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/ai-analyst-lab/ai-analyst-plugin/slide-transformnpx skills add ai-analyst-lab/ai-analyst-plugin --skill slide-transformgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-pluginWrote 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/ai-analyst-lab/ai-analyst-plugin/slide-transform)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/slide-transform"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/slide-transform.svg" alt="Measured on agentmods" 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 | $0.00115 | $0.02387 |
| Opus 5 | $0.00057 | $0.01193 |
| Sonnet 5 | $0.00023 | $0.00477 |
| Haiku 4.5 | $0.00012 | $0.00239 |
Grade A, and why
slide-transform 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 5d 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Slide Transform
Purpose
Take one bad slide and produce 2-3 redesigned variants, each with an explanation of what changed and why. Each variant optimizes for a different dimension of the Data Story Checklist.
When to Use
Apply this skill when:
- The user asks to fix, improve, or redesign a specific slide — "fix slide 3", "make this slide better", "transform this slide"
- After
/deck-critiqueidentifies slides scoring below 6/12 — target the worst offenders - The user wants to see multiple approaches to presenting the same content
This skill can be invoked directly as /slide-transform or called by the presentation-doctor orchestrator agent.
Inputs
{{SLIDE_CONTENT}}: The original slide content — either raw text, Marp markdown for one slide, or a slide object fromdeck_parser.py{{OPTIMIZE_FOR}}(optional): Which checklist dimension to prioritize —SO-WHAT,STAKES,EVIDENCE,ASK, orall(default:all){{AUDIENCE}}(optional): Who the presentation is for{{CONTEXT}}(optional): What decision or meeting this slide supports{{CRITIQUE}}(optional): The per-slide scorecard from/deck-critique— if provided, uses the specific scores to guide the transformation
Instructions
Before You Start: Input Validation
If the user hasn't provided the actual slide content:
Stop and ask for it. Do NOT create an example slide or guess what the slide might contain. You need the real slide content to provide useful transformations. Ask:
- "Can you share the slide content? You can paste the text, share the Marp markdown, or describe what's currently on the slide."
Reason: Transforming a hypothetical slide wastes time and produces variants the user can't actually use. The whole point is to fix THEIR slide, not a made-up one.
If the user's context is unclear:
Ask clarifying questions before proceeding:
- What decision does this slide need to inform? (helps determine if Variant C should emphasize stakes vs ask)
- Who's the audience? (exec = emphasis on stakes and ROI; PM = emphasis on action and metrics)
- What's the primary problem with the current slide? (helps prioritize which variant to recommend)
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.
- 5d ago First seen · 261 lines · 115 tokens per session scan A 6098febb6906
slide-transform is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (32 stars, last pushed 9d ago), licensed MIT. It adds 115 tokens to every session and 2,387 once invoked, about $0.0006 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 2026-08-30.
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