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Agent Skill · 研究检索

frappe-impl-scheduler(frappe impl 调度程序)

frappe-impl-scheduler 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

frappe-impl-scheduler 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 50,488。

总安装 612周安装 25GitHub Stars 87下载 198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
unknown

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:frappe-impl-scheduler(frappe impl 调度程序)
来源仓库:https://github.com/openaec-foundation/erpnext_anthropic_claude_development_skill_package
仓库路径:skills/frappe-impl-scheduler
安装命令:
npx skills add https://github.com/openaec-foundation/erpnext_anthropic_claude_development_skill_package --skill frappe-impl-scheduler
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/openaec-foundation/erpnext_anthropic_claude_development_skill_package --skill frappe-impl-scheduler

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

frappe-impl-scheduler 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景从来源线索中获取信息的场景。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/frappe-impl-scheduler

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/openaec-foundation/erpnext_anthropic_claude_de…;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

frappe-impl-scheduler 怎么安装?

在终端执行 npx skills add https://github.com/openaec-foundation/erpnext_anthropic_claude_development_…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

frappe-impl-scheduler 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

frappe-impl-scheduler 需要什么权限?

权限级别是需要联网。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。

frappe-impl-scheduler 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

frappe-impl-scheduler 用的人多吗?

公开数据是累计安装 612 次,近一周安装 25 次,下载 198 次,GitHub 87 星。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。

frappe-impl-scheduler 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
frappe-impl-scheduler

frappe impl 调度程序 · 本页

61287需要联网未明确通过

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

Frappe Scheduler & Background Jobs - Implementation

Workflow for implementing scheduled tasks and background jobs. For exact syntax, see frappe-syntax-scheduler.

Version: v14/v15/v16 compatible


Main Decision: scheduler_events vs frappe.enqueue

WHAT ARE YOU BUILDING?
|
+-- Runs at fixed intervals/times?
|   +-- YES --> scheduler_events (hooks.py)
|   |           Task receives NO arguments
|   |           See: Workflow 1-2
|   |
|   +-- NO --> Triggered by user action or code?
|              +-- YES --> frappe.enqueue()
|              |           Pass any serializable data
|              |           See: Workflow 3-4
|              |
|              +-- NO --> Reconsider requirements
Aspectscheduler_eventsfrappe.enqueue
Triggered byTime/intervalCode execution
Defined inhooks.pyPython code
ArgumentsNONE (must be parameterless)Any serializable data
Use caseDaily cleanup, hourly syncUser-triggered long task
Queue controlEvent suffix (_long)queue= parameter
Restart behaviorRuns on scheduleLost if worker restarts

Which Scheduler Event Type?

NeedEvent KeyQueue
Every scheduler tickallshort (NEVER >60s)
Hourly (<5 min)hourlyshort
Hourly (5-25 min)hourly_longlong
Daily (<5 min)dailyshort
Daily (5-25 min)daily_longlong
Weekly (<5 min)weeklyshort
Weekly (5-25 min)weekly_longlong
Monthly (<5 min)monthlyshort
Monthly (5-25 min)monthly_longlong
Custom schedulecron["expr"]short

Rule: ALWAYS use *_long suffix for tasks exceeding 5 minutes.


Which Queue for frappe.enqueue?

QueueDefault TimeoutUse For
short300s (5 min)Quick operations (<1 min)
default300s (5 min)Standard tasks (1-5 min)
long1500s (25 min)Heavy processing (>5 min)

Rule: ALWAYS specify queue= explicitly. NEVER rely on the default.


Implementation Step 1: Scheduler Event

# myapp/tasks.py
import frappe

def daily_cleanup():
    """Daily cleanup - NO parameters allowed."""
    cutoff = frappe.utils.add_days(frappe.utils.nowdate(), -30)
    frappe.db.delete("Error Log", {"creation": ("<", cutoff)})
    frappe.db.commit()
# hooks.py
scheduler_events = {
    "daily": ["myapp.tasks.daily_cleanup"]
}

After editing hooks.py: ALWAYS run bench migrate.


Implementation Step 2: Background Job (frappe.enqueue)

# myapp/api.py
import frappe
from frappe.utils.background_jobs import is_job_enqueued

@frappe.whitelist()
def process_documents(doctype, filters):
    job_id = f"process_{doctype}_{frappe.session.user}"

    if is_job_enqueued(job_id):
        return {"message": "Already in progress"}

    frappe.enqueue(
        "myapp.tasks.process_batch",
        queue="long",
        timeout=1800,
        job_id=job_id,
        enqueue_after_commit=True,
        doctype=doctype,
        filters=filters
    )
    return {"status": "queued"}

Testing Scheduled Tasks

Method 1: bench execute (direct)

# Run the function directly (no queue involved)
bench --site mysite execute myapp.tasks.daily_cleanup

Method 2: bench scheduler (full scheduler test)

# Check scheduler status
bench --site mysite scheduler status

# Enable scheduler
bench --site mysite scheduler enable

# Trigger all pending scheduler events NOW
bench --site mysite scheduler trigger

# Run specific event type
bench --site mysite execute frappe.utils.scheduler.trigger --args "['daily']"

Method 3: bench console (interactive)

bench --site mysite console
>>> frappe.enqueue("myapp.tasks.my_task", queue="short", now=True)
# now=True executes synchronously for testing

Method 4: Check Scheduled Job Type

1. Go to: Setup > Scheduled Job Type
2. Find: myapp.tasks.daily_cleanup
3. Verify: Frequency correct, Stopped = No
4. Click "Run Now" to trigger manually

Monitoring

Scheduled Job Log (UI)

Setup > Scheduled Job Log
- Shows every scheduler run with status
- Filter by: status (Success/Failed), creation date
- Check execution time to detect slow tasks

RQ Dashboard

# Start RQ monitor (development)
bench --site mysite rq-dashboard
# Opens at http://localhost:9181

# Show background job status
bench --site mysite show-pending-jobs
bench --site mysite show-failed-jobs

Programmatic Health Check

def scheduler_health_check():
    failed = frappe.db.count("Scheduled Job Log", {
        "status": "Failed",
        "creation": [">=", frappe.utils.add_to_date(None, hours=-1)]
    })
    if failed > 5:
        frappe.sendmail(
            recipients=["admin@example.com"],
            subject="Scheduler Alert: Many failures",
            message=f"{failed} scheduler jobs failed in last hour"
        )

Error Handling in Scheduled Tasks

Per-Record Error Isolation

def sync_all_orders():
    orders = get_pending_orders()
    success, errors = 0, 0

    for order in orders:
        try:
            sync_to_external(order)
            success += 1
        except Exception as e:
            errors += 1
            frappe.db.rollback()
            frappe.log_error(
                f"Sync failed for {order}: {e}",
                "Order Sync Error"
            )
    frappe.db.commit()
    frappe.logger("sync").info(f"{success} ok, {errors} errors")

Rule: ALWAYS wrap per-record processing in try-except. NEVER let one failure stop the entire batch.


Long-Running Job Patterns

Self-Chaining Pattern (>25 min tasks)

def process_batch(offset=0, batch_size=500, total=None):
    if total is None:
        total = frappe.db.count("Sales Invoice", {"custom_processed": 0})

    records = frappe.get_all("Sales Invoice",
        filters={"custom_processed": 0},
        pluck="name", limit=batch_size)

    if not records:
        return  # Done

    for name in records:
        process_single(name)
    frappe.db.commit()

    remaining = frappe.db.count("Sales Invoice", {"custom_processed": 0})
    if remaining > 0:
        frappe.enqueue(
            "myapp.tasks.process_batch",
            queue="long",
            offset=offset + batch_size,
            batch_size=batch_size,
            total=total
        )

Rule: ALWAYS split tasks >25 min into self-chaining batches.


Common Implementation Patterns

Email Digest (weekly summary)

# hooks.py
scheduler_events = {
    "cron": {
        "0 8 * * 1": ["myapp.newsletter.send_weekly_digest"]
    }
}

See references/examples.md Example 4 for complete implementation.

Data Cleanup (daily maintenance)

scheduler_events = {
    "daily_long": ["myapp.maintenance.daily_database_maintenance"]
}

See references/examples.md Example 1 for batch deletion pattern.

Report Generation (user-triggered)

frappe.enqueue(
    "myapp.tasks.generate_report",
    queue="long",
    timeout=3600,
    job_id=f"report::{frappe.session.user}",
    user=frappe.session.user
)

See references/workflows.md Workflow 6 for progress reporting.


Critical Rules

  1. Scheduler tasks receive NO arguments - Use settings or hardcoded values
  2. ALWAYS bench migrate after hooks.py changes - Required to register events
  3. Jobs run as Administrator - ALWAYS commit explicitly
  4. Commit in batches - NEVER per-record (every 100-500 records)
  5. ALWAYS use job_id for user-triggered jobs - Prevents duplicates
  6. Use enqueue_after_commit=True from document events - Ensures data exists
  7. Scheduler events should be thin - Enqueue heavy work to background

Version Differences

Aspectv14v15v16
Tick interval240s60s60s
Job dedup paramjob_namejob_idjob_id
enqueue_doc()YesYesYes
Custom queuesNoYesYes

Reference Files

FileContents
workflows.md8 step-by-step implementation patterns
decision-tree.mdDetailed decision flowcharts
examples.md5 complete working examples
anti-patterns.md14 common mistakes to avoid

See Also

  • frappe-syntax-scheduler - Exact syntax reference for hooks and enqueue
  • frappe-errors-serverscripts - Error handling patterns
  • frappe-impl-hooks - Hook configuration patterns
  • frappe-ops-bench - Bench commands for scheduler management
  • frappe-ops-performance - Performance tuning for background jobs
  • frappe-testing-unit - Testing scheduled task logic

平台分布

Codex

36.67%
按下载量换算73

Claude

30.98%
按下载量换算61

Cursor

18.16%
按下载量换算36

Gemini CLI

9.49%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

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

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。目前只有一个公开来源,建议同时核对源仓库。

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