Borrowing it
Nothing to install: this file belongs to shailendrahegde/pbi-to-exec-deck. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/shailendrahegde/pbi-to-exec-deck/main/.claude/commands/convert-to-deck.mdgit clone --depth 1 https://github.com/shailendrahegde/pbi-to-exec-deckWrote 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/commands/shailendrahegde/pbi-to-exec-deck/convert-to-deck)<a href="https://agentmods.dev/commands/shailendrahegde/pbi-to-exec-deck/convert-to-deck"><img src="https://agentmods.dev/badge/commands/shailendrahegde/pbi-to-exec-deck/convert-to-deck/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/commands/shailendrahegde/pbi-to-exec-deck/convert-to-deck"><img src="https://agentmods.dev/badge/commands/shailendrahegde/pbi-to-exec-deck/convert-to-deck.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 | $0.00000 | $0.00743 |
| Opus 5 | $0.00000 | $0.00371 |
| Sonnet 5 | $0.00000 | $0.00149 |
| Haiku 4.5 | $0.00000 | $0.00074 |
Grade A, and why
convert-to-deck 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Convert a Power BI dashboard export into an executive-ready presentation.
Usage
/convert-to-deck "C:\path\to\dashboard.pdf"
/convert-to-deck "C:\path\to\dashboard.pptx"
/convert-to-deck "C:\path\to\report.pbip"
The argument $ARGUMENTS is the path to the source file.
What to do
Step 1 — Prepare
Run the extractor to pull out dashboard images and metadata:
python convert_dashboard.py $ARGUMENTS --prepare
If --prepare fails because dependencies are missing, install them first:
pip install -r requirements.txt
python convert_dashboard.py $ARGUMENTS --prepare
Step 2 — Read the analysis request
Read temp/analysis_request.json
This tells you how many slides were extracted and where the images are saved.
If the source is a .pbip file and temp/pbip_context.json exists, read that too:
Read temp/pbip_context.json
Step 3 — Analyze each dashboard image
For every slide listed in analysis_request.json, read the image:
Read temp/slide_1.png
Read temp/slide_2.png
... (all slides)
Act as a senior analyst advising an IT decision maker. For each slide:
- Extract every visible number, percentage, and label with exact units (13K not 13,000)
- Identify which platforms, apps, teams, or features are shown — only mention what is visible
- Generate 3 insights following the
"Bold punchy line || Supporting evidence with data"format - Write a headline that answers "so what?" (memorable, no data dump)
For slides with charts or tables, generate a "chart" spec so the builder renders clean SVG — never embed raw screenshots. See CLAUDE.md for chart spec formats.
Also generate across all slides:
deck_title— compelling 5–10 word story-driven title (e.g. "Copilot Impact Confirmed: $14.7M in Value")deck_subtitle— scope line (platforms · org · date range)executive_summary— 5 synthesized findings, highest business impact firstrecommendations— 3–5 specific, data-grounded next steps
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 · 103 lines · 0 tokens per session scan A 1adf650aeb77
convert-to-deck is a command published in the GitHub repository shailendrahegde/pbi-to-exec-deck (11 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 743 tokens. 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 commands, from other repositories
brand-generate
Generate an on-brand document from a saved Brand Profile.
cti-report
Render case deliverables — relationship graph (PNG/SVG/Mermaid) and a polished PDF/DOCX assessment. Usage: /cti-report [--graph|--pdf].
prose-review-docs
Reviews markdown documentation files or directories against the active prose style rules — the plugin's vendor-neutral baseline plus your organization's overlay when one is configured. Accepts a file path or directory (recursive). Runs prose-style-checker and optionally Vale. Supports --fix to auto-apply safe…
ppt-image2-editable-rebuild
Rebuild image2 or imagegen reference slides as editable PowerPoint decks.
render-figures
Compile all .tex and .typ figure files in a directory.
harness-onboarding
Generate a human-readable onboarding document from HARNESS.md, AGENTS.md, and REFLECTIONLOG.md — a friendly guide for new team members.