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daily-loop-runner每日循环跑步者

Agent Skill

daily-loop-runner 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

3,444

周安装

138

GitHub Stars

公开资料未说明

下载量

1,115
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:daily-loop-runner(每日循环跑步者)
来源仓库:https://github.com/sunbinnju-star/daily-loop-runner
安装命令:
openclaw skills install daily-loop-runner
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 daily-loop-runner

简介

为单个项目运行受控每日循环,支持计划启动与结束后恢复。

  • 适用于项目管理、实验迭代或重复性工作流自动化。
  • 内置状态持久化机制,确保中断后可继续执行。
  • 安装命令:openclaw skills install daily-loop-runner。
  • 使用前请验证项目配置文件语法正确,防止循环逻辑错误。

SKILL.md

name
daily-loop-runner
description
Run one controlled daily project loop for a single active project. Use on: scheduled daily runs, planner-initiated project steps, resuming a project after cleanup, user requests for active project advancement. Triggered when a project needs to advance by one meaningful step per day.

Daily Loop Runner

Advance one project by one meaningful step per loop. State read before execution, structured writeback after.

Input

Required:

  • project_card — full project card with current state, goals, blockers
  • latest_weekly_review — most recent weekly review notes
  • recent_daily_logs — list of recent daily loop logs (last 3-5)
  • open_questions — unresolved questions from previous loops

Optional:

  • forced_bottleneck — override automatic bottleneck selection

Output Schema

today_objective: string               # one clear goal for today
selected_agent: string | null         # which agent or tool will execute
task_input: object                    # structured input for the selected agent
expected_output: string                # what success looks like
execution_summary: string             # what actually happened
findings: string[]                    # key discoveries
decisions: string[]                   # decisions made based on findings
next_action: string | null            # what to do tomorrow
project_card_updates: object          # fields to update on project card
writeback_payload: object             # structured record for project memory
safe_to_proceed: boolean              # false if state was incomplete

Hard Rules

  1. One project per run. Do not split focus.
  2. One bottleneck per run. Pick the most critical blocker.
  3. One main action per run. One meaningful step, not a sprint.
  4. No execution without state read. Always read project_card and recent logs first.
  5. No successful completion without next_action. Every loop must feed into the next.

Loop Phases

Phase 1: State Read

  • Read project_card fully
  • Read recent_daily_logs
  • Note open_questions from previous runs
  • Identify current project phase and milestone

Phase 2: Bottleneck Selection

  • Pick the single most critical bottleneck
  • If forced_bottleneck provided, use it
  • If nothing is blocking, advance the primary goal

Phase 3: Task Input Construction

  • Build a focused task_input for the selected agent
  • Include: what to do, why it matters, what success looks like
  • Exclude: everything else

Phase 4: Execution

  • Dispatch task to selected agent
  • Wait for execution_summary and findings

Phase 5: Writeback

  • Update project_card with project_card_updates
  • Write execution_summary + findings to daily log
  • Populate next_action for tomorrow's loop
  • Set safe_to_proceed = true

Failure Handling

If state is incomplete (missing project_card, no recent logs, unclear objective):

  • Stop the run immediately
  • Set safe_to_proceed = false
  • Request cleanup or missing-state repair
  • Do not attempt execution with partial state

State Machine

IDLE → READY → RUNNING → WRITING → DONE
                    ↓
              BLOCKED (if state incomplete)

Respect the state machine. Never skip from IDLE to RUNNING.

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

70.48%
按下载量换算786

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

来源信息

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