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 sammcj/agentic-coding --skill pptx-to-mdgit clone --depth 1 https://github.com/sammcj/agentic-codingWrote 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/sammcj/agentic-coding/pptx-to-md)<a href="https://agentmods.dev/skills/sammcj/agentic-coding/pptx-to-md"><img src="https://agentmods.dev/badge/skills/sammcj/agentic-coding/pptx-to-md/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/sammcj/agentic-coding/pptx-to-md"><img src="https://agentmods.dev/badge/skills/sammcj/agentic-coding/pptx-to-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00064 | $0.01605 |
| Opus 5.5 | $0.00026 | $0.00642 |
| Sonnet 5.5 | $0.00013 | $0.00321 |
| Haiku 4.5 | $0.00006 | $0.00161 |
Grade A, and why
pptx-to-md 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extract PPTX to per-slide markdown
This skill turns a .pptx file into one markdown file per slide, preserving layout context and image meaning. It does not paraphrase the text or describe images out of context. The output is suitable as input to a content uplift pass, a markdown-to-HTML build, or any other downstream transform.
When to use
The deck mixes text with embedded screenshots, diagrams, charts, or code samples in a layout that matters (columns, side-by-side panels, callouts). Plain text extraction would lose either the layout or the meaning of the images.
IMPORTANT: If the deck is: a PDF, text-only or if it has no images that are meaningful to the content, uvx 'markitdown[all]' <path-to-file> -o output.md is faster and usually sufficient without going through this skill's more complex pipeline as described below. You can try this and ask the user to review the output letting them know that if it's not sufficient you will continue with the more complex slide extraction pipeline.
Pipeline
PPTX -> prepare.py -> manifests + rendered JPGs + embedded PNGs
-> dispatch one sub-agent per slide
-> per-slide markdown files
-> concatenate.py -> deck.md
The orchestrator (you, in the calling session) does two things: run the prepare and concatenate scripts, and dispatch one sub-agent per visible slide. Each sub-agent does the actual vision-and-text composition for one slide and writes one markdown file. Sub-agents are independent so they parallelise cleanly.
Step 1 - prepare the workspace
python <skill>/scripts/prepare.py <pptx-path> <workspace-dir>
This unzips the PPTX, renders every visible slide to a JPG via LibreOffice and pdftoppm, then writes one manifest JSON per visible slide. After rendering, the script checks the JPG count matches the slide count and warns to stderr if they diverge - LibreOffice has been known to silently drop slides, so always read that warning before dispatching sub-agents.
Run this step OUTSIDE any command sandbox. LibreOffice headless needs to write its per-user profile and set OS/task policies that a sandbox blocks, so under sandboxing soffice fails silently: no PDF, empty output, and no deck_index.json. Under Claude Code specifically, run prepare.py with the Bash tool's dangerouslyDisableSandbox: true. Symptom to recognise: rendered/ stays empty and no deck_index.json is written while the soffice process sits at near-zero CPU.
What ships with it
5 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.
- 1mo ago First seen · 99 lines · 64 tokens per session scan A b6d05a0d29fe
pptx-to-md is a skill published in the GitHub repository sammcj/agentic-coding (167 stars, last pushed yesterday), licensed Apache-2.0. It adds 64 tokens to every session and 1,605 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
python-pptx-generator
Generate complete Python scripts that build polished PowerPoint decks with python-pptx and real slide content.
code-documentation-doc-generate
You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user guides, and technical references using AI-powered analysis and industry best practices.
csv-workbench
Analyze CSV files in /mnt/data and return concise numeric summaries.
review-artifact-comments
Only use when the user explicitly invokes this skill by name.
slides
Create and edit presentation decks as single self-contained HTML files with a live, editable preview and print-to-PDF export. Use when the user wants slides, a deck, or a presentation.
xlsx
Read and extract cell data from .xlsx Excel spreadsheets as TSV. Use when the user uploads or references an Excel file to read or summarize.