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作者: admin | 来源: ClawHub
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V 1.0.0
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fragments

# Fragments ## Setup Check 1. Read `~/.config/fragments.json` (Windows: `%USERPROFILE%\.config\fragments.json`). 2. If file missing → first install. Detect current platform, read the matching setup guide: - Claude Code → `references/setup-claude-code.md` - OpenCode → `references/setup-opencode.md` - OpenClaw → `references/setup-openclaw.md` 3. If file exists → verify MCP is configured. If incomplete → read the matching setup guide. 4. All good → proceed to normal usage. ## Platform Detection Detect the current platform by checking for platform-specific markers: | Platform | Detection Marker | |----------|------------------| | Claude Code | `~/.claude/` directory exists | | OpenCode | `~/.config/opencode/` directory exists | | OpenClaw | `~/.openclaw/` directory exists | ## Modes ### memo — Full Lifecycle Management Create, search, update, delete, and comment on memos via MCP tools. **Workflows:** - Create & dedup → `references/memo-capture.md` - Update & delete → `references/memo-capture.md#lifecycle` - Comments → `references/memo-comments.md` Write operations require user confirmation before calling. ### daily-log — Daily Work Journal One structured log per user per day. Content follows `.plan` format enforced by the Memos server. Format rules, diff-merge logic, and hook trigger workflow: → `references/daily-log.md` ### search — Semantic Search Server-side full-text retrieval via MCP, optional client-side TF-IDF + LSA rerank for semantic/fuzzy queries. Pipeline details and tuning parameters: → `references/search-strategy.md` ## Retrieval Strategy Data volume can be large. Always prefer targeted retrieval over bulk listing. ### Memos 1. **Search first**: `memos_search_memos(query=...)` — use when the user has any intent, keyword, or topic. Returns bounded results. 2. **Get by ID**: `memos_get_memo(name=...)` — use when you already know the memo name. Expand full content only for shortlisted results. 3. **List as fallback**: `memos_list_memos(page_size=10)` — use only for explicit "show recent" requests. Always set a small `page_size`. 4. **Client-side rerank**: pipe search results through `scripts/fragments_search.py` for semantic ranking when server-side results need refinement. ### Comments - **List comments**: `memos_list_memo_comments(name=...)` — retrieve all comments on a memo. Comments inherit the parent memo's visibility. ### Daily Logs 1. **Get by date**: `memos_get_daily_log(date=YYYY-MM-DD)` — single log lookup. Pass `creator="users/{id}"` to view another user's log (PROTECTED visibility). 2. **List with date range**: `memos_list_daily_logs(start_date, end_date, page_size=10)` — use only for explicit "show this week/month" requests. Always bound the range. ### Tags - `memos_list_tags` — lightweight, use to discover available tags for filtering. No read operations require user confirmation. ## Write Operations All write operations require explicit user confirmation before calling. Read operations need no confirmation. Never echo PAT tokens to the conversation. ### Memo Writes | Operation | MCP Tool | When to Use | |-----------|----------|-------------| | Create | `memos_create_memo` | New idea, note, snippet | | Update | `memos_update_memo` | Modify content, visibility, pin | | Delete | `memos_delete_memo` | Remove memo (irreversible) | | Add comment | `memos_create_memo_comment` | Append discussion to memo | ### Daily Log Writes - `memos_save_daily_log(date=..., content=...)` — full replacement save. Always include complete content (existing + new lines). ## Hook Workflow (Passive Trigger) When triggered by agent task completion: 1. Assess whether this session performed meaningful work. Skip if trivial. 2. Call `memos_get_daily_log` for today's date. 3. Format new entries in `.plan` style. 4. Diff against existing content. Skip if no new information. 5. Long-form content → suggest creating a memo first, reference in daily log. 6. Show user the full merged log (existing + new). Wait for confirmation. 7. Call `memos_save_daily_log` with complete content (full replacement).

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skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 fragments-1776057741 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 fragments-1776057741 技能

通过命令行安装

skillhub install fragments-1776057741

下载 Zip 包

⬇ 下载 fragments v1.0.0

文件大小: 17.56 KB | 发布时间: 2026-4-14 10:26

v1.0.0 最新 2026-4-14 10:26
Initial release of the "fragments" skill: fragmented work logging and idea capture via Memos, with structured and confirmable workflows.

- Capture, search, update, delete, and comment on memos via explicit triggers or passive agent hooks.
- Daily work journal in structured `.plan` format, with lifecycle management and integration into agent workflows.
- Advanced search features: semantic search, limited result sets, and client-side reranking.
- Platform autodetection (Claude Code, OpenCode, OpenClaw) and first-boot setup guidance.
- Enforces user confirmation for all write operations; read actions require none.

**MUST use docker image** https://hub.docker.com/repository/docker/deepshape/memos

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