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pulseflowpulseflow 效率

Agent Skill

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。

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下载量

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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: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。

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openclaw skills install pulseflow

简介

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。

SKILL.md

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.

适合场景

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需要根据任务场景推荐可安装能力包时

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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

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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

74.65%
按下载量换算733

安全审计

VirusTotal

通过

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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

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