Sn Ppt Workbench logo

Sn Ppt Workbench

OrganizationPopular
OpenSenseNova
sn-ppt-workbench

Use when the user asks to open, preview, inspect, or visually edit an existing SenseNova HTML presentation in the PPT Workbench, using an explicit deck_dir or the latest deck in the current workspace.

Overview

PublisherOpenSenseNova
RepositorySenseNova-Skills
Skill namesn-ppt-workbench
Stars
5.8K
Forks
402
Bundled files
19
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 19 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by OpenSenseNova on GitHub. Read the source before you install it.

Installation

Install the Sn Ppt Workbench AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/OpenSenseNova/SenseNova-Skills/tree/main/skills/sn-ppt-workbench
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/OpenSenseNova/SenseNova-Skills.git /tmp/SenseNova-Skills
mkdir -p .claude/skills
cp -r /tmp/SenseNova-Skills/skills/sn-ppt-workbench .claude/skills/sn-ppt-workbench
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sn Ppt Workbench in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sn Ppt Workbench on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sn Ppt Workbench is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

sn-ppt-workbench

Start or reuse the AI PPT editing WebUI for an existing HTML slide deck. The helper prefers Hermes/canvas/port-forward URLs when available. Without a forwarded URL, native hosts bind to localhost by default, while Docker/WSL bind to 0.0.0.0 so remote users can reach the WebUI through the host network.

Use Cases

  • The user already generated a deck and asks to open the WebUI/editor/workbench.
  • The user provides a deck_dir containing task_pack.json, slides/slide_NN.html, pages/page_NNN.html, or a root-level HTML deck.
  • The user says to inspect or edit previously generated slides without regenerating them.

Hard Rules

  1. Do not run sn-ppt-entry, sn-ppt-standard, page-html, batch-page-html, or export.
  2. Do not edit slide files directly. The WebUI handles user-visible editing.
  3. If deck_dir is missing, auto-detect only under $(pwd)/ppt_decks. Other roots are considered only when the caller explicitly passes --search-root; never scan home folders by default.
  4. If no usable deck is found, ask the user for the absolute deck_dir.
  5. Workbench startup is best-effort. If it skips or fails, report the reason and do not attempt generation as a fallback.
  6. Prefer a forwarded/canvas URL over localhost when the user may be on SSH, IM, or another remote device.
  7. When launched from the unified PPT flow, use the exact absolute task_pack.deck_dir; opening the Workbench must not create or switch tasks.
  8. Treat task_pack.json as progress/resume state and outline.md as the user-editable Story. Existing runtime builds may expose only part of these artifacts; report compatibility gaps instead of regenerating the deck.

Invocation

Use the helper directly:

bash
python3 $SKILL_DIR/scripts/open_workbench.py --deck-dir "<deck_dir>" --agent-session-id "${HERMES_SESSION_KEY:-}"

On native Windows where python3 is unavailable:

bash
python $SKILL_DIR/scripts/open_workbench.py --deck-dir "<deck_dir>" --agent-session-id "%HERMES_SESSION_KEY%"

If the user did not provide a deck path, let the helper auto-detect:

bash
python3 $SKILL_DIR/scripts/open_workbench.py --agent-session-id "${HERMES_SESSION_KEY:-}"

Pass same-session bridge details when available:

bash
python3 $SKILL_DIR/scripts/open_workbench.py \
  --deck-dir "<deck_dir>" \
  --agent-session-id "${HERMES_SESSION_KEY:-}" \
  --agent-managed 1 \
  --agent-provider hermes \
  --agent-transport gateway \
  --webui-base-url "${HERMES_WEBUI_BASE_URL:-}" \
  --gateway-base-url "${HERMES_GATEWAY_BASE_URL:-}"

--agent-transport may be omitted: the helper auto-selects gateway when the Hermes Gateway endpoint and key resolve (environment or Hermes .env files), then webui / acp / rest when only those details exist. Explicit flags and WORKBENCH_AGENT_TRANSPORT always win. With no resolvable bridge the bottom chat stays read-only by design.

For non-Hermes interactive providers, pass structured bridge details instead of scraping CLI/TUI output:

bash
python3 $SKILL_DIR/scripts/open_workbench.py \
  --deck-dir "<deck_dir>" \
  --agent-managed 1 \
  --agent-provider openclaw \
  --agent-transport rest \
  --agent-base-url "${WORKBENCH_AGENT_BASE_URL:-}" \
  --agent-api-key "${WORKBENCH_AGENT_API_KEY:-}"

python3 $SKILL_DIR/scripts/open_workbench.py \
  --deck-dir "<deck_dir>" \
  --agent-managed 1 \
  --agent-provider codex \
  --agent-transport acp \
  --acp-command "${WORKBENCH_ACP_COMMAND:-codex-acp}"

python3 $SKILL_DIR/scripts/open_workbench.py \
  --deck-dir "<deck_dir>" \
  --agent-managed 1 \
  --agent-provider box-agent \
  --agent-transport acp \
  --acp-command "${WORKBENCH_ACP_COMMAND:-${BOX_AGENT_ACP_COMMAND:-box-agent-acp}}"

When this helper runs inside Box Agent, the exported BOX_AGENT_PYTHON or BOX_AGENT_SKILL_TOOLS_ROOT environment automatically selects box-agent, acp, and the installed box-agent-acp command. Explicit WORKBENCH_AGENT_* flags or environment variables still take precedence.

For WorkBuddy, pass --agent-provider workbuddy only as provider identity. Tell the user clearly that WorkBuddy currently has no supported API or ACP interface for the interactive workbench bridge, so the WebUI can show WorkBuddy status but cannot send bottom-chat modification turns back to WorkBuddy.

CLI Subcommands (direct launch fallback)

When bypassing open_workbench.py and invoking the workbench launcher directly, use subcommands:

bash
node <launcher> start   --deck-dir "<path>" [--port 0] [--agent-managed]
node <launcher> status  --deck-dir "<path>"
node <launcher> stop    --deck-dir "<path>"

The old argument-only form (no subcommand) is deprecated — it will print a usage error.

Restart pitfall: start silently reuses an existing server instance for the same deck-dir (response contains "reused": true). If you updated the workbench code, you MUST run stop first, then start — otherwise the old process keeps serving stale code:

bash
node <launcher> stop  --deck-dir "<path>"
node <launcher> start --deck-dir "<path>" --port 0

Bind Host

The workbench resolves its bind address from --host CLI flag → WORKBENCH_HOST env var → default 127.0.0.1. When the user needs remote/LAN access, set WORKBENCH_HOST=0.0.0.0:

bash
export WORKBENCH_HOST=0.0.0.0
node <launcher> start --deck-dir "<path>" --port 0

The response url field will then show the LAN IP instead of 127.0.0.1.

Output Handling

Parse the single JSON line from stdout.

When status == "ok", echo the returned editor_url, public_url, or workbench.editorUrl for existing-deck editing requests. The helper may also return generation_url; that URL is the generation progress page at /progress, while the editor is /editor.

text
PPT 编辑工作台已启动:<editor_url>

If workbench.reused == true, say it reused the existing server.

If bind_host is 0.0.0.0, the URL is a Docker/WSL LAN fallback. Tell the user it must be reachable from their device/network; if not, ask them to provide a Hermes/canvas/port-forward URL and rerun with --public-url, or an explicit bind host with --host.

When status == "skipped" or status == "failed", echo the reason field. If reason == "nodejs_missing", ask whether the user wants NodeJS/dependencies installed; if they decline, do not open the WebUI. Ask for a valid deck_dir only if the reason says no deck was found.

Environment

The helper locates the editor launcher in this order:

  1. SENSENOVA_PPT_WORKBENCH_CLI
  2. PPT_WORKBENCH_CLI
  3. The runtime packaged beside this Skill
  4. The nearest src/ppt-editor source checkout or packaged release in the current worktree
  5. Common ~/Repository/ppt-editor fallbacks

The helper does not build the editor during an end-user launch. Packaged Skills must include workbench-runtime; source checkouts must build src/ppt-editor explicitly before using its launcher. The repository-level webui/ directory is a separate product and is not a launcher fallback for this Skill.

Remote URL discovery order:

  1. Explicit --public-url
  2. WORKBENCH_PUBLIC_URL, HERMES_WORKBENCH_PUBLIC_URL
  3. Hermes/canvas/forwarding env vars such as HERMES_CANVAS_URL, HERMES_PORT_FORWARD_URL, CANVAS_URL, PORT_FORWARD_URL, TUNNEL_URL
  4. Codespaces/Gitpod URL patterns
  5. Localhost on native hosts, or LAN fallback from the machine's non-loopback IPv4 address on Docker/WSL

Gateway Auth Setup

For writable interactive agent bridging (chat panel in workbench), Hermes keeps using the existing WebUI/Gateway protocol. OpenClaw should be exposed through a Gateway/REST-compatible HTTP endpoint. Codex, Claude Code, and Box Agent should use ACP JSON-RPC adapters, configured with --acp-command or WORKBENCH_ACP_COMMAND. Box Agent defaults to its installed box-agent-acp entry point. Never parse provider CLI/TUI output for chat synchronization.

For writable Hermes Gateway bridging, the Gateway API server and workbench must authenticate with matching API keys.

Key env vars:

VariableSet ByValue
API_SERVER_KEYGateway (.env)Shared secret
WORKBENCH_GATEWAY_API_KEYWorkbench envSame as API_SERVER_KEY; preferred explicit bridge key
HERMES_GATEWAY_BASE_URLWorkbench envhttp://127.0.0.1:8642
WORKBENCH_AGENT_PROVIDERWorkbench envhermes, openclaw, codex, claude-code, box-agent, or workbuddy
WORKBENCH_AGENT_TRANSPORTWorkbench envwebui, gateway, rest, or acp
WORKBENCH_AGENT_BASE_URLWorkbench envOpenClaw/Gateway REST endpoint
WORKBENCH_AGENT_API_KEYWorkbench envREST provider bearer token
WORKBENCH_ACP_COMMANDWorkbench envACP adapter command, e.g. codex-acp
BOX_AGENT_ACP_COMMANDBox Agent / Workbench envOptional override for the default box-agent-acp adapter command

Quick steps:

  • Gateway: set API_SERVER_KEY in .env, restart gateway
  • Workbench: set WORKBENCH_GATEWAY_API_KEY to same value, set HERMES_GATEWAY_BASE_URL=http://127.0.0.1:8642
  • If no explicit bridge key is set, the Node relay falls back to API_SERVER_KEY, HERMES_GATEWAY_API_KEY, then backend-only AI_GATEWAY_API_KEY (ppt-editor-dev by default). Prefer the explicit bridge key for custom/shared gateways.

Progress Echo

Always send a short progress message before and after the helper:

WhenExample
Before helper正在启动 PPT 预览工作台,不会重新生成幻灯片...
SuccessPPT 编辑工作台已启动:http://127.0.0.1:18087
Generation progress URL available生成进度工作台:http://127.0.0.1:18087/progress
Skip/failurePPT 工作台未启动:<reason>

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sn Ppt Workbench AI skill do?

Use when the user asks to open, preview, inspect, or visually edit an existing SenseNova HTML presentation in the PPT Workbench, using an explicit deck_dir or the latest deck in the current workspace.

Why use Sn Ppt Workbench on TypingMind?

Because you install it once and use it with any model. Sn Ppt Workbench is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sn Ppt Workbench in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenSenseNova/SenseNova-Skills/tree/main/skills/sn-ppt-workbench. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sn Ppt Workbench?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sn Ppt Workbench?

As many as you like. As long as a model supports skills, you can use Sn Ppt Workbench with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sn Ppt Workbench AI skill free?

Yes. It is published on GitHub by OpenSenseNova under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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