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-optimizegit 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-optimize)<a href="https://agentmods.dev/skills/davistroy/claude-marketplace/sg-optimize"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/sg-optimize/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-optimize"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/sg-optimize.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 | $0.00038 | $0.00741 |
| Opus 5.5 | $0.00015 | $0.00296 |
| Sonnet 5.5 | $0.00008 | $0.00148 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
sg-optimize 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slide Generator: Optimize Step
Run quality analysis and automated improvement on drafted slide content. Uses Claude with extended thinking (budget_tokens=4096, temperature=1.0) to score and improve content across 5 dimensions: readability, tone consistency, structure, redundancy, and citation quality.
Pre-loaded Context
Working directory:
!pwd
Available presentation files:
!ls -la *.md 2>/dev/null | grep -i pres || echo "No presentation files found"
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 installedANTHROPIC_API_KEYset in environment- A
presentation.mdfile from the draft step
Input Validation
Required:
<presentation.md>- Path to presentation markdown file
Optional:
--output <path>- Explicit output file path. If omitted, thesgengine chooses the output location itself — this is not documented in this repository (the engine lives in the privatedavistroy/slide-generatorrepo, ADR-0008/D23); runsg optimize --helpto confirm current behavior before relying on it.
Instructions
- Verify input: Confirm the presentation markdown exists and contains slide content
- Run optimization:
sg optimize presentation.md - Verify output: Confirm optimized file was created
- Report results: Show quality scores (before/after if available), improvements made
How It Works
The optimize step uses:
- Extended thinking: budget_tokens=4096 for deep analysis (temperature=1.0 required)
- 5-dimension scoring: Readability, tone, structure, redundancy, citations
- Representative sampling: For decks >15 slides, samples representative slides rather than processing all
- Batched optimization: Large decks optimized in batches with quality verification
- Assistant prefill: Forces structured JSON output for consistent scoring
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 · 79 lines · 38 tokens per session scan A 4016ff1d3d87
sg-optimize is a skill published in the GitHub repository davistroy/claude-marketplace (5 stars, last pushed 19d ago), licensed MIT. It adds 38 tokens to every session and 741 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.
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