OpenclawContinuousWork 1.0.0

全面优化 OpenClaw 对话体验并强化任务闭环执行。Use when user asks to 优化, 工作, 项目, 持续工作, 不要停, 继续做, 继续工作, 或希望助手接收指令后持续推进直到完成。Also use when the user asks for complete optimization...

Security Scan

The skill's code and docs largely match a module-optimization purpose, but its runtime instructions demand aggressive, persistent autonomous behavior and allow scripted modifications of arbitrary files without explicit safeguards — this mismatch raises concern.

Purpose & Capability

Name/description (continuous optimization) aligns with the included scripts and markdown modules: the bundle contains tools to audit, re-index, graph, detect conflicts, normalize encoding, and run a one-command pipeline. However, the SKILL.md emphasizes changing dialog behavior and continuous autonomous execution at the assistant level while the code operates on repository files; this dual focus (agent behavioral directives + file-modifying maintenance scripts) is plausible but worth noting.

Instruction Scope

SKILL.md and References/ContinuousExecutionDirective.md push the agent to 'continuously execute until user confirms termination' and require 10-minute progress reports. The OptimizationDirective explicitly allows modifications/deletions/additions. The provided scripts will rewrite files (e.g., NormalizeEncoding.py, BuildReferenceMap.py, BuildModuleGraph.py) and operate recursively on a user-specified target path. There are no in-band safeguards (no confirmations, no target-restriction) described in SKILL.md, so the agent could be instructed to make broad destructive changes or run indefinitely without further human confirmation.

Install Mechanism

No external install spec or remote downloads; all code is bundled as local Python scripts. This is low install-risk because no external archive/binary is fetched. Scripts are readable and straightforward (no obfuscated code or network calls).

Credentials

The skill declares no environment variables or external credentials, which is consistent. However, it implicitly requires read/write access to the agent workspace and arbitrary target paths (the pipeline accepts a target path and will traverse and rewrite files). Given that OptimizationDirective permits modifying/deleting/adding files, that level of filesystem access is significant and not constrained by the SKILL.md (no explicit requirement that target be limited to the skill's own repo).

Persistence & Privilege

always is false (good), but SKILL.md contains strong directives that the agent should not stop until user confirmation and should report every 10 minutes. Because the platform allows autonomous invocation by default, these behavioral constraints could cause prolonged autonomous activity. That combination (autonomy + explicit 'do not stop' directive + file-modifying scripts) increases the blast radius compared to a self-contained helper.

What to consider before installing

This skill appears to implement a continuous 'optimization' workflow by scanning and modifying markdown and text files and by instructing the assistant to run persistently. Before installing or enabling it, consider: 1) Run the scripts on a read-only copy or isolated test workspace first to verify what they change (NormalizeEncoding, BuildReferenceMap, RunOptimizationPipeline will write files). 2) Confirm how the agent will be invoked autonomously — request or enforce that the agent must ask for explicit user confirmation before any write/delete operation or before entering a continuous execution mode. 3) If you don't want long-running autonomous behavior, disable autonomous invocation for this skill or remove/soften the 10-minute automatic-report and 'do not stop' directives in SKILL.md. 4) Request that the maintainer add explicit safeguards: a required, validated target whitelist, dry-run mode by default, and interactive prompts for destructive changes. 5) If you lack confidence in the maintainer, avoid granting this skill write access to important directories or run it only in a sandbox.

OpenClaw Continuous Work

Goal

• 连续推进：接到指令后持续执行直到完成。
• 优化闭环：优化任务必须全链路落地并回归验证。
• 稳定反馈：里程碑 + 时间触发进度汇报，避免沉默或刷屏。

Rule Map

• 规则总览（自动索引）：References/ReferenceMap.md
• 模块化规范：References/ModuleSystem.md
• 模块加载顺序配置：References/ModuleOrder.json

Core Modules

• 通用连续执行规则：References/GeneralRules.md
• 持续执行强约束：References/ContinuousExecutionDirective.md
• 优化任务专项规则：References/OptimizationRules.md
• 优化指令原文基线：References/OptimizationDirective.md
• 汇报模板：References/ReportingTemplate.md
• 优化清单：References/OptimizationChecklist.md
• 验收模板：References/AcceptanceTemplate.md
• 质量评分：References/QualityRubric.md

Scripts

• 一键优化流水线：Scripts/RunOptimizationPipeline.py
  • 用法：python Scripts/RunOptimizationPipeline.py <target_path>
  • 作用：串联执行命名巡检、内容/链接巡检、索引重建并输出汇总结果。
• 命名规范巡检：Scripts/NamingAudit.py
  • 用法：python Scripts/NamingAudit.py <target_path> --json
  • 作用：扫描命名不符合“单词首字母大写”规则的文件/文件夹并给出建议。
• 模块顺序校验：Scripts/ValidateModuleOrder.py
  • 用法：python Scripts/ValidateModuleOrder.py
  • 作用：校验 References/ModuleOrder.json（缺失模块、重复项、冲突项），输出 ModuleOrderReport.md/json。
• 模块索引重建：Scripts/BuildReferenceMap.py
  • 用法：python Scripts/BuildReferenceMap.py
  • 作用：自动重建 References/ReferenceMap.md，让新增 MD 模块即时纳入索引。
• 模块依赖图构建：Scripts/BuildModuleGraph.py
  • 用法：python Scripts/BuildModuleGraph.py
  • 作用：自动生成 References/ModuleGraph.md 与 References/ModuleGraph.json。
• 规则冲突巡检：Scripts/DetectRuleConflicts.py
  • 用法：python Scripts/DetectRuleConflicts.py
  • 作用：自动生成 References/ConflictReport.md 与 References/ConflictReport.json。
• 内容去重与链接巡检：Scripts/ContentLinkAudit.py
  • 用法：python Scripts/ContentLinkAudit.py <target_path> --json
  • 作用：检测重复段落与失效 Markdown 链接，支持持续精简与联动。
• 编码规范化：Scripts/NormalizeEncoding.py
  • 用法：python Scripts/NormalizeEncoding.py
  • 作用：统一文本文件为 UTF-8（无 BOM）+ LF，降低写入与解析报错风险。

Maintainer Notes

• 新增场景优先写入 References/，保持本文件精简。
• 优先扩展：触发词、失败升级策略、完成判定与验收模板。