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openclaw-workspaceOpenClaw workspace 搜索

Agent Skill

openclaw-workspace 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

44,550

周安装

1,875

GitHub Stars

2

下载量

15,363
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-workspace(OpenClaw workspace 搜索)
来源仓库:https://github.com/ivangdavila/openclaw-workspace
安装命令:
openclaw skills install openclaw-workspace
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-workspace

简介

审核和改进 OpenClaw 跨灵魂、代理和工具的工作空间。

  • 适用于角色调整、主动行为和记忆管理优化。
  • 支持工作流程适配和技能整合,提升整体性能。
  • 安装命令:openclaw skills install openclaw-workspace。
  • 需确认权限范围和维护状态,避免触发配置变更或数据访问。

SKILL.md

name
OpenClaw Workspace
slug
openclaw-workspace
version
1.0.0
homepage
https://clawic.com/skills/openclaw-workspace
description
Audit and improve OpenClaw workspaces across SOUL, AGENTS, TOOLS, USER, MEMORY, and skills for persona tuning, proactive behavior, recall, and workflow fit. Use when (1) the user wants to improve or analyze their workspace; (2) they want the agent to become more proactive, sharper, or better organized; (3) they ask how to change soul, agent behavior, memory, tools, or skills; (4) they want workspace improvements based on prior conversations.
changelog
Clarified activation wording so the skill is picked more reliably for broad workspace improvement requests.
metadata
{"clawdbot":{"emoji":"🧩","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

When to Use

Use when the user wants to improve, audit, debug, redesign, or understand their OpenClaw workspace as a working system, not as isolated files.

This skill should also activate when the user asks why the agent behaves a certain way, how to make it more proactive, how to improve recall, how to tune tone or autonomy, or how to evolve the workspace from prior conversations.

If the request is broad or the user does not know where to start, default to proposing a deep workspace audit first.

Improvement Surface

LayerImprove Here WhenWhat Good Looks Like
SOUL.mdTone, personality, confidence, warmth, bluntness, humor, tasteThe agent sounds intentional, stable, and human rather than generic
IDENTITY.mdName, vibe markers, stable self-description, outward identity cuesThe agent presents itself consistently across channels and sessions
AGENTS.mdStartup behavior, work style, boundaries, proactivity, escalation rulesThe agent starts strong, acts resourcefully, and stays inside clear operating rules
TOOLS.mdTool usage conventions, local notes, operating hints, environment quirksThe agent uses available tools better without pretending new tools exist
USER.mdStable facts about the human, context, preferences, identity cuesThe agent adapts to the person without building a creepy dossier
MEMORY.mdDurable lessons, recurring priorities, long-term preferences, important factsMain-session recall is sharp without becoming bloated or stale
memory/ daily notesRecent context, fresh changes, current projects, recent mistakes or winsThe agent can reason from recency instead of relying only on old summaries
HEARTBEAT.mdRecurring checks, proactive follow-through, idle-time maintenanceProactivity feels useful and timely instead of noisy
skills/Capability gaps, reusable playbooks, domain-specific operating rulesRepeated problems move out of ad hoc prompting and into reusable skill behavior

Core Rules

1. Default to Deep Audit Mode for Broad Workspace Requests

  • If the user says "improve my workspace", "analyze my workspace", "why is my agent like this", or anything equally broad, start by proposing a deep audit.
  • A deep audit should inspect the current workspace stack, recent memory evidence, active behavior patterns, and the biggest friction points before prescribing changes.
  • If the user already names a target such as proactivity, memory, tone, or tools, audit that layer first but still map likely side effects on adjacent layers.
  • The default audit order is: bootstrap behavior files first, then memory evidence, then skills, then concrete improvement proposals.
  • A good audit ends with three outputs: what is driving the current behavior now, what is misaligned, and the smallest diffs that would materially improve it.

2. Diagnose by Layer Instead of Giving Generic Advice

  • Do not give vague "make it more proactive" or "improve memory" advice without locating which file or mechanism controls that behavior.
  • Voice and personality belong in SOUL.md.
  • Stable self-presentation and identity markers belong in IDENTITY.md.
  • Startup routines, decision defaults, red lines, escalation rules, and proactive behavior belong in AGENTS.md and sometimes HEARTBEAT.md.
  • Tool notes belong in TOOLS.md.
  • Human-specific context belongs in USER.md.
  • Durable recall belongs in MEMORY.md, while recent raw context belongs in memory/ daily files.
  • Repeated domain workflows belong in skills, not in bloated root files.

3. Use Prior Conversations as Primary Evidence

  • Before proposing workspace changes from history, search existing memory first rather than guessing from the current message alone.
  • Use memory_search on MEMORY.md plus memory/*.md whenever the question depends on previous preferences, recurring mistakes, deadlines, people, or long-running work.
  • If transcript-backed recall is available, use recent session evidence to identify repeated friction, repeated user corrections, and patterns worth turning into workspace rules.
  • If transcript recall is not available, say so plainly and propose the smallest safe upgrade path for conversation-based improvement instead of pretending the evidence exists.

4. Keep Bootstrap Files High-Leverage and Compact

  • AGENTS.md, SOUL.md, and TOOLS.md are bootstrap context, so every line should earn its place.
  • Keep identity, startup, boundaries, and execution defaults in root files; move heavy procedures, niche runbooks, and long examples into skills or narrower supporting files.
  • If behavior is inconsistent, first check for prompt bloat, duplicate rules, contradictory instructions, and stale sections before adding more text.
  • Prefer one sharp rule in the right file over five overlapping paragraphs across the workspace.

5. Make the Smallest Change That Fixes the Behavior

  • Tune the specific layer that owns the problem instead of rewriting the whole workspace.
  • Personality issues should not trigger a memory rewrite.
  • Identity presentation issues should not trigger an AGENTS rewrite if IDENTITY.md is the real owner.
  • Memory drift should not trigger a SOUL rewrite.
  • Missing capability should not be patched into AGENTS.md if it belongs in a skill.
  • When proposing improvements, show concrete diffs or exact replacement blocks and explain the expected behavioral change, not just the file destination.

6. Tune Proactivity With Boundaries, Not With Vibes

  • "Be more proactive" is not enough; define what the agent should notice, when it should act, and when it must ask first.
  • Use AGENTS.md for general proactive stance and HEARTBEAT.md for recurring checks, follow-through, and quiet-time behavior.
  • Separate internal initiative from external action: reading, organizing, checking, and drafting can often be proactive; messaging, spending, deleting, scheduling, or publishing usually still need approval.
  • If a workspace feels passive, look for missing startup rules, no heartbeat loop, weak next-step behavior, and missing recovery patterns before adding louder wording.

7. Respect Privacy, Session Boundaries, and Real Platform Behavior

  • MEMORY.md is high-trust personal context and should be treated more carefully than general workspace notes.
  • Do not recommend copying private long-term memory into shared-context behavior files unless the user explicitly wants that tradeoff.
  • TOOLS.md does not grant new tool access; it only improves how the agent uses tools that already exist.
  • Conversation-driven upgrades must respect storage, privacy, and operational cost tradeoffs when enabling broader recall.
  • Never recommend hidden workspace rewrites; improvements should be explicit, reviewable, and tied to a concrete reason.

Common Traps

TrapWhy It FailsBetter Move
Stuffing everything into AGENTS.mdBootstrap context becomes noisy, contradictory, or truncatedKeep AGENTS.md lean and move specialized behavior into skills or tighter files
Treating SOUL.md as an execution manualPersonality and execution policy get mixed into one unstable blobKeep SOUL.md about identity and tone; keep operating rules in AGENTS.md
Ignoring IDENTITY.mdName, vibe, and self-presentation drift across contextsKeep stable identity markers in IDENTITY.md instead of scattering them
Using TOOLS.md to "enable" toolsThe agent still only has the tools granted by runtime policyUse TOOLS.md for usage hints, local conventions, and caveats only
Putting durable preferences into daily notesImportant context gets buried in recency noisePromote stable patterns into MEMORY.md or USER.md
Putting current project churn into MEMORY.mdLong-term memory becomes stale, bloated, and low-signalKeep fresh work in memory/ daily files and periodically distill it
Making proactivity broader without boundariesThe agent becomes noisy, interruptive, or riskyDefine trigger conditions, quiet hours, and approval boundaries explicitly
Auditing without conversation evidenceRecommendations sound generic and miss repeated user painSearch memory first, then propose changes backed by actual patterns
Enabling wider recall without explaining tradeoffsUsers get surprise storage, privacy, or cost consequencesExplain exactly what gets indexed, why, and what the user gains

Default Audit Output

When running the default deep audit, produce a compact improvement packet:

  1. Current behavior map:

which files are actually driving tone, startup, memory, proactivity, and capabilities right now

  1. Evidence:

repeated user requests, recurring frictions, stale rules, duplication, or missing layers

  1. Recommended changes:

low-risk, medium-risk, and structural improvements with exact target files

  1. Suggested next move:

review diffs, apply one layer only, or run a full workspace cleanup

Do not end with generic advice alone. The user should leave with a real plan tied to specific workspace files.

Related Skills

Install with clawhub install <slug> if user confirms:

  • analysis - Run workspace and system audits with prioritized findings and remediation
  • proactivity - Tune initiative, follow-through, and heartbeat behavior
  • memory - Design deeper storage systems when built-in memory is not enough
  • self-improving - Turn repeated corrections into durable operating improvements

Feedback

  • If useful: clawhub star openclaw-workspace
  • Stay updated: clawhub sync

适合场景

01

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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

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能力概览

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能力 2

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能力 3

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能力 4

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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

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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

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