" \
--aspect-ratio 16:9 \
--model photon-1 \
[--image-ref "https://example.com/ref.jpg" --image-ref-weight 0.85] \
[--out output/luma/]
All flags:
| Flag | Default | Description |
|---|---|---|
--prompt | (required) | Text description of the image |
--aspect-ratio | 16:9 | 1:1, 3:4, 4:3, 9:16, 16:9, 9:21, 21:9 |
--model | photon-1 | photon-1 or photon-flash-1 |
--image-ref | — | Public URL for style/structure reference |
--image-ref-weight | 0.85 | Weight of reference image (0.0–1.0) |
--modify-ref | — | Base image URL to modify |
--modify-ref-weight | 0.5 | Weight for modification fidelity |
--out | output/luma/ | Output directory for downloaded images |
--poll-interval | 3 | Seconds between polling requests |
--check-key | — | Verify LUMA_API_KEY is set and exit |
output/luma/ with descriptive filenames (e.g., photon1_hero_16x9.png). The output directory is relative to the current working directory when the script is invoked.failure_reason from the API response.Reformat the user's description into a structured spec. Only make implied details explicit — do not invent new requirements.
Template (include only relevant lines):
Primary request: <user's main prompt>
Scene/background: <environment or setting>
Subject: <main subject>
Style/medium: <photo/illustration/3D/cinematic/etc>
Composition/framing: <wide/close-up/overhead; subject placement>
Lighting/mood: <lighting type and emotional tone>
Color palette: <dominant colors or palette notes>
Aspect ratio: <e.g., 16:9 landscape>
Avoid: <elements to exclude>
Augmentation rules:
Primary request: a misty mountain lake at sunrise
Scene/background: alpine lake surrounded by pine trees, light morning fog
Style/medium: photorealistic nature photography
Composition/framing: wide panoramic, lake centered, mountains in background
Lighting/mood: golden hour, warm and serene
Aspect ratio: 16:9 landscape
Avoid: people, boats, watermarks, oversaturation
Primary request: a ceramic coffee mug on a wooden table
Scene/background: warm kitchen interior, soft bokeh background
Subject: minimalist white ceramic mug, steam rising
Style/medium: clean product photography
Lighting/mood: soft diffused window light
Aspect ratio: 1:1 square
Avoid: text, logos, harsh shadows, clutter
photon-flash-1 for quick iteration; switch to photon-1 for final quality.| Model | Speed | Quality | Best for |
|---|---|---|---|
photon-1 | Slower | Higher | Final assets, complex scenes |
photon-flash-1 | Fast | Good | Rapid iteration, drafts |
The script uses only the Python standard library. No additional packages are required.
Audit and incrementally retrofit an existing codebase so its intent and behavior are equally legible to people and AI agents. Applies Context Architecture's eight principles: place AGENTS.md at boundaries, bind every context claim to a mechanism (lint, types, tests, review), name boundaries, and find context that has rotted. Use when an agent reimplements code that already exists, invents structure, follows stale or deleted docs, propagates a deprecated pattern, or resolves ambiguity at random, or when asked to make a repository "agent-ready", "AI-legible", or to add or fix AGENTS.md / CLAUDE.md files.
Use when the user wants to integrate with the X (Twitter) API via Xquik to search tweets, look up user profiles, extract followers, run giveaway draws, monitor accounts, or access trending topics. Also use when the user mentions 'Xquik,' 'Twitter API,' 'X API,' 'tweet scraper,' 'follower extraction,' or 'Twitter monitoring.' Covers REST API, webhooks, and MCP server setup.
Fill any PDF locally and place each value precisely in a visual editor. Use when the user wants to fill out a PDF form, enter data into a PDF, complete a tax/insurance/bank form, or position text on a flat/scanned PDF. Handles flat (field-less) PDFs, per-character (comb) fields, and native AcroForm fields; leaves the signature blank for the user to sign.
Automated Android CI/CD pipeline to Google Play — supports TWA, React Native, Flutter, and native Android. Run npx android-cicd to set up keystore generation, GitHub Secrets, and a multi-stage workflow (internal/alpha/beta/production) with auto-bump versionCode.
Use this skill whenever a developer wants to turn an idea into a complete, production-ready, end-to-end system plan BEFORE writing any code. Trigger on 'plan this system', 'design the architecture for', 'help me blueprint', 'deep plan for X', 'break this idea into components', 'expand into action points', 'full implementation plan', or when the user pastes a project idea wanting architecture, components, pipelines, and file-level execution mapped out. Casual phrasing also triggers: 'help me think this through end-to-end', 'plan before coding'. Also covers living-workspace patterns: self-improving knowledge bases, reflection loops with auditor agents, four-agent teams, schema-as-code, wiki health scoring. **Resume triggers**: 'where did we leave off', 'continue this plan', 'resume my blueprint' - rehydrates state from disk via SESSION.md/NEXT.md/decisions/. Web research is mandatory every invocation.
Use when adding a blog to a Next.js + Sanity site, building a blog section from scratch, integrating Sanity CMS for editorial content, or setting up an SEO-optimized article surface. Triggers on phrases like 'add a blog', 'build the blog', 'create blog section', 'set up blog with Sanity', 'integrate Sanity CMS', 'blog architecture', or any new-blog scoping conversation on a Next.js project.