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chore: update term configs, skill docs and Python 3.10 compat

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- term_change_log: record watch term add history
- term_watchlist: add initial watch terms from cleanup review
- term_aliases: minor update
- filter_context.personal: reorganize interest keywords
- keyword-cleanup-review skill: clarify JSON as formal artifact, markdown as temp review copy
- openclaw_delivery: add Python <3.11 UTC import compat
- daily-keyword-index-design: update suggestion artifact semantics
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2026-04-14 09:51:57 +08:00
parent c0194647d8
commit a06f2a1d08
7 changed files with 253 additions and 38 deletions
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configs/filter_context.personal.json
+25 -20
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@@ -23,34 +23,39 @@
"前沿科技"
],
"interest_keywords": [
"Java",
"Go",
"Python",
"Spring",
"Agent",
"Agent Skills",
"AgentScope",
"AI Agent",
"AliSQL",
"Claude Code",
"DeepSeek",
"FastAPI",
"Gin",
"Go",
"gRPC",
"MySQL",
"PostgreSQL",
"Redis",
"Java",
"Kafka",
"微服务",
"可观测性",
"Kubernetes",
"云原生",
"AI Agent",
"Agent",
"LLM",
"RAG",
"MCP",
"Prompt Engineering",
"Workflow",
"向量数据库",
"知识库",
"MySQL",
"MySQL复制延迟",
"OpenAI",
"DeepSeek",
"OpenClaw",
"AliSQL",
"MySQL复制延迟"
"PostgreSQL",
"Prompt Engineering",
"Python",
"RAG",
"ReActAgent",
"Redis",
"Spring",
"SubAgent",
"Workflow",
"云原生",
"可观测性",
"向量数据库",
"微服务",
"知识库"
]
}
configs/term_change_log.json
+101 -1
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@@ -1,4 +1,104 @@
{
"schema_version": "v1",
"entries": []
"entries": [
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_watch_term",
"term": "A2A",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=0.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_watch_term",
"term": "Agentic Loop",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=1.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_watch_term",
"term": "AI Gateway",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=1.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_watch_term",
"term": "Claude Skills",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=1.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_watch_term",
"term": "Cron",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=0.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_watch_term",
"term": "CoPaw",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=0.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_interest_keyword",
"term": "Claude Code",
"reason": "Meets the configured interest-keyword review threshold and is not yet covered by interest keywords or stopwords. Evidence: total_count=7, days_seen=4, recent_count=4.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_interest_keyword",
"term": "Agent Skills",
"reason": "Meets the configured interest-keyword review threshold and is not yet covered by interest keywords or stopwords. Evidence: total_count=6, days_seen=3, recent_count=0.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_interest_keyword",
"term": "SubAgent",
"reason": "Meets the configured interest-keyword review threshold and is not yet covered by interest keywords or stopwords. Evidence: total_count=4, days_seen=4, recent_count=2.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_interest_keyword",
"term": "AgentScope",
"reason": "Meets the configured interest-keyword review threshold and is not yet covered by interest keywords or stopwords. Evidence: total_count=4, days_seen=4, recent_count=1.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
},
{
"applied_at": "2026-04-08T02:34:14.194320Z",
"action": "add_interest_keyword",
"term": "ReActAgent",
"reason": "Meets the configured interest-keyword review threshold and is not yet covered by interest keywords or stopwords. Evidence: total_count=3, days_seen=3, recent_count=1.",
"suggestions_path": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"suggestion_date": "2026-04-08",
"based_on_days": 7
}
]
}
configs/term_watchlist.json
+45 -2
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@@ -1,5 +1,48 @@
{
"schema_version": "v1",
"updated_at": "2026-03-27T00:00:00Z",
"terms": []
"updated_at": "2026-04-08T02:34:14.194320Z",
"terms": [
{
"term": "A2A",
"added_at": "2026-04-08T02:34:14.194320Z",
"source": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=0.",
"status": "watching"
},
{
"term": "Agentic Loop",
"added_at": "2026-04-08T02:34:14.194320Z",
"source": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=1.",
"status": "watching"
},
{
"term": "AI Gateway",
"added_at": "2026-04-08T02:34:14.194320Z",
"source": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=1.",
"status": "watching"
},
{
"term": "Claude Skills",
"added_at": "2026-04-08T02:34:14.194320Z",
"source": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=1.",
"status": "watching"
},
{
"term": "CoPaw",
"added_at": "2026-04-08T02:34:14.194320Z",
"source": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=0.",
"status": "watching"
},
{
"term": "Cron",
"added_at": "2026-04-08T02:34:14.194320Z",
"source": "outputs/term_index/review/term-cleanup-suggestions-2026-04-08.json",
"reason": "Falls into the configured watch-term review range and should be observed before promotion into interest keywords. Evidence: total_count=2, days_seen=2, recent_count=0.",
"status": "watching"
}
]
}
docs/design/daily-keyword-index-design.md
+17 -4
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@@ -326,8 +326,13 @@ LLM 可以帮助做清洗建议，但不适合直接维护主词元库。
skill 不直接修改配置文件，而是生成建议文件，例如：
- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.md`
- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.json`
- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.md`
其中建议语义为：
- JSON 是 review / apply 之间的唯一正式建议产物
- Markdown 是人工临时审阅展示稿，不是长期真相来源
低复杂治理层建议补充三类输入：
@@ -403,8 +408,9 @@ skill 不直接修改配置文件，而是生成建议文件，例如：
2. 程序更新 `daily/YYYY-MM-DD.json`
3. 程序更新 `term_stats.json`
4. 每周或人工触发一次词元清洗 skill
5. skill 输出建议
6. 人工确认后再更新配置文件
5. skill 生成 suggestions JSON（正式建议产物）
6. 如需要人工阅读，再临时生成 Markdown 展示稿
7. 人工确认后再更新配置文件
## 14. 与规则引擎的关系
@@ -445,7 +451,8 @@ skill 不直接修改配置文件，而是生成建议文件，例如：
再补治理层：
- 增加词元清洗 skill
- 输出建议文件
- 输出建议文件（以 JSON 为正式产物）
- Markdown 仅作为按需生成的人工展示层
- 人工确认后更新配置
### Phase 3
@@ -459,3 +466,9 @@ skill 不直接修改配置文件，而是生成建议文件，例如：
## 16. 一句话结论
这套设计选择“只统计日报中的 `keywords`，由程序维护轻量词元库，再由独立 skill 周期性做清洗建议”，目的是在控制数据规模的前提下，为规则配置和长期兴趣演化提供稳定、可审计、可扩展的基础设施。
补充的产物策略是：
- facts/state 长期保留
- suggestions JSON 作为正式建议产物短期保留
- review bundle 与 Markdown 展示稿降级为临时工作文件 / 展示层
skills/keyword-cleanup-review/SKILL.md
+55 -6
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@@ -9,7 +9,7 @@ description: 审查和整理本仓库的每日关键词索引和频率统计。
## 工作流程
1. 构建精简的审查数据包：
1. 构建精简的审查数据包（临时工作文件）：
```bash
python skills/keyword-cleanup-review/scripts/build_review_bundle.py
@@ -21,15 +21,32 @@ python skills/keyword-cleanup-review/scripts/build_review_bundle.py
- `--top 50`
- `--output outputs/term_index/review/keyword-cleanup-bundle.json`
2. 阅读生成的数据包和建议模式：
2. 阅读建议模式：
- `outputs/term_index/review/keyword-cleanup-bundle.json`
- `skills/keyword-cleanup-review/references/suggestion-schema.md`
3. 生成两份输出：
3. 运行 suggestions 生成脚本：
- 一份简短的供人工审阅的 Markdown 报告
- 一份符合模式的 JSON 建议文件
```bash
python scripts/generate_term_cleanup_suggestions.py ^
--bundle outputs/term_index/review/keyword-cleanup-bundle.json
```
默认生成：
- 一份符合模式的 JSON 建议文件（正式建议产物）
如需人工审阅展示稿，再显式加：
```bash
python scripts/generate_term_cleanup_suggestions.py ^
--bundle outputs/term_index/review/keyword-cleanup-bundle.json ^
--emit-markdown
```
这时才会额外生成：
- 一份简短的供人工审阅的 Markdown 报告（临时展示稿）
4. 严格保持边界：
@@ -78,10 +95,41 @@ Markdown 输出应：
- 分类别名、停用词、兴趣关键词和关注词建议
- 用简短、具体的句子解释理由
说明：Markdown 主要用于人工临时审阅，不必默认当作长期资产保留。
JSON 输出应遵循：
- `references/suggestion-schema.md`
说明：JSON 是 review / apply 之间的唯一正式建议产物，应优先保留。
## 产物保留策略
长期保留：
- `data/term_index/daily/*.json`
- `data/term_index/term_stats.json`
- `configs/filter_context.personal.json`
- `configs/term_watchlist.json`
- `configs/term_aliases.json`
- `configs/term_stopwords.json`
- `configs/term_change_log.json`
短期保留：
- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.json`
临时产物：
- `outputs/term_index/review/keyword-cleanup-bundle.json`
- `outputs/term_index/review/term-cleanup-suggestions-YYYY-MM-DD.md`
默认执行口径：
- bundle 只作为运行时工作文件，默认只保留当前最新一份
- Markdown 只作为人工展示层，优先按需生成，不默认长期归档
- JSON suggestions 是 review / apply 之间唯一正式建议输入
## 仓库说明
当前仓库行为：
@@ -98,5 +146,6 @@ JSON 输出应遵循：
- 脚本：
- `scripts/build_review_bundle.py`
- `scripts/generate_term_cleanup_suggestions.py`
- 参考文档：
- `references/suggestion-schema.md`
src/summary_mcp/models/openclaw_delivery.py
+6 -1
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@@ -1,6 +1,11 @@
from __future__ import annotations
from datetime import UTC, date, datetime
try:
from datetime import UTC, date, datetime
except ImportError: # Python < 3.11 compatibility
from datetime import timezone, date, datetime
UTC = timezone.utc
from pydantic import BaseModel, Field