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docs: document long outputs and FunASR hotwords

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nite
2026-07-14 17:00:27 +08:00
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@@ -89,6 +89,8 @@ If the agent's runtime supports structured questioning (e.g., a `clarify` tool o
**Completion criteria:** user has described at least a rough editing goal, and the agent has probed the relevant axes above.
**Long requirement summaries:** if the synthesized requirements, transcript-derived notes, or edit-planning response will be long, do not dump the whole thing into chat by default. Ask the user whether to save it as a file instead. Markdown (`.md`) is the default format for requirement summaries and edit plans; if the user requests another format (JSON, CSV, DOCX, etc.), use the requested format when practical.
### Step 4 — Transcribe audio
Use the bundled `funasr-script` in `scripts/transcription/`. **Prefer Fun-ASR-Nano** as the default transcription model — it has higher accuracy and sensitivity on Chinese audio. Use SenseVoice only for fast previews.
@@ -130,6 +132,8 @@ uv run --directory SKILL_DIR/scripts/transcription funasr-nano VIDEO_PATH --list
Where `VIDEO_DIR` is the directory containing the video file, `SKILL_DIR` is the skill installation directory, and `AUDIO_LANGUAGE_CODE` is the explicit transcription language (for example `zh` for Mandarin Chinese).
**Context and hotwords:** Fun-ASR-Nano is an LLM-based ASR model and upstream code supports prompt-style `language` and `hotwords` hints. However, do not assume the current bundled script automatically performs cross-segment semantic correction: it currently passes `language` / `use_itn`, but does not pass external hotwords or rolling `prev_text` context between VAD segments. If the video contains known game terms, names, locations, item names, or other jargon, ask the user for a hotword list or derive candidate terms and confirm them before transcription. See `references/funasr-nano-context-hotwords.md`. Hotwords are biasing hints, not a substitute for final manual checking.
**Common OBS multi-track audio layouts.** When the user says "multi-track" or mentions OBS recording, these are the typical stream layouts:
| Track | Typical content |
@@ -319,7 +323,7 @@ For fast-paced story + comedy gameplay videos, cull hard: keep combat, danger, r
This workflow is especially effective for requests like **“find fast-paced funny + story-driven candidate segments”**. It keeps token/runtime cost low while still verifying whether a transcript-highlighted moment actually has usable on-screen action.
Output a Markdown table with overall recommendations, then let the user iterate. **Respond in the same language the user is using.**
Output a Markdown table with overall recommendations, then let the user iterate. **Respond in the same language the user is using.** If the plan is likely to be long (large tables, detailed scripts, full requirement summaries, or multi-section recommendations), ask whether the user wants it saved as a file instead of pasted into chat. Default to Markdown (`.md`) for saved plans unless the user requests another format.
```markdown
## Edit Plan