Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
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Generates text in a learned writing voice. Use when drafting content that must match a specific author's style profile extracted by voice-extract.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Generate text in a user's extracted writing voice.
scribe:voice-extract)scribe:voice-review)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.
voice-generate:profile-loaded - Voice profile readvoice-generate:register-selected - Register chosenvoice-generate:source-framed - Material framed as notesvoice-generate:generated - Text producedvoice-generate:review-dispatched - Sent to review agentsPROFILE_DIR="$HOME/.claude/voice-profiles/{name}"
Read in order:
extraction.md - Core voice featuresregisters/{register}.md - Active registercraft-rules.md - Shared craft techniques (if exists)banned-phrases.md - Anti-patterns to avoid (if exists)Check for per-project override:
if [ -f ".voice/override.md" ]; then
# Merge project overrides with profile
fi
Load: @modules/register-selection
Select register by:
registers/default.mdLoad: @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):
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)
- ", so" tails on fact after fact (cut the consequence, or give it
its own sentence)
- "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}
After generation:
If .voice/override.md exists in the current project:
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Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
The English summary is being prepared. Showing the original description.
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
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Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
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Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
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Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
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Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
The English summary is being prepared. Showing the original description.