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Presenton Agent Skill

Generate AI-powered presentations locally using Presenton. Use when: (1) User asks to create a presentation or slideshow, (2) User wants to convert a document or prompt into slides, (3) User needs PPTX/PDF export with AI-generated content.

2k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
127
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/besoeasy/open-skills --skill presenton

The instruction itself

13 sections, as written by the author

Presenton — AI Presentation Generator

Presenton is an open-source, locally-run AI presentation generator. It creates professional slideshows from text prompts or uploaded documents, exports to PPTX and PDF, and exposes a built-in MCP server so agents can generate presentations programmatically.

When to use

  • Use case 1: When the user asks to generate a presentation or slideshow on any topic
  • Use case 2: When you need to convert a document, report, or prompt into structured slides
  • Use case 3: When the user wants to export a presentation as PPTX or PDF
  • Use case 4: When building agent workflows that produce presentation outputs via MCP
  • Use case 5: When the user wants AI-generated presentations that run entirely on their own device

Required tools / APIs

  • Docker (recommended) or Node.js LTS + Python 3.11 + uv for local dev
  • One of: OpenAI API key, Google Gemini API key, Anthropic API key, or a local Ollama instance
  • Optional image providers: DALL-E 3, Gemini Flash, Pexels, Pixabay, or ComfyUI

Install options:

# Docker (Linux/macOS) — recommended
docker run -it --name presenton \
  -p 5000:80 \
  -v "./app_data:/app_data" \
  ghcr.io/presenton/presenton:latest

# Docker (Windows PowerShell)
docker run -it --name presenton `
  -p 5000:80 `
  -v "${PWD}\app_data:/app_data" `
  ghcr.io/presenton/presenton:latest

# With OpenAI + DALL-E 3 (no UI key entry needed)
docker run -it --name presenton \
  -p 5000:80 \
  -e LLM="openai" \
  -e OPENAI_API_KEY="<your-key>" \
  -e IMAGE_PROVIDER="dall-e-3" \
  -e CAN_CHANGE_KEYS="false" \
  -v "./app_data:/app_data" \
  ghcr.io/presenton/presenton:latest

Skills

generate_presentation_via_api

Generate a presentation by sending a prompt to the Presenton REST API.

# Start Presenton first (see install above), then call the API
curl -fsS --max-time 60 \
  -X POST "http://localhost:5000/api/v1/ppt/generate" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Introduction to Quantum Computing", "n_slides": 8}'

# The response includes a presentation ID; download PPTX with:
PPTX_PATH=$(curl -s "http://localhost:5000/api/v1/ppt/generate" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Introduction to Quantum Computing", "n_slides": 8}' \
  | jq -r '.pptx_url')
curl -s "http://localhost:5000${PPTX_PATH}" -o presentation.pptx

Node.js:

async function generatePresentation(prompt, nSlides = 8, baseUrl = 'http://localhost:5000') {
  const res = await fetch(`${baseUrl}/api/v1/ppt/generate`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({ prompt, n_slides: nSlides }),
  });
  if (!res.ok) throw new Error(`HTTP ${res.status}: ${await res.text()}`);
  return await res.json(); // contains pptx_url and pdf_url
}

// Usage
// generatePresentation('Introduction to Quantum Computing', 10).then(console.log);

generate_with_mcp

Use Presenton's built-in MCP server to generate presentations from an AI agent.

# Add Presenton MCP server to your agent config (e.g. Claude Desktop, Cursor)
# mcp.json entry:
cat <<'EOF'
{
  "mcpServers": {
    "presenton": {
      "url": "http://localhost:5000/mcp"
    }
  }
}
EOF

Node.js:

// The MCP server exposes a generate_presentation tool.
// Call it via your MCP client library:
const result = await mcpClient.callTool('presenton', 'generate_presentation', {
  prompt: 'Climate Change: Causes and Solutions',
  n_slides: 10,
});
console.log(result); // { pptx_url, pdf_url }

generate_with_custom_template

Upload an existing PPTX to create an on-brand template, then generate from it.

# Upload a template PPTX to extract theme/design
curl -fsS --max-time 30 \
  -X POST "http://localhost:5000/api/v1/ppt/upload-template" \
  -F "file=@my_template.pptx"

# Generate a new presentation using that template
curl -fsS --max-time 60 \
  -X POST "http://localhost:5000/api/v1/ppt/generate" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Q3 Sales Report", "n_slides": 6, "template": "my_template"}'

Node.js:

const { readFileSync } = require('fs');

async function uploadTemplate(filePath, baseUrl = 'http://localhost:5000') {
  const form = new FormData();
  form.append('file', new Blob([readFileSync(filePath)]), 'template.pptx');
  const res = await fetch(`${baseUrl}/api/v1/ppt/upload-template`, {
    method: 'POST',
    body: form,
  });
  if (!res.ok) throw new Error(`Upload failed: HTTP ${res.status}`);
  return await res.json();
}

// Usage
// uploadTemplate('./branding.pptx').then(console.log);

Output format

  • pptx_url: Path to download the generated PPTX file (string)
  • pdf_url: Path to download the generated PDF file (string)
  • Error shape: { detail: "<message>" } — check Presenton logs for root cause

Rate limits / Best practices

  • Generation takes 15–60 seconds depending on the model and number of slides; use async handling
  • Cache generated presentations by prompt hash to avoid redundant API calls
  • Use DISABLE_IMAGE_GENERATION=true for faster, text-only output during development
  • Prefer Pexels or Pixabay as image providers to avoid per-image AI costs
  • Set CAN_CHANGE_KEYS=false in production to lock down credentials

Agent prompt

You have Presenton capability. When a user asks to create a presentation:

1. Confirm the topic and desired number of slides (default: 8)
2. Call POST http://localhost:5000/api/v1/ppt/generate with {"prompt": "<topic>", "n_slides": <n>}
3. Wait for the response (up to 60 seconds) and extract pptx_url and pdf_url
4. Offer the user download links for both PPTX and PDF
5. If a custom template is requested, upload it first via /api/v1/ppt/upload-template and include the template name in the generate request

Always check that Presenton is running at http://localhost:5000 before calling the API.
Report any HTTP errors with the status code and response body so the user can diagnose the issue.

Troubleshooting

Presenton container not starting:

  • Symptom: docker run exits immediately or port 5000 is unreachable
  • Solution: Check docker logs presenton for errors; ensure port 5000 is free (lsof -i :5000)

Generation times out:

  • Symptom: API call hangs beyond 60 seconds
  • Solution: Verify the LLM API key is valid and the model is reachable; reduce n_slides; check container logs

No images in slides:

  • Symptom: Slides are generated but contain no images
  • Solution: Set IMAGE_PROVIDER and the matching API key environment variable; or set DISABLE_IMAGE_GENERATION=true to skip images

MCP server not responding:

  • Symptom: Agent cannot connect to http://localhost:5000/mcp
  • Solution: Confirm Presenton is running and the MCP endpoint is accessible; check firewall rules

See also

  • ../browser-automation-agent/SKILL.md — Automate the Presenton web UI when API access is not available
  • ../pdf-manipulation/SKILL.md — Post-process exported PDFs
  • ../static-assets-hosting/SKILL.md — Host generated presentations for sharing

Notes

  • Source: https://github.com/presenton/presenton
  • License: Apache 2.0
  • Skill file path: skills/presenton/SKILL.md

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How to use it

Copy the folder

Take besoeasy/presenton from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference docker. Without those the skill loads but fails at the first command.