Claude-night-market voice-generate
Generate text in a learned writing voice using extracted voice
install
source · Clone the upstream repo
git clone https://github.com/athola/claude-night-market
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/athola/claude-night-market "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/scribe/skills/voice-generate" ~/.claude/skills/athola-claude-night-market-voice-generate && rm -rf "$T"
manifest:
plugins/scribe/skills/voice-generate/SKILL.mdsource content
Voice Generation Skill
Generate text in a user's extracted writing voice.
Core Principle: Source Material Framing
The single largest variable in output quality is how source material is framed in the prompt. Material framed as "raw notes I'm still thinking through" produces text that feels like thinking. Material framed as summaries produces reporting.
Always frame user-provided source material as raw notes unless the user explicitly requests otherwise.
Required TodoWrite Items
- Voice profile readvoice-generate:profile-loaded
- Register chosenvoice-generate:register-selected
- Material framed as notesvoice-generate:source-framed
- Text producedvoice-generate:generated
- Sent to review agentsvoice-generate:review-dispatched
Step 1: Load Voice Profile
PROFILE_DIR="$HOME/.claude/voice-profiles/{name}"
Read in order:
- Core voice featuresextraction.md
- Active registerregisters/{register}.md
- Shared craft techniques (if exists)craft-rules.md
- Anti-patterns to avoid (if exists)banned-phrases.md
Check for per-project override:
if [ -f ".voice/override.md" ]; then # Merge project overrides with profile fi
Step 2: Register Selection
Load:
@modules/register-selection
Select register by:
- Explicit user request ("use casual register")
- Context matching from register metadata
- Default fallback to
registers/default.md
Step 3: Frame Source Material
Load:
@modules/source-framing
Default framing (always use unless user overrides):
Below are my rough notes on this topic. I'm still thinking through these ideas. Use them as the raw material for the piece, not as a structure to follow: --- {user_provided_source_material} ---
Alternative framings (only if user requests):
- "structured outline" - when user wants to preserve structure
- "key points to cover" - when user provides bullet points
- "conversation to draw from" - when source is a transcript
Step 4: Generation Prompt
Compose the generation prompt:
You are writing a piece in a specific voice. The voice features below were extracted from the writer's own work. Follow them as concrete instructions, not suggestions. ## Voice Features {extraction.md content} ## Active Register: {register_name} {register content} ## Craft Techniques (apply all) - Concrete-first: Lead with specific, physical details before any abstraction - Naming: When you describe a pattern in 2+ sentences, compress it into a 2-4 word label - Opening moves: Start mid-thought, with a specific moment, or with a counterintuitive claim. Never start with throat-clearing - Human-moment anchoring: Ground every abstraction in a specific scene or lived experience - Aphoristic destinations: At least one sentence per section should be worth repeating out of context ## Banned (never use) {banned_phrases content, or default list:} - Em dashes (use commas, colons, semicolons, parentheses) - "delve", "utilize", "leverage", "facilitate" - "it's important to note", "in today's world" - "here's the thing", "let that sink in" - "furthermore", "moreover", "comprehensive" - Negation-correction patterns ("This isn't X. This is Y.") ## Source Material {framed source material from Step 3} ## Task Write the piece. Follow the voice features precisely. Apply craft techniques. Do not use any banned phrases. The output should read as if the writer produced it themselves. Length: {user_specified or ~same as source material} Format: {user_specified or prose paragraphs}
Step 5: Post-Generation
After generation:
- Scan output for banned phrases (auto-fix silently)
- Check for em dashes (replace with appropriate punctuation)
- Dispatch to voice-review skill if user wants review
- Save pre-review snapshot if learning mode is active
Model Routing
- Generation: Use Opus. Tonal shifts, parenthetical subversion, and subtle voice qualities require the larger model. Sonnet flattens these.
- Banned phrase scan: Can run locally (regex/grep)
- Review agents: Sonnet is sufficient (structured prompts)
Per-Project Voice
If
.voice/override.md exists in the current project:
- Read override content
- Merge with profile (overrides take precedence)
- Note in output: "Applied project voice override"
Exit Criteria
- Text generated in the specified voice
- No banned phrases present
- Craft techniques applied (concrete-first, naming, etc.)
- Source material framed as raw notes
- Review dispatched (if requested)
- Snapshot saved (if learning mode active)