sn-ppt-entry
Entry point for PPT generation. Asks the user to choose a mode (fast, standard, or creative), then collects role / audience / scene / page_count as needed. For standard mode, also asks how images should be sourced (AI generation, web search, or none), whether charts should use AI-generated infographics or ECharts, and whether the final deliverable should be PPTX or PDF. Parses uploaded pdf/docx/md/txt files, produces task_pack.json + info_pack.json in a new deck_dir, then dispatches to sn-ppt-creative or sn-ppt-standard. Fast mode skips optional questions and gets straight to building. Use whe
npx skills add OpenSenseNova/SenseNova-Skills --skill sn-ppt-entry --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# sn-ppt-entry ## Hard preconditions Run `sn-ppt-doctor` hard checks (`SN_API_KEY` or capability-specific API keys / node / sn-image-base) at the start of this skill. If any fails, stop and tell the user to run `/skill sn-ppt-doctor`. If the user is not asking to generate a new deck and only wants to open an existing/generated deck in the WebUI, do not run these generation preconditions. Dispatch directly to `/skill sn-ppt-workbench`. ## Flow 1. Extract parameters from the user's message: - `role` (speaker identity) - `audience` - `scene` (where the deck will be used) - `page_count` - `language` — detect from the user's query: `zh-Hans` (Simplified Chinese), `zh-Hant` (Traditional Chinese), or `en` (English). Do NOT ask the user; just infer and record it. If unsure, use `zh-Hans`. 2. If the user asks only to open/preview/edit an existing generated deck in the WebUI, dispatch to `/skill sn-ppt-workbench deck_dir=<abs-or-user-provided-path>` and stop. Do not ask mode questions. 3. If `task_pack.json` + `info_pack.json` already exist in a deck_dir the user refers to and the user asks to continue generation, read them and jump to step 10 (see "Resume" below). 4. **Always ask the user w
- Hard preconditions
- Flow
- askuser boundary conditions
- Invoking the LLM for documentdigest
- Schemas
- 🚫 Hard rules
- Failure handling
- Progress echo — MANDATORY
- Output and handoff
- Does NOT
python3 $PPT_STANDARD_DIR/scripts/launch_workbench.py --deck-dir <deck_dir> --source-session-id "${HERMES_SESSION_KEY:-}" --agent-managed 1
set PPT_STANDARD_DIR=C:\Users\...\Repository\ppt-editor\skills\sn-ppt-standard && python %SKILL_DIR%\scripts\caption_images.py --deck-dir <deck_dir>
python3 -c "
import sys, json, pathlib
from model_client import llm
raw = json.loads(pathlib.Path('<deck_dir>/raw_documents.json').read_text())
Build the digest-safe view: strip tables[] and image paths, keep text + indices
docs_view = []
for d in raw.get('documents', []):
user_prompt = json.dumps({What does the sn-ppt-entry skill do?
Entry point for PPT generation. Asks the user to choose a mode (fast, standard, or creative), then collects role / audience / scene / page_count as needed. For standard mode, also asks how images should be sourced (AI generation, web search, or none), whether charts should use AI-generated infographics or ECharts, and whether the final deliverable should be PPTX or PDF. Parses uploaded pdf/docx/md/txt files, produces task_pack.json + info_pack.json in a new deck_dir, then dispatches to sn-ppt-creative or sn-ppt-standard. Fast mode skips optional questions and gets straight to building. Use whe
How do I install it?
Run `npx skills add OpenSenseNova/SenseNova-Skills --skill sn-ppt-entry --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From OpenSenseNova/SenseNova-Skills, a repository with 4,855 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.