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 agentmods add skills/sananthanarayan/skilldrop/deck-buildernpx skills add sananthanarayan/skilldrop --skill deck-buildergit clone --depth 1 https://github.com/sananthanarayan/skilldropWhat 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 | $0.00076 | $0.01880 |
| Opus 5 | $0.00038 | $0.00940 |
| Sonnet 5 | $0.00015 | $0.00376 |
| Haiku 4.5 | $0.00008 | $0.00188 |
Grade A, and why
deck-builder 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 2d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
deck-builder
You help the user produce an actual editable .pptx file, not just an outline. The skill runs python-pptx under the hood to materialize slides with a chosen color palette, multiple layout types, and audience-tuned density.
This skill pairs with two others:
audience-profile— decides how dense / how many / which sections the deck should haveslide-outliner— drafts the per-slide content before this skill turns it into a.pptx
For a single fast pipeline, use all three in order: profile → outline → build.
How to respond
-
Gather three inputs before generating anything:
-
Content. Either a finished outline (from
slide-outliner), a long doc the user wants compressed into slides, or a list of points. If the content is thin ("here's the topic, you fill in"), pause and ask — making slides up is the easiest way to make a bad deck. -
Audience. One of:
exec,board,technical,sales,internal,investor,partner,customer. If the user gives a free-form description ("VP of Eng + their staff at a partner"), map to the closest archetype and call out your choice. Useaudience-profilefor the structural rules. -
Palette. Always ask the user before generating — don't pick for them, and don't default silently. Present the choice like this:
Pick a palette before I generate the deck:
corporate-blue— default for B2B / enterprise audiencesmonochrome— restrained / when content is sensitivevibrant— internal / sales / pitch decksdark-mode— engineering audiences, live demoseditorial— long-form / read-ahead decksforest— calm, nature-leaningsunset— warm, narrative-leaning- Or give me hex values for
primary/secondary/accent/background/text - Or paste your brand colors and I'll map them into the five roles
-
What ships with it
9 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.
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.
- 2d ago First seen · 115 lines · 76 tokens per session scan A 68a06d640d85
deck-builder is a skill published in the GitHub repository sananthanarayan/skilldrop (2 stars, last pushed 18d ago), licensed MIT. It adds 76 tokens to every session and 1,880 once invoked, about $0.0004 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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