/voice-review

name: voice-review
description: Runs parallel prose and craft review agents against a voice profile. Use when checking generated content for AI patterns and voice drift before publishing.
globs: "**/*.{md,txt}"
alwaysApply: false
category: writing-quality
tags:
- voice
- review
- prose
- craft
- quality
tools: []
complexity: medium
estimated_tokens: 1600
progressive_loading: false
dependencies:
- scribe:voice-extract
- scribe:voice-generate
- scribe:slop-detector
- imbue:review-core
- imbue:structured-output

Voice Review Skill

Dispatch dual review agents and present unified findings.

When NOT To Use

• Producing the text (use `scribe:voice-generate`)
• A generic AI-pattern scan with no voice profile (use

`scribe:slop-detector`)

Method: Parallel Dual-Gate Review

Two agents run in parallel on the generated text: 1. **Prose reviewer**: AI patterns, banned phrases, voice drift 2. **Craft reviewer**: Naming, destinations, dwelling, devices, anchoring

Hard failures (banned phrases, em dashes) are auto-fixed. Everything else returns as advisory tables for user decision.

Required Progress Items

1. `voice-review:text-loaded` - Generated text read 2. `voice-review:register-loaded` - Voice register loaded 3. `voice-review:agents-dispatched` - Both reviewers launched 4. `voice-review:hard-fails-fixed` - Auto-corrections applied 5. `voice-review:advisories-presented` - Tables shown to user 6. `voice-review:findings-verified` - Citations confirmed by verifier

Step 1: Load Context

Read:

• The generated text (from file or clipboard)
• The active voice register
• The banned phrases list

Step 2: Dispatch Review Agents

Launch both agents in parallel:

Agent(prose-reviewer):
  - text: {generated_text}
  - register: {register_content}
  - banned_phrases: {banned_list}

Agent(craft-reviewer):
  - text: {generated_text}
  - register: {register_content}

Step 3: Process Results

Hard Failures

Apply all auto-fixes from prose reviewer silently:

• Remove/replace banned phrases
• Replace em dashes with appropriate punctuation
• Rewrite negation-correction patterns

Report: "Fixed N hard failures (X banned phrases, Y em dashes, Z patterns)"

Advisory Tables

Present both tables to the user:

**Prose Review Advisories:**

| # | Line | Anchor | Pattern | Current | Proposed fix | |---|------|--------|---------|---------|--------------|

**Craft Review:**

| Dimension | Rating | Notes | Proposed improvement | |-----------|--------|-------|---------------------|

Step 4: User Decision

For each advisory row, user can:

• **Accept** (a): Apply the proposed fix
• **Reject** (r): Keep the current text
• **Rewrite** (w): Apply a custom fix

Present as:

[1] Prose: Frictionless transition at "Furthermore, the..."
    Proposed: Cut transition, start mid-thought
    [a]ccept / [r]eject / re[w]rite?

Step 5: Apply Decisions

• Apply accepted fixes to the text
• Skip rejected items
• For rewrites, incorporate user's version
• Save final text

Step 6: Snapshot (if learning active)

If the user has learning mode enabled:

• Save "post-review" snapshot (text after hard-fail fixes,

before user decisions on advisories)

• Save "post-fixes" snapshot (text after user decisions)
• Both go to `~/.claude/voice-profiles/{name}/learning/snapshots/`

Integration with voice-generate

When dispatched from voice-generate, the flow is: 1. voice-generate produces text 2. voice-generate calls voice-review 3. voice-review dispatches agents, processes results 4. User makes decisions on advisories 5. If learning mode: snapshots saved for later comparison

Standalone Usage

Can also be run on any existing text:

/voice-review path/to/file.md --profile myvoice --register casual

Verify Findings Are Grounded (`voice-review:findings-verified`)

Write advisory rows to `.review/findings.json`, run the citation verifier (`Skill(imbue:review-core)` Step 5), and drop or label `UNVERIFIED` any the verifier rejects.

Verification

After the review completes, validate these conditions:

• Both review agents returned results (no timeouts)
• Hard failures auto-fixed and diff shown to user
• Advisory tables presented with accept/reject/rewrite options
• User decisions applied to the final text
• Final text saved to disk
• Snapshots saved (if learning mode active)

Exit Criteria

• [ ] Both review agents returned results without timeout
• [ ] Hard failures auto-fixed and diff shown to user
• [ ] Advisory tables presented with accept/reject/rewrite options
• [ ] User decisions applied to the final text
• [ ] Final text saved to disk
• [ ] Every advisory row carries a `Line` (file:line) and verbatim `Anchor`;

`citation_verifier.py` confirmed all citations (exit `0`) or unverified rows are dropped/labeled `UNVERIFIED`

Test Spec

The test suite (`test_voice_review.py`) validates:

• Skill file exists and references parallel dispatch
• Hard failure vs advisory separation is documented
• Prose reviewer agent exists with hard-failure patterns
• Craft reviewer agent exists with five-dimension ratings
• Both agents produce tabular output for downstream merging