菜单
Transform written content (blog posts, newsletters, articles) into visual slide deck images. This skill should be used when converting text content into presentation format, creating slide graphics from outlines, or generating visual summaries of written material.
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
Final adversarial audit of finished work by one top-tier model (Fable 5 or Opus 4.8), in a single report-only pass across three axes: verify the load-bearing invariants (especially any you could NOT run locally), simplify without losing properties, and hunt for live variants of the bug shapes just fixed. You then verify each finding and act. Use as the closing gate on a substantive or risky change before calling it done, especially when part of it (a systest, a migration, a concurrency path) can't be validated locally. Distinct from /advisor (decision consult), /review-loop (multi-agent fix loop), and /variant-analysis (single-pattern sweep). Invoke via /advisor-review or after finishing hard-to-verify work.
Line-level git staging and non-interactive rebase for agents that know exactly which lines they changed. Use when you need atomic commits carved out of a larger diff, or when you need to squash/drop/reorder/reword commits without interactive prompts.
On-demand consultation of a higher-tier model (Opus 4.8 or Fable 5) from a cheaper executor session. Emulates the native advisor-tool pattern in Claude Code: keep the main loop on a cheap model (Sonnet 5) and call the expensive model rarely, via a focused consultation packet, for a plan/decision/'what am I missing' — not for code. Use when the executor is stuck, before committing to a plan, after repeated failed attempts at the same fix, or before a risky/irreversible change. Invoked via /advisor or when the executor recognizes a consult checkpoint.
Expensive planner (Opus 4.8 / Fable 5) decomposes a task into independent work items, a fleet of cheap Sonnet 5 (or Haiku 4.5) workers executes them in parallel via a Workflow, and the planner synthesizes the results. Emulates the native orchestrator pattern in Claude Code: keep the expensive model scarce (one planning pass, one synthesis pass) and the cheap model abundant (N parallel workers). Prefers a deterministic dynamic workflow when available; falls back to in-instance Task dispatch. Use when the user types /orchestrate or asks to decompose, fan out, or parallelize a task across independent workers.
Babysit CI after a push: a monitor→classify→remediate state machine that watches a run to completion, mechanically fixes trivial/build breakage, reproduces test failures locally to tell a flake from a real bug, reruns suspected flakes within a budget, hands reproduced failures to a fixer that commits a fixup and pushes, and loops until CI is green or it can justify a bail back to the user. Prefers a deterministic dynamic workflow when available; falls back to in-instance Task dispatch. Use when the user types /ci-loop or asks to watch/babysit/auto-fix CI for a pushed branch or PR until it's green.
Adversarial review→triage→fix loop until a cold verifier signs off. Fans out lens-specific reviewer subagents, verifies every finding against the code (killing false positives), auto-applies confirmed fixes as fixup commits, and repeats until a fresh verifier approves. Prefers a deterministic dynamic workflow when available; falls back to in-instance Task dispatch. Use when the user types /review-loop or asks to adversarially review-and-fix a change set, branch, or commit range until clean.
| name | slide-creator |
| description | Transform written content (blog posts, newsletters, articles) into visual slide deck images. This skill should be used when converting text content into presentation format, creating slide graphics from outlines, or generating visual summaries of written material. |
| allowed-tools | Bash(python:*), Read, Write, Skill |
This skill transforms written content into visual slide deck images using AI image generation. It analyzes text content, extracts key points, and generates presentation-quality slide images.
nano-banana skill must be available for image generation.google-genai package installedRead and analyze the source content to identify:
Structure the presentation as:
Slide 1: Title slide (topic, subtitle)
Slide 2: Introduction/Problem statement
Slides 3-N: Key points (one concept per slide)
Slide N+1: Conclusion/Summary
Slide N+2: Call to action (optional)
For each slide, create an image prompt that:
Use the nano-banana skill to generate images:
# Single slide
python ~/.claude/skills/nano-banana/scripts/generate_image.py \
"Professional slide background: [concept], [style], 16:9 aspect, clean with text space" \
slide_01.png --aspect 16:9
# Batch generation
python ~/.claude/skills/nano-banana/scripts/batch_generate.py \
slide_prompts.json ./slides/ --aspect 16:9 --parallel 3
Accept feedback and regenerate specific slides:
# Edit existing slide
python ~/.claude/skills/nano-banana/scripts/edit_image.py \
slides/slide_03.png "make the colors more vibrant" slides/slide_03_v2.png
Bold typography-inspired background for [topic] presentation, [style], gradient [colors], modern and professional, 16:9 aspect ratio
Visual metaphor for [concept]: [metaphor description], [style], [brand colors], clean composition with space on [left/right] for text overlay, presentation graphic
Abstract data visualization representing [metric/trend], infographic style, [colors], clean white background, professional presentation graphic
Section divider for [section name], abstract [theme] imagery, gradient [colors], full bleed background, minimal text space
Inspiring background for conclusion: [theme], uplifting atmosphere, [colors], professional, space for summary points
See references/slide-styles.md for pre-defined style presets:
Create a slide_prompts.json file:
[
{
"prompt": "Title slide for AI presentation, modern tech aesthetic, blue gradient, bold composition",
"filename": "slide_01_title.png",
"aspect": "16:9"
},
{
"prompt": "Visual metaphor: neural network as interconnected nodes, tech illustration style, blue and purple",
"filename": "slide_02_intro.png",
"aspect": "16:9"
},
{
"prompt": "Growth chart concept, abstract rising bars with glow effect, tech presentation style",
"filename": "slide_03_growth.png",
"aspect": "16:9"
}
]
# The Future of Remote Work
Remote work is transforming how we think about productivity...
## Key Benefits
1. Flexibility
2. Work-life balance
3. Global talent access
## Challenges
- Communication
- Culture building
- Technology needs
## Best Practices
...
1. Title: "The Future of Remote Work"
2. Hook: Remote work transformation visual
3. Benefits: Flexibility metaphor
4. Benefits: Work-life balance visual
5. Benefits: Global connectivity
6. Challenges: Communication barriers
7. Solutions: Best practices overview
8. Conclusion: Future outlook
[
{"prompt": "Title slide: Future of Remote Work, modern office fading into home workspace, professional blue tones", "filename": "slide_01.png"},
{"prompt": "Remote work transformation: office desk morphing into laptop anywhere, clean illustration style", "filename": "slide_02.png"},
{"prompt": "Flexibility concept: person working from beach, mountain, city cafe montage, lifestyle photography style", "filename": "slide_03.png"}
]
When the user requests changes:
output_dir/
├── slide_01_title.png
├── slide_02_intro.png
├── slide_03_point1.png
├── slide_04_point2.png
├── slide_05_point3.png
├── slide_06_conclusion.png
└── slide_prompts.json # Save prompts for reference