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Agent Skill · 研究检索

manage(manage 搜索)

manage 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。

manage 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 62,939。

总安装 324周安装 13GitHub Stars 124下载 105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:manage(manage 搜索)
来源仓库:https://github.com/kenneth-liao/ai-launchpad-marketplace
仓库路径:skills/manage
安装命令:
npx skills add https://github.com/kenneth-liao/ai-launchpad-marketplace --skill manage
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/kenneth-liao/ai-launchpad-marketplace --skill manage

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。

用于查找、检索和筛选相关信息。manage 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位结果。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。通过 GitHub 安装,需确认权限和维护状态。

可能触发联网、命令执行或文件读写操作。建议结合原始 README 了解具体用法。

来源仓库内路径:skills/manage

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/kenneth-liao/ai-launchpad-marketplace --skill…;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

    它需要接触敏感数据,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

manage 怎么安装?

在终端执行 npx skills add https://github.com/kenneth-liao/ai-launchpad-marketplace --skill manage。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

manage 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。

manage 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

manage 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。

manage 用的人多吗?

公开数据是累计安装 324 次,近一周安装 13 次,下载 105 次,GitHub 124 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。

manage 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
manage

manage 搜索 · 本页

324124接触敏感数据未明确有提醒

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

Scheduler

Manage automated Claude Code tasks across macOS, Linux, and Windows. Schedule marketplace skills, freeform prompts, or shell scripts to run on a recurring cron schedule or as one-off tasks, with safety controls and desktop notifications.

Platform Support

PlatformSchedulerNotificationsAPI Key Storage
macOSlaunchd (plist + launchctl)osascript (native)Keychain (security CLI)
Linuxsystemd user timers (.service +.timer)notify-send (libnotify)secret-tool (GNOME Keyring) or ~/.config/anthropic/api-key
WindowsTask Scheduler (schtasks.exe + XML)BurntToast / Windows toastWindows Credential Manager or %USERPROFILE%\.config\anthropic\api-key

The platform is auto-detected at runtime. Tasks record which platform they were created on.

Overview

This orchestrator manages the full lifecycle of scheduled tasks. It delegates all operations to scheduler.py and presents results conversationally.

Core Principle: This is a thin orchestrator. All scheduling logic, file generation, and platform scheduler interaction are handled by scheduler.py with platform-specific backends. This skill manages the conversational flow only.

When to Use

Use this skill when:

  • Scheduling a recurring or one-off task (skill, prompt, or script)
  • Listing, pausing, resuming, or removing scheduled tasks
  • Viewing results or logs from past scheduled runs
  • Testing a scheduled task before activating it

Prerequisites

  • macOS, Linux, or Windows
  • claude CLI in PATH (for skill and prompt tasks)
  • uv installed (for running scheduler.py)
  • Linux only: systemctl --user available (systemd with user session)
  • Windows only: PowerShell 5.1+ and Task Scheduler access

First-Time Setup

On first invocation, verify claude is authenticated and in PATH:

claude -p "hello" --max-turns 1 --output-format text

If this fails, guide the user to run claude login before proceeding.

Also check if the scheduler directory exists. The scheduler uses project-level storage by default — it looks for .git or CLAUDE.md to find the project root, then stores state at <project>/.claude/scheduler/:

ls .claude/scheduler/registry.json

If it does not exist, the first add command will create it automatically. No manual setup needed. You can override the location with the SCHEDULER_DIR environment variable, or fall back to ~/.claude/scheduler/ when outside a project.

Workflow

When the user invokes /manage, present the operation menu:

  1. Add a new scheduled task
  2. List all scheduled tasks
  3. Pause a task
  4. Resume a paused task
  5. Remove a task
  6. Results — view output from a task
  7. Logs — view execution logs
  8. Run now — test a task immediately
  9. Cleanup — delete old logs and results
  10. Repair — regenerate wrappers and schedule artifacts

Then execute the selected operation below.

Operation: Add

Walk the user through each field conversationally:

Step 1: Task name Ask: "What should this task be called?" Generate a slug ID from the name (e.g., "Weekly note ideas" → weekly-note-ideas).

Step 2: Task type Ask: "What type of task?"

  • Skill — invoke a marketplace skill (e.g., creator-stack:generate-note-ideas)
  • Prompt — run a freeform Claude prompt
  • Script — execute a shell script

Step 3: Target Based on type:

  • Skill: Ask which skill. Suggest relevant installed skills if possible.
  • Prompt: Ask for the prompt text.
  • Script: Ask for the absolute path to the script.

Step 4: Frequency Ask: "Recurring or one-off?"

  • Recurring — runs on a schedule until paused or removed
  • One-off — runs once at the specified time, then auto-completes

Step 5: Schedule Ask: "What schedule? You can use natural language or a cron expression." Examples: "Every Monday at 8am", "Daily at 9:00", "Every weekday at 7:30am", "Tomorrow at 9am", "0 8 * * 1"

Convert natural language to a cron expression. For one-off tasks, convert the target datetime to a specific cron (e.g., "tomorrow at 9am" on Feb 25 → 0 9 26 2 *).

Confirm with the user: "That's 0 8 * * 1 — Every Monday at 8:00 AM. Correct?"

Step 6: Safety limits Ask: "Safety limits? Defaults are max 20 turns, 15 minute timeout." Let user accept defaults or customize.

Step 6a: Output directory (optional) Ask: "Want results saved to a specific directory? Default is the scheduler's results folder." If the user provides a path, it will be resolved to an absolute path and used as the flat output directory (no date subdirectories). If skipped, results go to <scheduler_dir>/results/YYYY-MM-DD/{id}.md.

Step 6b: Permissions (skip for script-type tasks) Scheduled tasks run non-interactively — Claude Code can't ask the user to approve tool use. Without pre-approved permissions, tools that need approval will fail silently.

Ask: "What permissions should this task have?" Offer these presets:

  • Default — no extra permissions (works if you have bypassPermissions set globally)
  • Readonly — read files, search, browse web (safe for research/reporting tasks)
  • Research — read files, search, web browse, curl (for data gathering)
  • Full edit — read, write, edit files, git, npm, uv, python, web (for code maintenance tasks)
  • Bypass — skip all permission checks (--dangerously-skip-permissions)
  • Custom — specify individual tool names

For custom, prompt for individual tool specs (e.g., Read, Write, Bash(git *)) separated by spaces.

Show the selected permission mode in the confirmation summary table.

CLI flags:

  • --permission-preset readonly|full-edit|research|bypass
  • --permission-mode default|acceptEdits|plan|dontAsk|bypassPermissions
  • --allowed-tools Read Write 'Bash(git *)' (individual tool specs)

Step 7: Confirm and create Present a summary table:

FieldValue
IDweekly-note-ideas
NameWeekly note ideas
TypeSkill
Targetcreator-stack:generate-note-ideas
FrequencyRecurring
ScheduleEvery Monday at 8:00 AM (0 8 * * 1)
Max turns20
Timeout15 min
Working dir{current project directory}
Output dir(default)
Permissions(default) / readonly / research / full-edit / bypass / custom

Ask: "Create this task?"

On confirmation, run:

uv run <skill_dir>/scripts/scheduler.py add \
  --id "weekly-note-ideas" \
  --name "Weekly note ideas" \
  --type skill \
  --target "creator-stack:generate-note-ideas" \
  --cron "0 8 * * 1" \
  --max-turns 20 \
  --timeout-minutes 15 \
  --working-directory "{cwd}"

For one-off tasks, add the --run-once flag. You can also specify --output-directory and --permission-preset:

uv run <skill_dir>/scripts/scheduler.py add \
  --id "morning-news-pulse" \
  --name "Morning news pulse" \
  --type prompt \
  --target "Research today's AI news" \
  --cron "0 9 26 2 *" \
  --max-turns 20 \
  --timeout-minutes 15 \
  --run-once \
  --permission-preset research \
  --output-directory "/path/to/output" \
  --working-directory "{cwd}"

Report: "Created and activated! Next run: {next run time}." For one-off tasks, add: "This will auto-complete after running."

Operation: List

Run:

uv run <skill_dir>/scripts/scheduler.py list

Present as a formatted table:

IDNameTypeScheduleStatusLast Run

If no tasks exist, say "No scheduled tasks yet. Use Add to create one."

Operation: Pause

  1. Run list to show active tasks
  2. Ask which task to pause
  3. Run:
uv run <skill_dir>/scripts/scheduler.py pause --id "{task_id}"
  1. Confirm: "Paused '{task_id}'. It won't run until you resume it."

Operation: Resume

  1. Run list to show paused tasks
  2. Ask which task to resume
  3. Run:
uv run <skill_dir>/scripts/scheduler.py resume --id "{task_id}"
  1. Confirm: "Resumed '{task_id}'. Next run: {next time}."

Operation: Remove

  1. Run list to show all tasks
  2. Ask which task to remove
  3. Confirm: "This will stop the schedule and delete the wrapper and schedule artifacts. Results and logs are kept. Proceed?"
  4. Run:
uv run <skill_dir>/scripts/scheduler.py remove --id "{task_id}"
  1. Confirm: "Removed '{task_id}'."

Operation: Results

  1. Ask which task (or show list if unclear)
  2. Run:
uv run <skill_dir>/scripts/scheduler.py results --id "{task_id}"
  1. Display the latest result content inline

To list all results:

uv run <skill_dir>/scripts/scheduler.py results --id "{task_id}" --all

Operation: Logs

  1. Ask which task
  2. Run:
uv run <skill_dir>/scripts/scheduler.py logs --id "{task_id}"
  1. Display recent log entries

Operation: Cleanup

Delete old log and result files to reclaim disk space:

uv run <skill_dir>/scripts/scheduler.py cleanup --max-days 30

The --max-days flag controls the retention period (default: 30 days). Log files are cleaned by modification time; result date-directories are cleaned by directory name.

Tip: You can schedule cleanup itself as a recurring task:

uv run <skill_dir>/scripts/scheduler.py add \
  --id scheduler-cleanup \
  --name "Scheduler Cleanup" \
  --type script \
  --target "<skill_dir>/scripts/cleanup-wrapper.sh" \
  --cron "0 3 * * 0" \
  --working-directory "{cwd}"

Operation: Repair

Regenerate missing or outdated wrapper scripts and schedule artifacts for all active tasks. Useful after plugin updates, permission changes, or if a wrapper was accidentally deleted.

  1. Ask whether to force-regenerate all wrappers or only missing ones.
  2. Run:
uv run <skill_dir>/scripts/scheduler.py repair

Or with force:

uv run <skill_dir>/scripts/scheduler.py repair --force
  1. Report how many issues were fixed.

Operation: Run Now

Important: scheduler.py run spawns claude -p as a subprocess, which fails inside an active Claude Code session ("cannot be launched inside another Claude Code session"). Since users typically invoke this skill from within Claude Code, use the deferred scheduling approach instead.

Procedure:

  1. Ask which task to test.
  2. Read the registry to save the task's current cron schedule:
uv run <skill_dir>/scripts/scheduler.py get --id "{task_id}"

Note the current cron value.

  1. Compute a cron expression for ~2 minutes from now (e.g., if current time is 10:03, use 5 10 {day} {month} *). Include the day and month to avoid the task firing again on subsequent days.
  2. Pause the task, edit the cron in the registry, and reload:
uv run <skill_dir>/scripts/scheduler.py pause --id "{task_id}"

Then edit .claude/scheduler/registry.json directly — find the task by ID and change its cron field to the near-future expression. Then resume:

uv run <skill_dir>/scripts/scheduler.py resume --id "{task_id}"

Finally, regenerate the wrapper and schedule with the new cron:

uv run <skill_dir>/scripts/scheduler.py repair --force
  1. Tell the user: "Task rescheduled to run in ~2 minutes. Waiting for it to fire..."
  2. Poll for the result every 30 seconds (up to the task's timeout + 2 minutes):
uv run <skill_dir>/scripts/scheduler.py results --id "{task_id}"

Compare timestamps to confirm a new result appeared after the reschedule.

  1. Once the result appears (or timeout), restore the original cron. Edit .claude/scheduler/registry.json to set the cron field back to the original value, then reload:
uv run <skill_dir>/scripts/scheduler.py repair --force
  1. Show the result output to the user and confirm the original schedule is restored.

Cron Expression Reference

For converting natural language to cron:

Natural LanguageCron Expression
Every day at 9am0 9 * * *
Every Monday at 8am0 8 * * 1
Every weekday at 7:30am30 7 * * 1-5
Every Sunday at midnight0 0 * * 0
Every hour0 * * * *
Every 1st of the month at 6am0 6 1 * *
Twice daily (9am, 5pm)Two tasks needed

Error Recovery

"Task already exists": Suggest a different ID or remove the existing one first. "Invalid cron expression": Show the cron reference table and ask again. "Wrapper not found": Run repair:

uv run <skill_dir>/scripts/scheduler.py repair

"Task failed (check logs)": Use the Logs operation to show what went wrong. "Task succeeded but output is empty": Likely a permission issue. Scheduled tasks run non-interactively and can't prompt for tool approval. Add a permission preset (e.g., --permission-preset readonly for read-only tasks) and regenerate wrappers with repair --force. "Wrapper needs permission update": After changing a task's permissions in the registry, run repair --force to regenerate all wrappers with the new settings.

Notes

For implementation details on permissions, lock files, sleep behavior, storage, and platform specifics, see references/implementation-notes.md.

Quality Checklist

  • Task type correctly identified (skill/prompt/script)
  • Cron expression validated and confirmed with user
  • Summary table presented before creating
  • scheduler.py command executed successfully
  • User informed of next run time (for add/resume)
  • Confirmation requested before destructive operations (remove)

平台分布

Codex

33.96%
按下载量换算36

Claude

32.71%
按下载量换算34

Cursor

19.15%
按下载量换算20

Gemini CLI

9.22%
按下载量换算10

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。

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