Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/shaharsha/claude-skillsnpx agentmods add skills/shaharsha/claude-skills/presentation-generatorWrote 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/shaharsha/claude-skills/presentation-generator)<a href="https://agentmods.dev/skills/shaharsha/claude-skills/presentation-generator"><img src="https://agentmods.dev/badge/skills/shaharsha/claude-skills/presentation-generator/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/shaharsha/claude-skills/presentation-generator"><img src="https://agentmods.dev/badge/skills/shaharsha/claude-skills/presentation-generator.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 | $0.00264 | $0.03785 |
| Opus 5 | $0.00132 | $0.01893 |
| Sonnet 5 | $0.00053 | $0.00757 |
| Haiku 4.5 | $0.00026 | $0.00379 |
Grade A, and why
presentation-generator 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 10d 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Presentation Generator
Image-as-slide decks. Every slide is a single 16:9 PNG generated by gpt-image-2. The slide is free to be anything visual: a cinematic photograph, a structured infographic with stacked principle cards, an architecture flowchart, a big-number stat, a comparison split-screen, a UI mockup with side annotations, a quote card, a do/don't table, an icon grid, a timeline, a hand-drawn whiteboard sketch.
The skill's job is to make Claude think like a creative director — narrative arc first, visual style locked, composition chosen per slide, prompts engineered with intention — before spending API tokens on imagery.
The two axes of a slide
- Style (locks at the deck level): aesthetic, palette, typography vibe, decorative motif. Constant across all slides — this is what makes the deck feel like one artifact.
- Composition (varies per slide): is this slide a hero photo, a flowchart, an infographic, a big number, a comparison? Pick what serves the slide's job.
Both NotebookLM's Cinematic Video Overviews and well-designed brand decks do exactly this. Lock style; vary composition.
The six phases
Research → Narrative Plan → Style Lock → Parallel Generation (×4) → QA → Assemble
Runs end-to-end autonomously. No approval gate between phases.
Phase 1 — Research
Build a dossier on the topic before touching the deck.
- Local files referenced ("the project plan", a path, a slug) → read with the Read tool.
- Online topic → WebSearch + WebFetch.
- Mixed → both. Local files are ground truth; online is supporting context.
- Brand book exists → if there's a
BRAND.mdfrom thebrand-systemskill in the project, read it. Use its palette, typography, and motif language verbatim in the deck-plan'sstyle_brief. Setbrand_sourcein the plan to point at it. This gives pixel-tight brand fidelity.
Keep the dossier in working memory: 5-15 key facts, quotes worth surfacing, numbers worth visualizing, audience signals.
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .gitignore 242 B
- README.md 6.5 KB
- reference/consistency-tactics.md 5.9 KB
- reference/image-prompting.md 13 KB
- reference/narrative-frameworks.md 6.5 KB
- reference/output-formats.md 5.2 KB
- reference/slide-compositions.md 19 KB
- reference/visual-style-brief.md 8.1 KB
- scripts/build-pptx.py 3.5 KB runs code
- scripts/generate-deck.py 10 KB runs code
- scripts/lock-style.py 5.7 KB runs code
- scripts/qa-slides.py 4.3 KB runs code
- scripts/README.md 5.2 KB
- scripts/render-pdf.sh 5.4 KB runs code
- templates/deck-plan.example.json 17 KB
- templates/deck-plan.schema.json 7.6 KB
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.
- 10d ago First seen · 227 lines · 264 tokens per session scan A 90310b8c19f9
presentation-generator is a skill published in the GitHub repository shaharsha/claude-skills (5 stars, last pushed 13d ago), licensed MIT. It adds 264 tokens to every session and 3,785 once invoked, about $0.0013 per session on Opus 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 2026-08-31.
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