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 BlackBeltTechnology/pi-agent-dashboard --skill deck3d-from-pptxgit clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboardWrote 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/blackbelttechnology/pi-agent-dashboard/deck3d-from-pptx)<a href="https://agentmods.dev/skills/blackbelttechnology/pi-agent-dashboard/deck3d-from-pptx"><img src="https://agentmods.dev/badge/skills/blackbelttechnology/pi-agent-dashboard/deck3d-from-pptx/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/blackbelttechnology/pi-agent-dashboard/deck3d-from-pptx"><img src="https://agentmods.dev/badge/skills/blackbelttechnology/pi-agent-dashboard/deck3d-from-pptx.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 | $0.00100 | $0.02200 |
| Opus 5.5 | $0.00040 | $0.00880 |
| Sonnet 5.5 | $0.00020 | $0.00440 |
| Haiku 4.5 | $0.00010 | $0.00220 |
Grade A, and why
deck3d-from-pptx 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 4d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
deck3d-from-pptx
Take a real .pptx and rebuild it as a deck3d presentation whose slides match the
original when the camera stops and move through 3D space between slides. Every
creative decision is the user's: you generate variants, show them, ask, and record
the answer in style.json. The deck3d rules of the deck3d tune
loop still apply: never edit deck.html, never edit derived IR fields (only
overrides), no randomness, timers or network in local effects, and finish with
deck3d check deck.html --style clean — or every remaining warning explained (a derived
credits slide counts as explained).
Detail per step (what to read, how to author variants, which samples, the question):
reference/steps.md.
0. Import and reference renders (always first)
deck3d pptx import talk.pptx -o talk [--ref exports/]
writes talk/pptx/layout.json (1920-unit slide space, items with stable ids
sNN-iMMM), talk/pptx/media/, a baseline deck.md and deck.json whose
overrides.assets pin the layout and every media file. Unsupported constructs (charts,
SmartArt, tables, EMF/WMF, WordArt, gradient fills…) become visible fallback items —
a crop of the reference render, else an outlined placeholder — each with one warning.
Reference renders come first. Ask the user (ask_user) for a PNG export of the deck
(PowerPoint: File → Export → PNG, all slides; Keynote and Slide1.PNG names work) and
pass the folder as --ref. Skip the question only when LibreOffice (soffice) and
pdftoppm are on PATH. If the user declines, say so once, and from then on every step
reports snapshot review (deck3d snapshot, eyeballing, check) instead of
compare scores — never pretend a score exists.
Then build the baseline: cd talk && deck3d build deck.md -o deck.html (a native deck3d
slide per pptx slide). Re-importing later keeps your tuning: deck3d pptx import talk.pptx -o talk --force matches slides by content, backs up deck.json.bak, and
deck3d variants replay re-applies every recorded pick.
What ships with it
2 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.
- 4d ago First seen · 135 lines · 100 tokens per session scan A caa9914c2c95
deck3d-from-pptx is a skill published in the GitHub repository BlackBeltTechnology/pi-agent-dashboard (319 stars, last pushed yesterday), licensed MIT. It adds 100 tokens to every session and 2,200 once invoked, about $0.0004 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 2026-10-12.
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