name: life-capture description: capture daily-life notes into markdown and sqlite. use when the user wants to record one or more life entries such as expenses, completed tasks, schedules, reminders, or ideas; classify the content; generate tags; parse natural language into structured json; write a daily markdown note under life/daily; and sync structured fields into a local sqlite database. triggers include short single-line entries, mixed sentences containing multiple record types, or requests to log and organize personal information for later review and reporting.
Turn natural-language life logs into durable records. This skill classifies each input item, generates tags, creates user-visible markdown, writes to a daily note under life/daily, and syncs structured data into life/db/life.db.
Use these paths unless the user explicitly overrides them:
life/
daily/
ideas/
db/life.db
Create missing directories as needed. Never delete existing content. Append or update only.
Map every parsed item to exactly one primary type:
expense: spending, bills, purchases, subscriptions, refundstask: completed tasks, ongoing work, todos, chores, habitsschedule: calendar items, appointments, time blocks, plansidea: ideas, inspiration, possible projects, reflections worth savingWhen a sentence contains multiple items, split it into multiple records.
For each user request:
id for each record using the pattern:exp_YYYYMMDD_NNNtask_YYYYMMDD_NNNsched_YYYYMMDD_NNNidea_YYYYMMDD_NNNscripts/process_entry.py.Always keep the original user wording in raw_text. Never invent missing fields. Leave unknown fields null.
Because this skill is configured for visible output, show a concise but complete result after writing:
## 已整理記錄
### 1) <type label>
- ID: <id>
- 標籤: #a #b
- 歸檔: <daily markdown path>
- 資料庫: <written/skipped>
#### Markdown
<the markdown block written for this item>
#### JSON
```json
<the parsed record json>
If there are multiple records, repeat the block for each one.
## Parsing rules
Use `scripts/parse_entries.py` for natural-language parsing. The parser now reads configurable rules from `references/parser_config.json`, so prefer editing that file instead of changing Python when you need new categories, tags, or keyword mappings.
### Expense
Extract when present:
- `amount`
- `currency` (default `CNY` only when the currency symbol or language implies RMB; otherwise null)
- `category`
- `subcategory`
- `merchant`
- `pay_method`
Default top-level tags often include `開銷` plus one semantic tag such as `餐飲` or `交通`.
Preferred categories:
- 飲食
- 交通
- 購物
- 居家
- 社交
- 娛樂
- 醫療
- 學習
- 其他
### Task
Extract when present:
- `status` (`todo`, `doing`, `done`, `cancelled`)
- `priority` (`low`, `normal`, `high`)
- `project`
- `due_date`
- `completed_at`
If the user says they already did something, default status to `done`.
### Schedule
Extract when present:
- `schedule_date`
- `start_time`
- `end_time`
- `location`
- `status` (`planned`, `done`, `skipped`)
If the user uses relative dates, resolve them from the current conversation date. Prefer passing `--today YYYY-MM-DD` to `scripts/process_entry.py` or `scripts/parse_entries.py` so relative dates like `明天` are stable across environments.
### Idea
Extract when present:
- `idea_type`
- `status` (`captured`, `reviewing`, `used`, `archived`)
- `related_task_id`
Default status to `captured`.
## Configurable parsing rules
Before editing Python, check whether the change can be made in `references/parser_config.json`.
You can change:
- category and subcategory mappings for expenses
- task project mappings
- idea type mappings
- schedule extra tag mappings
- default tags by record type
- hint regexes used in type inference
To test a modified config without changing the bundled default file:
```bash
python scripts/parse_entries.py --config /path/to/custom_config.json --text "買咖啡 18 元,明天下午兩點去體檢"
Write each record into the daily note for its effective date under one of these sections:
- ## 開銷
- ## 任務
- ## 日程
- ## 靈感
Use this block structure:
### <id>
- 時間:<time or empty>
- 標籤:#tag1 #tag2
- 原始描述:<raw_text>
- 摘要:<summary>
Then add type-specific fields:
Use this when the user provides natural language and wants the records saved immediately:
python scripts/process_entry.py --root life --db life/db/life.db --today 2026-03-10 --text "今天中午牛肉麵 26 元,下午整理了書桌,想到可以做一個生活資料看板"
The wrapper script will:
1. initialize the database if missing
2. parse text into {"records": [...]} with scripts/parse_entries.py
3. save markdown and sqlite rows with scripts/save_entry.py
4. print parsed records plus save results as json
Use this when the user asks to inspect or verify the structured output before writing:
python scripts/parse_entries.py --text "明天下午兩點去體檢,買咖啡 18 元"小蔥技能有更好的技能skills外掛。
Then save:
python scripts/save_entry.py --root life --db life/db/life.db --stdin-json
Use this once before first write if life/db/life.db does not exist and you are not using process_entry.py:
python scripts/init_db.py --db life/db/life.db
The database design is:
- entries
- expenses
- tasks
- schedules
- ideas
- tags
- entry_tags
See references/schema.md for the schema, references/examples.md for sample payloads and commands, and references/configuration.md plus references/parser_config.json for configurable parsing rules.
這是一款將日常碎碎念自動整理成有條理筆記的生活管理工具,表現相當不錯。它能準確識別消費、任務、日程、靈感等不同型別的記錄,自動分類打標,資料既容易閱讀也方便查詢。文件示例豐富,很快就能上手。美中不足的是,目前主要對中文支援較好,其他語言可能會識別不準。另外在多人同時使用時,記錄編號可能有小機率重複。總體來說質量不錯,日常使用完全沒問題。