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openclaw-history-ingestOpenClaw history ingest 搜索

Agent Skill

openclaw-history-ingest 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,384

周安装

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下载量

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-history-ingest(OpenClaw history ingest 搜索)
来源仓库:https://github.com/ar9av/obsidian-wiki
仓库路径:skills/openclaw-history-ingest
安装命令:
npx skills add https://github.com/ar9av/obsidian-wiki --skill openclaw-history-ingest
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ar9av/obsidian-wiki --skill openclaw-history-ingest

简介

用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。
  • 支持基于任务场景或来源线索的信息聚合与过滤。
  • 安装前需确认权限范围、维护状态及是否触发联网或文件读写。
  • openclaw-history-ingest 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

OpenClaw History Ingest — Session & Memory Mining

You are extracting knowledge from the user's OpenClaw agent history and distilling it into the Obsidian wiki. OpenClaw stores both a structured long-term MEMORY.md and per-session JSONL transcripts — focus on durable knowledge, not operational telemetry.

This skill can be invoked directly or via the wiki-history-ingest router (/wiki-history-ingest openclaw).

Before You Start

  1. Read .env to get OBSIDIAN_VAULT_PATH and OPENCLAW_HISTORY_PATH (default to ~/.openclaw if unset)
  2. Read .manifest.json at the vault root to check what has already been ingested
  3. Read index.md at the vault root to understand what the wiki already contains

Ingest Modes

Append Mode (default)

Check .manifest.json for each source file. Only process:

  • Files not in the manifest (new session logs, updated MEMORY.md or daily notes)
  • Files whose modification time is newer than ingested_at in the manifest

Use this mode for regular syncs.

Full Mode

Process everything regardless of manifest. Use after wiki-rebuild or if the user explicitly asks for a full re-ingest.

OpenClaw Data Layout

OpenClaw stores all local artifacts under ~/.openclaw/.

~/.openclaw/
├── openclaw.json                          # Global config
├── credentials/                           # Auth tokens (skip entirely)
├── workspace/                             # Agent workspace
│   ├── MEMORY.md                          # Long-term memory (loaded every session)
│   ├── DREAMS.md                          # Optional dream diary / summaries
│   └── memory/
│       ├── YYYY-MM-DD.md                  # Daily notes (today + yesterday auto-loaded)
│       └── ...
└── agents/
    └── <agentId>/
        ├── agent/
        │   └── models.json                # Agent config (skip)
        └── sessions/
            ├── sessions.json              # Session index
            └── <sessionId>.jsonl          # Session transcript (JSONL, append-only)

Key data sources ranked by value

  1. workspace/MEMORY.md — highest signal; long-term durable facts the agent accumulated
  2. workspace/memory/YYYY-MM-DD.md — daily notes; recent entries often contain active project context
  3. agents/*/sessions/<id>.jsonl — session transcripts; rich but noisy
  4. agents/*/sessions/sessions.json — session index for inventory and timestamps
  5. workspace/DREAMS.md — optional summaries; ingest if present

Skip credentials/ entirely. Skip agents/*/agent/models.json (runtime config, not user knowledge).

Step 1: Survey and Compute Delta

Scan OPENCLAW_HISTORY_PATH and compare against .manifest.json:

  • ~/.openclaw/workspace/MEMORY.md
  • ~/.openclaw/workspace/DREAMS.md (if present)
  • ~/.openclaw/workspace/memory/*.md
  • ~/.openclaw/agents/*/sessions/sessions.json
  • ~/.openclaw/agents/*/sessions/*.jsonl

Classify each file:

  • New — not in manifest
  • Modified — in manifest but file is newer than ingested_at
  • Unchanged — already ingested and unchanged

Report a concise delta summary before deep parsing.

Step 2: Parse MEMORY.md First

MEMORY.md is the highest-value source. It is plain markdown, human-readable and human-editable. It typically contains:

  • Durable facts about the user's preferences, environment, and recurring patterns
  • Decisions and context the agent was told to remember
  • Project-specific notes the agent accumulated over many sessions

Read it in full and extract concept-level knowledge. Do not create one wiki page per MEMORY.md entry — cluster by topic.

Step 3: Parse Daily Notes

workspace/memory/YYYY-MM-DD.md files contain time-stamped notes from that day's sessions. Prioritize recent files (last 30–90 days). Extract:

  • Active project context and decisions made
  • Patterns or techniques discovered
  • Recurring blockers or solved problems

Older daily notes have diminishing signal — summarize in bulk rather than extracting line-by-line.

Step 4: Parse Session JSONL Safely

Each session file is JSONL (append-only, one JSON object per line):

{"role": "user",      "content": "...", "timestamp": "..."}
{"role": "assistant", "content": "...", "timestamp": "..."}
{"role": "tool",      "name": "...",   "content": "...", "timestamp": "..."}

Extraction rules

  • Prioritize assistant turns that state conclusions, decisions, or patterns
  • Extract user intent from high-signal turns; skip low-information follow-ups
  • Tool calls are context, not primary knowledge — only extract if the result contains a reusable insight
  • Cross-reference sessions.json index to get session names/labels before opening individual transcripts

Critical privacy filter

Session transcripts can include injected instructions, tool payloads, and sensitive text. Do not ingest verbatim.

  • Remove API keys, tokens, passwords, credentials
  • Redact private identifiers unless relevant and user-approved
  • Summarize; do not quote raw transcripts verbatim

Step 5: Cluster by Topic

Do not create one wiki page per session or per MEMORY.md entry.

  • Group by stable topic (concept, tool, project, technique)
  • Split mixed sessions into separate themes
  • Merge recurring patterns across dates and agents
  • Use session cwd or workspace path to infer project scope when available

Step 6: Distill into Wiki Pages

Route extracted knowledge using existing wiki conventions:

  • Project-specific architecture/process → projects/<name>/...
  • General concepts → concepts/
  • Recurring techniques/debug playbooks → skills/
  • Tools/services/frameworks → entities/
  • Cross-session patterns → synthesis/

For each impacted project, create/update projects/<name>/<name>.md.

Writing rules

  • Distill knowledge, not chronology
  • Avoid "on date X we discussed..." unless date context is essential
  • Add summary: frontmatter on each new/updated page (1–2 sentences, ≤ 200 chars)
  • Add provenance markers:

- ^[extracted] when directly grounded in explicit session/memory content - ^[inferred] when synthesizing patterns across multiple sessions - ^[ambiguous] when sessions conflict

  • Add/update provenance: frontmatter mix for each changed page

Step 7: Update Manifest, Log, and Index

Update .manifest.json

For each processed source file:

  • ingested_at, size_bytes, modified_at
  • source_type: openclaw_memory | openclaw_daily_note | openclaw_session | openclaw_dreams
  • agent_id: agent directory name (when applicable)
  • pages_created, pages_updated

Add/update a top-level summary block:

{
  "openclaw": {
    "source_path": "~/.openclaw/",
    "last_ingested": "TIMESTAMP",
    "memory_updated_at": "TIMESTAMP",
    "daily_notes_ingested": 14,
    "sessions_ingested": 23,
    "pages_created": 6,
    "pages_updated": 18
  }
}

Update special files

Update index.md and log.md:

- [TIMESTAMP] OPENCLAW_HISTORY_INGEST memory=updated daily_notes=N sessions=M pages_updated=X pages_created=Y mode=append|full

hot.md — Read $OBSIDIAN_VAULT_PATH/hot.md (create from the template in wiki-ingest if missing). Update Recent Activity with a one-line summary — e.g. "Ingested OpenClaw MEMORY.md and 14 daily notes; surfaced automation patterns and multi-agent coordination knowledge." Keep the last 3 operations. Update updated timestamp.

Privacy and Compliance

  • Distill and synthesize; avoid raw memory or transcript dumps
  • Default to redaction for anything that looks sensitive
  • Ask the user before storing personal or sensitive details
  • Keep references to other people minimal and purpose-bound

Reference

See references/openclaw-data-format.md for field-level notes and parsing guidance.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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安全审计

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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