Token导航 LogoToken导航

Agent Skill · 效率

pulseflow(pulseflow 效率)

pulseflow 用于整理文档、README、Markdown 和说明材料,适合在 OpenClaw 中需要把零散信息整理成结构清晰的文档时使用。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。

pulseflow 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 15,874。

总安装 3,006周安装 124GitHub Stars 公开资料未说明下载 982核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.2.1

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:pulseflow(pulseflow 效率)
来源仓库:https://github.com/ayao99315/pulseflow
安装命令:
openclaw skills install pulseflow
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 pulseflow

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

使用仅附加的 AI 工作日志维护 Markdown 任务仪表板,通过心跳或按需刷新同步每日 AI 今日完成和每周使用面板。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install pulseflow;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

pulseflow 怎么安装?

在终端执行 openclaw skills install pulseflow。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pulseflow 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

pulseflow 需要什么权限?

权限级别是只读。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。

pulseflow 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pulseflow 用的人多吗?

公开数据是累计安装 3,006 次,近一周安装 124 次,下载 982 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

pulseflow 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
pulseflow

pulseflow 效率 · 本页

3,006—只读MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
pulseflow
description
Maintain a Markdown task dashboard backed by agent-written append-only AI work logs, then sync a daily AI DONE TODAY section plus a weekly usage panel via heartbeat or on-demand refresh. Use when building or operating a reusable task system where: (1) human tasks live in a single NOW.md dashboard, (2) agents automatically append work records after each completed work unit, (3) heartbeat scans logs and refreshes the AI-derived sections, (4) a new workspace or vault needs initialization with templates, paths, and sync state.

PulseFlow

Build and operate a simple task system with one human-facing dashboard file and one append-only AI log flow.

Core model

Use one current dashboard file as the source of truth for active work.

  • Weekly usage lives in one top summary panel only: AI USAGE THIS WEEK
  • Human work lives in four sections only: FOCUS, TODAY, UP NEXT, DONE
  • AI work lives in one summary section only: AI DONE TODAY
  • Agents do not write the dashboard directly
  • Agents append one log line after each completed work unit
  • Heartbeat or an explicit refresh reads usage data plus logs and rewrites the AI-derived sections

File roles

Use these files and keep their roles strict:

  • todo/NOW.md — current dashboard
  • todo/history/YYYY-MM.md — monthly archive
  • todo/system/config.json — installation-specific paths and agent list
  • todo/system/sync-state.json — last processed offsets/checkpoints
  • reports/<agent>-ai-log-YYYY-MM-DD.jsonl — append-only per-agent daily work logs

Initialization workflow

When setting up a new installation:

  1. Create todo/, todo/history/, and todo/system/
  2. Create todo/NOW.md from the dashboard template in references/now-template.md
  3. Create todo/history/<current-month>.md from references/history-template.md if missing
  4. Create todo/system/config.json from references/config-template.json
  5. Create todo/system/sync-state.json from references/sync-state-template.json
  6. Fill installation-specific values:

- dashboard path - history directory - reports directory per agent - optional agentsFilePath per agent - enabled agent list - timezone

  1. If an older dashboard exists, migrate the human task sections into the new todo/NOW.md
  2. Do not import old AI activity retroactively unless explicitly requested
  3. Create today's empty AI log files for enabled agents
  4. Install or refresh managed AI logging rules in configured AGENTS.md files
  5. If the installation explicitly wants scheduled summaries, fill notifications.summaryCrons in config and run scripts/install_summary_crons.js

Agent write contract

Each agent must append one JSON object per completed work unit to its own daily JSONL log.

Required fields:

  • ts — ISO timestamp with timezone
  • agent — agent name
  • task — one-line work summary
  • tokens — optional integer token count for that work unit; may be 0 or omitted

Example line:

{"ts":"2026-04-05T14:10:00+08:00","agent":"main","task":"完成量化交易系统回测模块初版","tokens":12000}

Rules:

  • Append only; never edit prior lines in-place
  • Write after each completed work unit, not only at day end
  • One line should be readable without extra context
  • Do not depend on per-task token totals for daily usage accounting
  • Do not write to todo/NOW.md directly from agents

Heartbeat sync workflow

On heartbeat or explicit refresh:

  1. Read todo/system/config.json
  2. Read todo/system/sync-state.json
  3. For each enabled agent, locate today's JSONL log
  4. Parse all valid lines for today
  5. Query OpenClaw usage summary for the current week and rebuild AI USAGE THIS WEEK
  6. Rebuild the AI DONE TODAY section from the log contents for today
  7. Compute today's total tokens from OpenClaw usage data, not by summing task lines
  8. Rewrite only the AI-derived sections in todo/NOW.md
  9. Update todo/system/sync-state.json

Important:

  • Treat the dashboard AI section as a derived view, not a write-ahead log
  • Rebuild from source logs for the current day instead of incrementally appending into Markdown
  • Skip malformed lines; never let one bad line break the whole sync

Dashboard format

Keep the dashboard simple and stable.

Top usage section:

  • ## AI USAGE THIS WEEK
  • table columns: Date / Total Tokens / Input / Output / Cache / Hit Rate

Human task sections:

  • ## FOCUS
  • ## TODAY
  • ## UP NEXT
  • ## DONE

AI section:

  • ## AI DONE TODAY
  • then bullet items formatted as:

- <agent>: <task>

Archive workflow

At end of day or next-day rollover:

  1. Append completed human tasks and the AI section snapshot into todo/history/YYYY-MM.md
  2. Update the month file's AI Usage Daily Summary block with finalized per-day usage rows
  3. Group archived day entries by clipped week sections inside the month file, and keep one AI Usage Weekly Summary table per visible week block
  4. Reset DONE in todo/NOW.md
  5. Reset AI DONE TODAY for the new day on first sync
  6. Rebuild AI USAGE THIS WEEK for the new current week
  7. Move unfinished FOCUS and unfinished TODAY into the new day's TODAY
  8. Keep unfinished UP NEXT unchanged
  9. Reset FOCUS to an empty placeholder

Scripts

  • scripts/append_ai_log.js — appends one JSONL AI work record to today's per-agent log
  • scripts/install_agent_log_rules.js — installs or updates managed AI log rule blocks in configured AGENTS.md files
  • scripts/install_summary_crons.js — optionally installs or updates template-driven notification cron jobs from notifications.summaryCrons in config; these jobs supplement rollover and do not replace it
  • scripts/init_system.js — creates missing dashboard, history, config, state files, today's empty AI logs, and installs managed agent log rules when configured; it does not install cron jobs by default
  • scripts/repair_system.js — repairs missing runtime files without overwriting healthy ones
  • scripts/rollover_now.js — daily rollover script; archives yesterday's human done + AI snapshot into a week-grouped month file, updates that week's AI Usage Weekly Summary, clears DONE, resets AI DONE TODAY, carries unfinished tasks forward, and updates rollover-state.json
  • scripts/sync_ai_done.js — deterministic sync script for heartbeat or manual refresh; reads config, queries weekly usage, scans today's agent JSONL logs, rebuilds AI USAGE THIS WEEK plus AI DONE TODAY, and updates sync state
  • scripts/validate_system.js — runs a local end-to-end validation covering init, sync, repair, rollover, and rollover idempotency

Run rollover with:

node <skill-dir>/scripts/rollover_now.js

Recommended scheduler:

  • daily cron at 00:15 Asia/Shanghai

Run with:

node <skill-dir>/scripts/sync_ai_done.js

Optional config override:

AI_WORKLOG_CONFIG=/path/to/config.json node <skill-dir>/scripts/sync_ai_done.js

Validation:

node <skill-dir>/scripts/validate_system.js

Install or refresh agent rules:

AI_WORKLOG_CONFIG=/absolute/path/to/todo/system/config.json node <skill-dir>/scripts/install_agent_log_rules.js

Optionally install or update summary cron jobs after filling notifications.summaryCrons in config:

AI_WORKLOG_CONFIG=/absolute/path/to/todo/system/config.json node <skill-dir>/scripts/install_summary_crons.js

Review the planned cron changes first with:

AI_WORKLOG_CONFIG=/absolute/path/to/todo/system/config.json node <skill-dir>/scripts/install_summary_crons.js --dry-run

Recommended production invocation:

AI_WORKLOG_CONFIG=/absolute/path/to/todo/system/config.json node <skill-dir>/scripts/sync_ai_done.js

Templates and references

Read these files as needed:

  • references/now-template.md — base dashboard template
  • references/history-template.md — monthly archive template
  • references/config-template.json — install config shape, including optional summary-cron settings
  • references/sync-state-template.json — sync checkpoint shape
  • references/agent-log-format.md — log schema and examples
  • references/heartbeat-checklist.md — heartbeat operating checklist
  • references/midday-summary-template.md — optional 15:30 summary structure
  • references/daily-close-template.md — optional 00:05 previous-day report structure, intended to run before rollover
  • docs/portability.md — env overrides, installation assumptions, and optional cron-install notes

Output standard

When asked to initialize, produce or update the installation files only. When asked to sync, update only the AI-derived sections and sync state unless the user asks for more. When asked to design or migrate, keep the system minimal and reusable; avoid installation-specific assumptions outside config.json.

Runtime note

The JavaScript runtime is the only supported implementation.

平台分布

OpenClaw

74.65%
按下载量换算733

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills