Flatten skill category directory structure
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# Phase 4: Chapter Audio Generation
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## Script Setup (Run Once Per Session)
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Read `skillScriptsPath` from the state file — written by Phase 0 with the skill's real install path:
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```bash
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export AUDIOBOOK_SCRIPTS=$(python3 -c "
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import json, os
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from pathlib import Path
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audiobook_root = Path(os.getcwd()) / '.audiobook'
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hits = list(audiobook_root.glob('*/.audiobook-state.json')) if audiobook_root.exists() else []
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if not hits:
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print('ERROR: state file not found — run Phase 0 first'); exit(1)
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data = json.loads(hits[0].read_text())
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val = data.get('skillScriptsPath', '').strip()
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if not val:
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print('ERROR: skillScriptsPath missing from state — re-run Phase 0'); exit(1)
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if not Path(val).is_dir():
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print(f'ERROR: skillScriptsPath does not exist: {val}'); exit(1)
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print(val)
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")
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echo "AUDIOBOOK_SCRIPTS=$AUDIOBOOK_SCRIPTS"
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```
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A clean path (no ERROR) means scripts are ready.
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**If you see `skillScriptsPath missing from state`:** Do NOT re-run Phase 0 just for this. Instead, derive the path directly from the `available_skills` list visible in your system context — find the `<location>` entry for the audiobook skill (e.g. `file:///Users/alice/.hub/skills/audiobook/SKILL.md`), strip `file://` and `/SKILL.md`, append `/scripts`. Then patch the state file:
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```python
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import json
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from pathlib import Path
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audiobook_root = Path(os.getcwd()) / ".audiobook"
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state_path = next(audiobook_root.glob("*/.audiobook-state.json"))
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state = json.loads(state_path.read_text())
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state["skillScriptsPath"] = "/derived/path/to/audiobook/scripts" # replace with actual
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state_path.write_text(json.dumps(state, ensure_ascii=False, indent=2))
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```
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Then re-run the Script Setup block above.
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---
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## 4.1 Core Principle: TTS Built-in Silence
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**Never add silence or crossfade via ffmpeg in post-processing.** All silence must come from `<#X#>` pause markers in the TTS text. TTS-generated silence shares the same noise floor and audio characteristics as the speech, preventing waveform discontinuities at splice points.
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## 4.2 TTS Text Silence Padding
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Each segment's TTS text needs head/tail silence padding. **This is applied automatically by the Step 1 script — do NOT manually edit segment text.**
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The chapter script from Phase 2 already contains inline `<#X#>` pause markers. Step 1 preserves ALL existing markers and adds head/tail padding on top.
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**Padding rules (applied automatically in Step 1):**
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| Position | Head Padding | Tail Padding |
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|----------|-------------|-------------|
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| First segment of book | `<#2#>` | `<#0.2#>` |
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| Last segment of book | `<#0.2#>` | `<#3#>` |
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| Chapter ending (not last) | `<#0.2#>` | `<#2#>` |
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| Normal segment | `<#0.2#>` | `<#0.2#>` |
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## 4.3 TTS Generation (Parallel with Pre-Indexed Plan)
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**The ONLY rule that matters: 1 text per call, max 3 calls per wave. Run every script below — do NOT skip any.**
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Generation uses **parallel `audios_generation` calls** with a **pre-indexed generation plan** to guarantee correct playback order regardless of completion timing.
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Each segment from the chapter script becomes **one entry** in the generation plan — no merging or grouping.
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### Step 1: Parse Chapter Script & Build Generation Plan (MANDATORY script)
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This script does everything:
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1. Reads the chapter script (preserving ALL `<#X#>` markers from Phase 2)
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2. Parses segment delimiters and headers
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3. Maps voice labels to voice_ids via `voice_settings.json`
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4. Applies 4.2 head/tail padding
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5. Outputs `generation_plan.json`
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6. **Prints every wave's calls — use these directly for Step 2**
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```bash
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python3 $AUDIOBOOK_SCRIPTS/build_generation_plan.py <chapter_number>
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```
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The script auto-detects chapter title from `chapters.md` and first/last chapter from `.audiobook-state.json`. It also validates voice assignment and warns if dialogue segments fall back to narrator voice.
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**This script is MANDATORY — run it first, then use its output for Step 2.**
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### Step 2: Fire TTS calls wave by wave
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Use the exact calls printed by Step 1. Each call has exactly **1 text** and **1 filename**.
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**Rules:**
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- Fire up to 3 calls per wave (copy the calls from Step 1 output) — **fire all 3 simultaneously (in parallel), NOT one by one**
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- Wait for ALL calls in a wave to complete before starting the next wave
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- No sleep needed between successful waves
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- **If any call fails → sleep 30 seconds, then continue to the next wave.** Do NOT retry the failed call inline. All failures are handled after Step 3.5 by the Failure & Retry script, which reads parameters from `generation_plan.json` (guaranteed correct). Inline retry risks using wrong parameters from LLM context.
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**Example (from Step 1 output):**
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```
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# Wave 1 (fire these 3 calls in parallel):
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audios_generation(texts=["<#0.2#>She opened the door.<#0.5#>"], voice_id="narrator", speed=0.9, filenames=["ch1_idx_0"])
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audios_generation(texts=["Hello!"], voice_id="alice", speed=1.0, filenames=["ch1_idx_1"])
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audios_generation(texts=["<#0.2#>He waved back.<#0.2#>"], voice_id="narrator", speed=0.9, filenames=["ch1_idx_2"])
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# Wait for wave 1 to complete. Then wave 2:
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audios_generation(texts=["Good morning."], voice_id="bob", speed=1.0, filenames=["ch1_idx_3"])
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...
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```
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**DO NOT:**
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- Put multiple texts in one call: `texts=["a", "b", "c"]` is WRONG
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- Invent your own filenames — use the `ch{N}_idx_{M}` from Step 1
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- Skip Step 1 and construct calls yourself
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### Step 3: Match blobs to plan (MANDATORY script)
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After all TTS calls complete, run this to map generated audio files back to plan entries:
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```bash
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python3 $AUDIOBOOK_SCRIPTS/match_blobs.py <chapter_number>
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```
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The script reads `generation_plan.json` + `assets.json`, matches by filename (last-write-wins for retries), and updates `generation_plan.json` with `blob_path` for each entry.
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### Step 3.5: Verify blob content (MANDATORY script)
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Verify every matched blob's metadata matches the plan (catches wrong voice_id or text from misfired calls):
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```bash
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python3 $AUDIOBOOK_SCRIPTS/verify_blobs.py <chapter_number>
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```
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The script compares voice_id and cleaned text from `assets.json` metadata against `generation_plan.json`. Mismatched entries have their `blob_path` cleared so the Retry script picks them up.
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**How `clean_text()` works (important for debugging false positives):**
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The script normalises both sides before comparing:
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1. **`html.unescape()`** — the chapter script (Phase 2 output) may store pause markers as `<#0.6#>` (HTML-escaped) rather than `<#0.6#>`. The plan inherits this encoding. The TTS metadata always stores raw markers. Unescaping before stripping ensures both sides match.
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2. **Smart-quote → ASCII normalisation** — the plan may contain Unicode curly quotes (`"` / `"` / `'` / `'`). The TTS engine normalises these to straight ASCII quotes (`"` / `'`) in stored metadata. Both sides are normalised before comparison.
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If you see unexpected "text mismatch" failures on Step 3.5, check `generation_plan.json` for `<` / `>` or `\u201c` / `\u201d` — these indicate the source script was HTML-escaped or contained smart quotes. The script handles both automatically; no manual fix needed.
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### Step 3.6: Organize segment files (MANDATORY script)
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Move segment audio files from the project root into `audio/chapter_{N}/segments/` and update `assets.json` paths:
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```bash
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python3 $AUDIOBOOK_SCRIPTS/organize_segment_files.py <chapter_number>
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```
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The script reads `generation_plan.json` for filenames, moves `.mp3` and `_subtitle.json` files, and updates `assets.json` path fields. Idempotent — safe to re-run after retries.
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### Step 4: Write manifest (MANDATORY script)
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```bash
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python3 $AUDIOBOOK_SCRIPTS/write_manifest.py <chapter_number>
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```
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The script reads `generation_plan.json`, writes `manifest.txt` in playback order, and verifies all blob files exist on disk.
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### Failure & Retry (MANDATORY script)
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If Step 3 reports unmatched segments, run this to get retry calls:
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```bash
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python3 $AUDIOBOOK_SCRIPTS/print_retry_calls.py <chapter_number>
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```
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The script cleans old workspace `.mp3` files (prevents gateway dedup suffix), then prints exact retry calls grouped by wave (max 3 per wave).
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**Retry procedure:**
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1. Run Step 3 (blob matching) + Step 3.5 (verification) to identify all failures
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2. Run the Failure & Retry script above — it reads `generation_plan.json` and prints exact calls
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3. Sleep 20 seconds (let system recover from transient issues)
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4. Fire the printed calls (max 3 per wave) — do NOT modify the parameters
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5. Re-run Step 3 + Step 3.5 → re-run this script → repeat until all matched
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**CRITICAL:** Never construct retry calls yourself. Always use this script's output. The script reads parameters from `generation_plan.json`, ensuring text, voice_id, speed, and filename are all correct. Manual retry from memory is the #1 cause of wrong audio content.
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Never skip a failed segment. The manifest requires every segment to have a blob_path.
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### TTS text limits
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- Each text should not exceed 2500 characters
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- If a single segment is too long, split by sentence into sub-segments connected with `<#0.2#>`
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- Sub-segments share the same voice_id and get consecutive indices in the plan
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## 4.4 Concatenation & Export
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### Step 1: Verify manifest
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```bash
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python3 $AUDIOBOOK_SCRIPTS/write_manifest.py <chapter_number>
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```
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This is the same script as Step 4 — it writes `manifest.txt` and verifies every file exists. Run it again here to confirm nothing changed between generation and concatenation.
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### Step 2: Delegate to editing sub-agent
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Pass the **exact ordered file list from manifest.txt** to the editing sub-agent. **Do NOT re-sort or re-order** — the manifest is the single source of truth.
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```
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请帮我拼接以下音频片段成一个完整的章节文件。
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不需要 crossfade、fade 或 DC removal — 直接拼接即可。
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片段列表（按顺序排列，不要重新排序）：
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1. /abs/path/to/.hilo/.blobs/{uuid1}.mp3
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2. /abs/path/to/.hilo/.blobs/{uuid2}.mp3
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3. /abs/path/to/.hilo/.blobs/{uuid3}.mp3
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...
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格式要求：MP3, 44100Hz, 256kbps
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输出文件名：chapter_{N}.mp3
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完成后请返回输出文件路径和时长。
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```
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**Important:**
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- Input file list MUST come from `manifest.txt`
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- Number each file to make order unambiguous
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- Do NOT specify an output path — let the editing agent decide
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- The editing sub-agent automatically handles canvas registration (writes to both project root and `.hilo/.blobs/`, registers in `assets.json`)
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### Filename rules
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- Individual segments: `ch{N}_idx_{M}` (generated by Step 1 script, do not change)
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- Final chapter audio: `chapter_{N}.mp3`
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- **Never use Chinese characters in any audio filename** — canvas registration silently fails
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## 4.5 Audio Quality Check
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After each chapter's final audio is exported, run the quality checker:
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```bash
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python3 $AUDIOBOOK_SCRIPTS/audio_check.py /path/to/exported_chapter.mp3
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```
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> **ffmpeg dependency:** `audio_check.py` and `generate_assembly_report.py` both shell out to `ffmpeg` / `ffprobe`. If `ffmpeg` is not on `$PATH`, prepend the binary location:
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> ```bash
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> PATH="/opt/homebrew/Cellar/ffmpeg/8.1/bin:$PATH" python3 $AUDIOBOOK_SCRIPTS/audio_check.py ...
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> ```
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> Find the binary with: `find /usr /opt /Users -name "ffmpeg" -type f 2>/dev/null | head -3`
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If issues are found, delegate fixes to the **editing sub-agent**:
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- **Pops/clicks**: Apply adeclick/adeclip filter
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- **DC offset > 1%**: Apply dcshift correction
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- **Clipping**: Reduce volume and regenerate the affected segments
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**Energy spikes are normal:** The quality checker reports "energy spikes" at segment boundaries (silence → speech onset from hard-cut concatenation). These are expected and require no action — they are not audio artifacts.
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## 4.6 Assembly Report
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After the quality check passes, generate a markdown assembly report. This is the **single source of truth** for users to inspect, locate, and request re-edits of any segment.
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### What it contains
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A markdown table with one row per segment:
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| Column | Content |
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|--------|---------|
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| `#` | Segment index (primary identifier for re-edit requests) |
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| `Start` / `End` | Precise timestamps `hh:mm:ss.ss` via ffprobe |
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| `Voice ID` | The actual `voice_id` used |
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| `Local File` | Root-directory filename (matches canvas display) |
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| `Text` | Clean spoken text with `<#X#>` markers stripped |
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### Generation script
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```bash
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python3 $AUDIOBOOK_SCRIPTS/generate_assembly_report.py <chapter_number>
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```
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> **ffmpeg dependency:** This script uses `ffprobe` to compute timestamps. If `ffprobe` is not on `$PATH`, prepend the binary location (same as 4.5 above).
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The script reads `generation_plan.json`, uses ffprobe to compute timestamps, maps blob refs to local filenames via `assets.json`, and writes `{book_name}_chapter_{N}_assembly.md` to the project root. Auto-detects language for tips text.
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> **Canvas note:** The canvas does not render markdown tables — only header lines are previewed. Users can open the assembly report in any markdown viewer for the full table.
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### Re-edit workflow
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When the user requests changes (e.g. "segment #14 sounds too fast"):
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1. Look up index 14 in `generation_plan.json` for `voice_id`, `speed`, `text`, `filename`
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2. Regenerate: `audios_generation(texts=[new_text], voice_id=..., speed=..., filenames=[filename])`
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3. Re-run Step 3 blob matching to pick up the new blob (latest entry with same filename wins)
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4. Rewrite `manifest.txt` from updated plan
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5. Re-concatenate via editing sub-agent
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6. Re-run quality check and regenerate assembly report
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## 4.7 Final User Message (REQUIRED)
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After the assembly report is generated, send a completion message. Match the user's language.
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Include:
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- Final audio filename (UUID on canvas)
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- Duration
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- Cast list (narrator + characters)
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- Assembly report filename
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- How to request fixes (mention segment # number)
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- Options: generate next chapter / re-edit a segment
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## 4.8 Multi-Chapter Generation
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> **Note:** True background/parallel chapter generation is not currently supported.
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> Chapters are processed one at a time (sequentially) to ensure quality and allow user review between chapters.
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**After the first chapter is confirmed by the user:**
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1. Tell the user how many chapters remain and ask if they want to continue generating them
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2. For each remaining chapter, follow the full 4.2–4.6 workflow in order:
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- Build generation plan → Fire TTS waves → Match blobs → Verify → Organize → Write manifest → Concatenate → Quality check → Assembly report
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3. After each chapter completes, update `chaptersCompleted` in `.audiobook-state.json`
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4. Notify the user that chapter N is done, show duration and assembly report filename, then ask whether to proceed to the next chapter or stop
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## Error Handling
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- TTS generation failure: Sleep 20s then retry. Never skip — keep retrying until success.
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- File parsing failure: Prompt the user to check file format
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- Audio concatenation failure: Check file paths and formats
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Reference in New Issue
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