菜单
Improves a voice profile by learning from manual edits. Use after editing generated text to refine registers and close voice drift over time.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/athola/claude-night-market --skill voice-learn命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
Turn hunches into accepted results: worthiness score, evidence bar, research-to-rules. Use when vetting ideas. Not for QA; use night-market-validation-and-qa.
Generates and self-executes a diff-derived test plan for a PR. Use when validating PR changes before merge. Do not use for code review; use sanctum:pr-review.
Curate the web-capture index. Use when the capture backlog grows, captures sit unprocessed at seedling/pending, or to surface stored research during work.
正在显示 SKILL.md
| name | voice-learn |
| description | Improves a voice profile by learning from manual edits. Use after editing generated text to refine registers and close voice drift over time. |
| globs | **/*.{md,txt} |
| alwaysApply | false |
| category | writing-quality |
| tags | ["voice","learning","improvement","feedback","iteration"] |
| tools | [] |
| complexity | high |
| model_hint | opus |
| estimated_tokens | 2000 |
| progressive_loading | true |
| modules | ["modules/snapshot-management.md","modules/pattern-analysis.md"] |
| dependencies | ["scribe:voice-extract","scribe:voice-generate","scribe:voice-review"] |
Learn from user edits to improve the voice profile over time.
scribe:voice-extract)scribe:voice-review)Every piece flows through three stages:
The learning agent compares stages 2 and 3 (post-review vs post-edit) to identify patterns in what the user changed. These patterns inform register and rule updates.
voice-learn:snapshots-loaded - All three stages readvoice-learn:diff-analyzed - Changes categorizedvoice-learn:accumulator-checked - Prior patterns reviewedvoice-learn:proposals-generated - Updates proposedvoice-learn:user-approved - Changes accepted by userLoad: @modules/snapshot-management
PROFILE_DIR="$HOME/.claude/voice-profiles/{name}"
SNAP_DIR="$PROFILE_DIR/learning/snapshots"
# Find the most recent snapshot set
# Format: {piece-name}-{timestamp}-{stage}.md
Read all three stages for the target piece.
Load: @modules/pattern-analysis
Compare post-review vs post-edit. Categorize every change:
| Category | Example |
|---|---|
| Tone adjustment | Softened a claim, added hedge |
| Voice insertion | Added parenthetical, aside, humor |
| Structure change | Broke paragraph, reordered |
| Precision edit | Replaced vague with specific |
| Deletion | Removed fluff or decoration |
| Addition | Added context, example, anchor |
Read learning/accumulator.json:
{
"patterns": [
{
"id": "pat-001",
"category": "tone_adjustment",
"description": "Softens confident claims about tool capabilities",
"instances": [
{"piece": "blog-post-1", "date": "2026-04-08", "diff": "..."}
],
"target": "register",
"status": "accumulating",
"first_seen": "2026-04-08",
"last_seen": "2026-04-08"
}
],
"staleness_threshold_days": 30
}
Match new changes against existing patterns:
For patterns that reach threshold (3+ instances or 1-2 matching prior accumulator entries with 2+ instances):
## Proposed Update
**Pattern**: {description}
**Target**: {register file or craft-rules.md}
**Evidence**: {N instances across M pieces}
| Piece | Date | Change Made |
|-------|------|-------------|
| ... | ... | ... |
**Proposed edit**:
- File: {path}
- Section: {section name}
- Current: "{current text or 'new addition'}"
- Proposed: "{new text}"
Add to accumulator with current instances. Report:
Holding: "{pattern description}" (N instances, need 3+)
If a new pattern contradicts an existing accumulator entry:
Contradiction detected:
- Existing: "{accumulator pattern}"
- New: "{contradicting pattern}"
- Resolution required: user must choose
Present proposals to user:
Learning found N patterns ready to apply:
[1] {pattern}: {proposed change}
Evidence: {N instances}
[a]pply / [s]kip / [v]iew evidence?
[2] ...
Apply approved changes to the target files.
Patterns in the accumulator expire after staleness_threshold_days
(default 30). If a pattern hasn't recurred within that window,
it was likely a one-off preference rather than a voice trait.
On each learning pass, prune stale entries:
# Remove patterns older than threshold with < 3 instances
The learning system captures snapshots automatically when voice-review completes. Snapshot naming:
{piece-filename}-{YYYYMMDD-HHMMSS}-pre-review.md
{piece-filename}-{YYYYMMDD-HHMMSS}-post-review.md
{piece-filename}-{YYYYMMDD-HHMMSS}-post-edit.md
The post-edit snapshot is captured when the user runs
/voice-learn after finishing their manual edits.