feat: add keyword maintenance skill
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---
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name: reader-keyword-maintenance
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description: 维护 reader 项目的关键词 review 目录与低频清理 SOP。当用户要求清理或整理 reader 的关键词 review 目录、控制哪些产物长期保留、检查 suggestions JSON 是否可 apply、或执行“只保留当前 bundle / 仅保留最近少量 suggestions JSON / 删除旧 markdown”等低频维护动作时使用。不要用于正式关键词 review 生成，不要用于 reader 日报主链路。
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---
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# Reader Keyword Maintenance
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这个 skill 负责 reader 关键词治理里的**低频维护动作**，目标是把清理策略、展示稿生成、dry-run 校验和 review 目录维护从 reader 主链路里拆出来，由 OpenClaw 单独承接。
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## 角色边界
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这个 skill 负责：
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- 检查 `outputs/term_index/review/` 当前有哪些产物
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- 判断哪些 review 产物应长期保留、短期保留或可清理
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- 用 `apply_term_suggestions.py --dry-run` 做 apply 前校验
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- 执行低频清理和收尾动作
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这个 skill 不负责：
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- 正式生成关键词 review 建议
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- 充当 alias / stopword 正式 review 决策器
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- 替代 reader 侧的 `keyword-cleanup-review`
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如果用户要的是“做一轮正式关键词 review / 生成正式 suggestions JSON”，应由 OpenClaw 去调用 reader 侧 `keyword-cleanup-review`，而不是由本 skill 直接承担。
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## 适用场景
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当用户要求以下事情时使用：
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- 查看或解释 `reader/outputs/term_index/review/` 下有哪些文件
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- 清理旧的 review bundle、old suggestions、old markdown
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- 只保留当前 bundle 或最近少量 suggestions JSON
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- 检查 suggestions JSON 是否可被 `apply_term_suggestions.py` 消费
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- 执行一次人工 review 准备动作，但不改变 reader 主链路设计
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不要用于：
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- 日报正式生产运行
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- 生成 daily term index / term_stats 主链路
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- 自动写配置作为默认行为
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- 修改 reader 仓库里的主 SOP 作为低频维护动作的默认入口
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- 正式生成 alias / stopword / interest / watch 建议
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## 默认口径
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长期保留：
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- `data/term_index/daily/*.json`
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- `data/term_index/term_stats.json`
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- `configs/filter_context.personal.json`
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- `configs/term_watchlist.json`
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- `configs/term_aliases.json`
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- `configs/term_stopwords.json`
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- `configs/term_change_log.json`
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正式建议产物（短期保留）：
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- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.json`
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临时工作文件 / 展示层：
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- `outputs/term_index/review/keyword-cleanup-bundle.json`
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- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.md`
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更细的保留/清理判断，读取：
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- `references/cleanup-policy.md`
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## 固定 SOP
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### 1. 检查 review 目录
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- 查看 `outputs/term_index/review/` 当前有哪些文件
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- 分类成：
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- 长期保留
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- 短期保留
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- 临时工作文件
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### 2. 准备人工审阅
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- 确认最新 bundle 存在
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- 确认最新 suggestions JSON 存在
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- 如需正式生成 suggestions 或 Markdown 展示稿，应转到 reader 侧 `keyword-cleanup-review`
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### 3. dry-run 校验 apply
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- 仅通过 `scripts/apply_term_suggestions.py --dry-run` 校验 suggestions JSON 是否可消费
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- 不直接落配置
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### 4. 清理 review 产物
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- 删除旧 markdown 展示稿
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- 默认只保留当前/latest bundle
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- 保守清理旧 suggestions JSON
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- 不碰 facts/state/config files
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## 常用动作
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### 1. 验证 suggestions JSON 能否被 apply 消费
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```bash
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cd /home/ubuntu/zhu/github/reader && \
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/usr/bin/python3.11 scripts/apply_term_suggestions.py \
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--suggestions outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.json \
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--accept-interest "Claude Code" \
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--dry-run
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```
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## 清理策略
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保守策略：
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- bundle：默认只保留当前最新一份
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- markdown：默认不归档，需要时现生成
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- suggestions JSON：只保留最近少量几份或已应用过的记录
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## 维护原则
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- 优先减少中间产物，不要让 review 工作文件变成长期资产
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- JSON suggestions 是 review / apply 之间唯一正式输入
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- Markdown 只是展示层，不是系统真相
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- 任何清理动作前，先确认不会影响当前待审阅或待 apply 的 suggestions JSON
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- 正式关键词 review 的生成入口不在这里，而在 reader 侧 `keyword-cleanup-review`
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执行清理或 review-prep 前，先读取：
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- `references/maintenance-checklist.md`
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# Alias Review Example
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Use this as the default style reference when preparing a low-frequency alias review report.
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## Suggested merges
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- `Claude code -> Claude Code`
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- 理由：明显属于同一产品名，仅是大小写写法不一致。
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- 证据：`Claude Code` 在最近多日持续出现，而小写写法只是在少量上下文中作为变体出现。
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- `Sub-Agent -> SubAgent`
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- 理由：更像词形差异，不构成新的独立概念。
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- 证据：两者都围绕同一 agent 架构语境出现，且没有稳定区分语义。
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## Not recommended to merge
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- `Skills ↔ Agent Skills`
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- 理由：前者过泛，后者更具体，当前强行归并会损失粒度。
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- `Anthropic ↔ Claude`
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- 理由：公司名与产品名并不等价，不应直接视为一个关键词。
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## Needs human judgment
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- `AI助手 ↔ AI Agent`
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- 风险点：语义可能接近，但中文表述范围更宽，是否并入需要结合实际使用语境判断。
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## Style notes
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- Keep the report concise.
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- Give judgment first, then evidence.
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- Do not claim anything is already applied.
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- Prefer conservative proposals over broad semantic merging.
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# Cleanup Policy
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## Purpose
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This reference defines how `reader-keyword-maintenance` should treat keyword governance artifacts.
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The goal is to keep long-term assets small and stable while allowing review-time working files to exist when needed.
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This policy is for low-frequency maintenance only.
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It does not replace the formal keyword review generation flow in reader.
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## Artifact classes
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### Long-term assets
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Keep these by default:
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- `data/term_index/daily/*.json`
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- `data/term_index/term_stats.json`
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- `configs/filter_context.personal.json`
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- `configs/term_watchlist.json`
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- `configs/term_aliases.json`
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- `configs/term_stopwords.json`
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- `configs/term_change_log.json`
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These are facts or active state.
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### Short-term decision artifacts
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Keep selectively:
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- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.json`
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Recommended policy:
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- keep only recent few files, or
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- keep only files that were actually used for apply decisions
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### Temporary working/display files
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Treat as disposable unless the user explicitly asks to archive them:
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- `outputs/term_index/review/keyword-cleanup-bundle.json`
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- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.md`
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Recommended policy:
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- bundle: keep only latest current file
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- markdown: generate on demand, do not archive by default
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## Default maintenance actions
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### Safe checks
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Before deleting anything:
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1. confirm the target is not the current bundle under active review
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2. confirm the target suggestions JSON is not the one about to be applied
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3. never delete configs or facts during review cleanup
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### Safe cleanup order
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1. remove or overwrite old markdown display drafts
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2. keep only latest bundle file
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3. prune old suggestions JSON files conservatively
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## Decision rules
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### When user says "clean review artifacts"
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Default action:
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- keep facts/state untouched
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- keep current suggestions JSON
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- remove markdown drafts if they are old and clearly derived display files
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- keep bundle only as current working file
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### When user says "prepare manual review"
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Default action:
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- ensure latest bundle exists
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- ensure latest suggestions JSON exists
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- do not generate formal suggestions or markdown here by default
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- if the user wants formal review material, route to reader-side `keyword-cleanup-review`
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### When user says "review alias candidates" or "review stopword candidates"
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Default action:
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- explain that formal keyword review generation belongs to reader-side `keyword-cleanup-review`
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- keep this skill focused on maintenance, cleanup, display generation, and dry-run validation
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- only proceed here if the user explicitly wants a low-frequency maintenance view rather than the formal review flow
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### When user says "what can be deleted"
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Explain in three buckets:
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- must keep
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- can keep temporarily
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- safe to regenerate/delete
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## Non-goals
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This policy does not change reader production logic.
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It only governs low-frequency maintenance and cleanup decisions in OpenClaw.
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# Maintenance Checklist
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Use this checklist before doing any cleanup or review-maintenance action for reader keyword artifacts.
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## Pre-check
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1. Confirm the current repo root is `/home/ubuntu/zhu/github/reader`
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2. Confirm the user asked for a maintenance / cleanup / review-prep action
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3. If the user actually wants formal keyword review generation, route to reader-side `keyword-cleanup-review` instead of using this maintenance skill
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4. Identify whether the action targets:
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- current bundle
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- suggestions JSON
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- markdown display draft
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- old review outputs
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## Safety check
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Before deleting or overwriting anything:
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1. Do not touch:
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- `data/term_index/daily/*.json`
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- `data/term_index/term_stats.json`
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- `configs/filter_context.personal.json`
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- `configs/term_watchlist.json`
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- `configs/term_aliases.json`
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- `configs/term_stopwords.json`
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- `configs/term_change_log.json`
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2. Confirm the suggestions JSON to keep is not the one about to be applied
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3. Treat markdown drafts as disposable only after confirming they are display-only artifacts
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## Review-prep flow
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When preparing manual review:
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1. Ensure the latest bundle exists
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2. Ensure the latest suggestions JSON exists
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3. Generate markdown only if the user explicitly wants human-readable review material
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4. Prefer showing conclusions in chat before creating more files
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## Cleanup flow
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Recommended order:
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1. remove old markdown display drafts
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2. keep only the current/latest bundle
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3. prune old suggestions JSON conservatively
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4. leave facts/state/config untouched
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## Post-check
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After the action:
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1. verify the expected kept files still exist
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2. verify no config file was accidentally changed
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3. summarize what was kept vs removed
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Block a user