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 davistroy/claude-marketplace --skill sg-generate-imagesgit clone --depth 1 https://github.com/davistroy/claude-marketplaceWrote 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/davistroy/claude-marketplace/sg-generate-images)<a href="https://agentmods.dev/skills/davistroy/claude-marketplace/sg-generate-images"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/sg-generate-images/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/davistroy/claude-marketplace/sg-generate-images"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/sg-generate-images.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 | $0.00039 | $0.00917 |
| Opus 5.5 | $0.00016 | $0.00367 |
| Sonnet 5.5 | $0.00008 | $0.00183 |
| Haiku 4.5 | $0.00004 | $0.00092 |
Grade A, and why
sg-generate-images 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 1mo 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slide Generator: Generate Images Step
Generate slide visuals using Gemini Pro from the validated graphics descriptions in the presentation. Uses a unified prompt builder and async batch generation for efficiency.
Pre-loaded Context
Working directory:
!pwd
Available presentation files:
!ls -la *.md 2>/dev/null | grep -i pres || echo "No presentation files found"
Existing images:
!ls -la images/ 2>/dev/null || echo "No images directory yet"
Prerequisites
- Preflight:
sg --versionmust succeed before proceeding — ifsgis missing, stop and tell the user this requires the privatedavistroy/slide-generatorengine (owner-only; see ADR-0008) slide-generatorpackage installedGOOGLE_API_KEYset in environment (Gemini Pro access)- A
presentation.mdfile with validated graphics descriptions - Graphics validation should be run first (
.graphics_validatedmarker)
Input Validation
Required:
<presentation.md>- Path to presentation markdown file
Optional:
--resolution <level>- Image resolution:small,medium,high(default: high)--image-format <fmt>- Output format:png,jpg(default: png)--skip-existing- Don't regenerate images that already exist
Instructions
- Verify prerequisites: Confirm
GOOGLE_API_KEYis set and presentation has validated graphics - Run image generation:
sg generate-images presentation.md --resolution high - Monitor progress: Image generation takes time (~5-10s per image)
- Verify output: Check that images were created in the
images/directory - Report results: Show count of images generated, any failures
How It Works
The image generation step uses:
- Gemini Pro (
gemini-3-pro-image-preview): Google's image generation model - Unified prompt builder:
prompt_builder.pyconstructs optimized prompts from descriptions - Async batch generation: Multiple images generated concurrently via
asyncio - API key in header: Authentication via header (not query param)
- Block reason diagnostics: Clear error messages when generation is blocked
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.
- 1mo ago First seen · 93 lines · 39 tokens per session scan A 095dd7928244
sg-generate-images is a skill published in the GitHub repository davistroy/claude-marketplace (5 stars, last pushed 19d ago), licensed MIT. It adds 39 tokens to every session and 917 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-04.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…