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openclaw-session-recallOpenClaw session recall 搜索

Agent Skill

openclaw-session-recall 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

8,274

周安装

338

GitHub Stars

公开资料未说明

下载量

2,650
OpenClaw

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

MIT-0

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-session-recall(OpenClaw session recall 搜索)
来源仓库:https://github.com/hchen13/openclaw-session-recall
安装命令:
openclaw skills install openclaw-session-recall
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install openclaw-session-recall

简介

搜索历史会话以恢复丢失的对话上下文与任务背景。openclaw-session-recall 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适用于新会话或消息较少时重建用户意图与历史关联。
  • 支持关键词匹配与语义相似度检索,提高召回准确性。
  • 需访问本地会话数据库或日志文件,注意权限与数据脱敏。
  • 恢复内容应结合当前会话综合判断,避免过度依赖旧上下文。

SKILL.md

name
session-recall
description
Search past session transcripts to recover lost conversation context. MUST use when: (1) the current session is new or has very few messages AND the user's message assumes shared context you don't have (they reference people, events, decisions, or topics not present in your current context), (2) user explicitly refers to a previous conversation ('continue where we left off', 'as we discussed', 'remember when...'), (3) you need to find a specific past discussion by keyword or time range. Key signal: if you find yourself about to reply 'I don't have context' or 'which topic are you referring to' — use this skill FIRST before asking the user to repeat themselves.

Session Recall

Search OpenClaw session transcript JSONL files to locate past conversations. Returns file paths and line numbers — read the relevant lines yourself to recover context.

When to Use

  • Missing context signal: Current session is new/short AND the user's message references people, events, decisions, or topics not present in your context — they clearly assume you know something you don't
  • Explicit recall: User says things like "continue where we left off", "as we discussed", "remember when we talked about..."
  • Self-check: You're about to reply "I don't have context" or "which topic are you referring to" — stop and use this skill first before asking the user to repeat themselves
  • You need to find when/where a specific topic was discussed

Commands

List available agents

Discover which agent IDs exist and how many sessions each has:

python3 SKILL_DIR/scripts/session-recall.py agents

Use this to find valid agent IDs before searching. Your own agent ID is typically visible in your session key (e.g. agent:myagent:... → agent ID is myagent).

List recent sessions

Show sessions with time range, turn count, and first message preview:

python3 SKILL_DIR/scripts/session-recall.py list --agent AGENT_ID --start 48h --limit 10

Output example:

/path/to/session.jsonl  [03-08 02:15 ~ 03:35]  32 turns  "Can you look into the impact of..."

Use this when the user's query is vague — scan previews to identify the right session, then read into it.

Search by keyword

Find specific mentions across transcripts:

python3 SKILL_DIR/scripts/session-recall.py search "keyword" --agent AGENT_ID --start 7d --limit 20

Output example:

/path/to/session.jsonl:142  [03-08 02:15] user: ...the keyword appears here in context...

The number after : is the line number. Use read --offset LINE --limit 30 to read surrounding context.

Time Parameters

--start and --end define the time window for filtering sessions.

FormatExampleMeaning
Relative duration30m, 6h, 2d, 1w, 3moMinutes/hours/days/weeks/months ago
Absolute date2026-03-01, 03-01Specific date (midnight)
Absolute datetime2026-03-01T14:00Specific date and time
Keywordtoday, yesterdayStart of today/yesterday
  • --start 7d → sessions from the last 7 days
  • --start 2026-02-01 --end 2026-02-28 → sessions within February
  • --end yesterday → sessions before today
  • Omit --end to include everything up to now
  • Omit both to search all time

Pagination

Use --offset and --limit to paginate through results:

# First page
session-recall list --start 30d --limit 10
# Second page
session-recall list --start 30d --limit 10 --offset 10
# Third page
session-recall list --start 30d --limit 10 --offset 20

The tool prints Showing X-Y of Z when there are more results beyond the current page.

All Parameters

ParameterDescription
--agentAgent ID. Run session-recall agents to list available IDs. Omit to search all.
--startStart of time window. Accepts durations, dates, datetimes, or keywords.
--endEnd of time window. Same formats as --start. Omit for "up to now".
--limitMax results per page. Default: 20 for list, 30 for search.
--offsetSkip N results for pagination. Default: 0.

Workflow

  1. Detect continuity intent — user implies prior context you don't have
  2. Try list first — scan session previews to narrow down candidates
  3. Then search if you have keywords, or pick a session from the list
  4. read the file at the returned line numbers (offset/limit) to load context
  5. Continue the conversation with recovered context

Important Notes

  • Replace SKILL_DIR with the actual skill directory path when calling
  • Only search your own agent's sessions by default
  • The tool does NOT use LLM — it's pure text search, fast and free
  • For vague queries with no keywords: use list, scan previews, then read promising sessions
  • Large sessions may have hundreds of lines — read selectively, don't load entire files
  • Use --offset to paginate when --limit doesn't cover all results

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

94.81%
按下载量换算2,512

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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来源信息

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