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Agent Skill · 研究检索

agentic-loop-designer(Agent 循环设计器)

agentic-loop-designer 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。

agentic-loop-designer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,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 15,277。

总安装 7,962周安装 342GitHub Stars 公开资料未说明下载 2,791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
1.0.0

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:agentic-loop-designer(Agent 循环设计器)
来源仓库:https://github.com/flynndavid/agentic-loop-designer
安装命令:
openclaw skills install agentic-loop-designer
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 agentic-loop-designer

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。

设计和部署自主代理循环,自动执行重复任务。支持是/否决策、触发器、批准与 Slack 输出模板。使用现成模板简化流程搭建与部署过程。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。建议在安装前确认是否会触发外部服务调用。

agentic-loop-designer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 agentic-loop-designer;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

agentic-loop-designer 怎么安装?

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

agentic-loop-designer 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。

agentic-loop-designer 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。

agentic-loop-designer 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。

agentic-loop-designer 用的人多吗?

公开数据是累计安装 7,962 次,近一周安装 342 次,下载 2,791 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。

agentic-loop-designer 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。

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
agentic-loop-designer

Agent 循环设计器 · 本页

7,962—需要联网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
agentic-loop-designer
version
1.0.0
price
29
bundle
ai-setup-productivity-pack
bundle_price
79
last_validated
2026-03-07

Agentic Loop Designer

Framework: The Yes/No Loop Canvas *Worth $300/hr consultant time. Yours for $29.*


What This Skill Does

Turns any repeatable task you're doing manually into an autonomous agent loop: trigger → agent → Slack ping → approve/skip. Includes 5 ready-to-deploy loop templates and a decision tree to design your own from scratch.

Problem it solves: Founders spend hours on task sequences that could run themselves. Email triage, weekly reports, standup summaries, lead qualification — if you do it the same way more than twice a week, it should be a loop.


The Yes/No Loop Canvas

A structured framework for designing any agentic loop in under 10 minutes. Built around one insight: every automatable task is just a series of yes/no decisions.

Canvas Structure

┌─────────────────────────────────────────────┐
│              YES/NO LOOP CANVAS             │
├─────────────────────────────────────────────┤
│  TRIGGER: What starts this loop?           │
│  ─────────────────────────────────────────  │
│  AGENT ACTION: What does the agent do?     │
│  ─────────────────────────────────────────  │
│  DECISION GATE: Approve / Skip / Escalate? │
│  ─────────────────────────────────────────  │
│  OUTPUT: What gets created or sent?        │
│  ─────────────────────────────────────────  │
│  MEMORY: What should persist for next run? │
└─────────────────────────────────────────────┘

Step 1: Trigger Qualification

What kicks off this loop?

Is there a natural trigger?
├── Time-based (daily/weekly/on schedule)
│   └── → Use: cron trigger
├── Event-based (new email, new issue, form submit)
│   └── → Use: webhook trigger
├── Threshold-based (metric crosses a line)
│   └── → Use: polling trigger with condition
└── Manual ("run this now")
    └── → Use: manual trigger with /command

Trigger scoring:

Trigger TypeReliabilitySetup EffortRecommended For
Cron★★★★★LowReports, summaries, digests
Webhook★★★★☆MediumNew data events
Polling★★★☆☆MediumMetric-based
Manual★★★★★NoneOn-demand workflows

Step 2: Agent Action Design

What should the agent actually do?

The action block answers three questions:

  1. What data does the agent need? (sources)
  2. What transformation happens? (the work)
  3. What's the output format? (how it lands)

Action Template:

SOURCES: [List tools/APIs the agent reads from]
TRANSFORM: [Plain English description of what agent does]
OUTPUT FORMAT: [Slack message / doc / file / API call]

Example:

SOURCES: Linear API (open issues), GitHub API (open PRs)
TRANSFORM: Group issues by assignee, flag items > 3 days old
OUTPUT FORMAT: Slack message with bullet list, @mention for flagged items

Step 3: Decision Gate Design

The most important part of any agentic loop.

Every loop needs a clear approval model. Use this matrix:

Risk LevelData SensitivityAction ScopeGate Type
LowNon-sensitiveRead-onlyAuto-run (no gate)
LowNon-sensitiveWrite/sendSlack preview → auto-send after 15 min
MediumSemi-sensitiveWrite/sendSlack approve button required
HighSensitiveAnyHuman review always
AnyAnyIrreversibleHuman review always

Gate implementation:

Slack message format for approval gates:
─────────────────────────────────
🤖 Loop: {Loop Name} | Run #{N}
{Agent output preview}

[✅ Approve] [⏭ Skip] [🛑 Stop Loop]
─────────────────────────────────
Timeout: {N} minutes → {default action}

Step 4: Output Design

Where does the work land?

Output destination decision tree:
├── Team visibility needed?
│   ├── Yes → Slack channel message
│   └── No → DM or file
├── Needs to be acted on later?
│   ├── Yes → Notion page / Linear issue / GitHub issue
│   └── No → Slack message (ephemeral OK)
├── Needs structured data?
│   ├── Yes → Notion database row / JSON file
│   └── No → Prose summary
└── External delivery needed?
    ├── Yes → Email (via SMTP/SendGrid) / webhook
    └── No → Internal tool

Step 5: Memory Design

What should persist between runs?

Memory checklist:
□ Last run timestamp (prevent duplicate work)
□ Previously processed item IDs (deduplication)
□ Cumulative state (running totals, streaks)
□ User preferences (learned from approvals/skips)
□ Error log (for debugging)

Simple memory implementation (file-based):

{
  "loop_id": "weekly-standup",
  "last_run": "2026-03-07T09:00:00Z",
  "processed_ids": ["issue-123", "pr-456"],
  "run_count": 14,
  "skip_count": 2
}

5 Ready-to-Deploy Loop Templates

Loop 1: Weekly Standup Digest

Trigger: Every Monday at 9am Sources: Linear (open issues), GitHub (open PRs), Slack (#general last 7 days) Action: Summarize each team member's open work + any blockers Gate: Auto-send (low risk, read-only) Output: Slack message in #standup

LOOP CONFIG:
─────────────────────────────────────
Name: Weekly Standup Digest
Trigger: cron("0 9 * * MON")
Agent prompt: |
  Read all open Linear issues assigned to each team member.
  Read all open GitHub PRs by author.
  For each person, write 2-3 bullet points: what they're working on,
  what's overdue (> 3 days), any blockers mentioned in Slack this week.
  Format as a Slack message with @mentions.
Gate: None (auto-send)
Output: POST to #standup
Memory: last_run timestamp
─────────────────────────────────────

Setup time: ~20 minutes | Time saved: 30-60 min/week


Loop 2: New Lead Qualifier

Trigger: New form submission (webhook from Typeform/Tally) Sources: Form response, company domain lookup (Clearbit/Apollo) Action: Score lead on ICP criteria, draft personalized follow-up email Gate: Slack approve → send email Output: Draft email + lead score in Notion CRM

LOOP CONFIG:
─────────────────────────────────────
Name: New Lead Qualifier
Trigger: webhook (form submission)
Agent prompt: |
  Receive new lead form data.
  Look up company via domain (use Clearbit if available).
  Score on: company size (0-30), role seniority (0-30),
  use case fit (0-40).
  Draft personalized 3-sentence intro email.
  Post to Slack: lead summary + score + draft email.
Gate: Approve button → sends email | Skip → logs as not qualified
Output: Notion CRM row + email (if approved)
Memory: processed form IDs (dedup)
─────────────────────────────────────

Setup time: ~45 minutes | Time saved: 2-4 hrs/week


Loop 3: GitHub PR Review Reminder

Trigger: Every weekday at 3pm Sources: GitHub API (open PRs, age, reviewer assignments) Action: Find PRs waiting > 24hr for review, draft reminder message Gate: Auto-send if PR age > 48hr, Slack preview if 24-48hr Output: Slack message @mentioning overdue reviewers

LOOP CONFIG:
─────────────────────────────────────
Name: PR Review Reminder
Trigger: cron("0 15 * * MON-FRI")
Agent prompt: |
  Fetch all open PRs across [repos].
  Find PRs with requested reviewers but no review in > 24 hours.
  Group by reviewer. For each reviewer, list their overdue PRs.
  Draft a friendly Slack message with PR links and ages.
Gate: If any PR > 48hr → auto-send. If 24-48hr → preview + 30min timeout
Output: #engineering Slack channel
Memory: last sent reminder per PR (avoid nagging)
─────────────────────────────────────

Setup time: ~15 minutes | Time saved: Ad-hoc interruptions → 0


Loop 4: Weekly Revenue Snapshot

Trigger: Every Friday at 5pm Sources: Stripe API, Notion metrics database, previous week's snapshot Action: Calculate WoW change in MRR, churn, new customers Gate: Auto-send (read-only financial data) Output: Slack message in #founders with sparkline context

LOOP CONFIG:
─────────────────────────────────────
Name: Weekly Revenue Snapshot
Trigger: cron("0 17 * * FRI")
Agent prompt: |
  Pull current MRR from Stripe.
  Compare to snapshot from 7 days ago (stored in memory).
  Calculate: MRR change ($, %), new customers, churned customers.
  Write 3-sentence narrative: what changed, why (if obvious), what to watch.
  Format for Slack with clear numbers.
Gate: Auto-send
Output: #founders Slack channel + update Notion metrics DB
Memory: last week's MRR, customer count (for WoW delta)
─────────────────────────────────────

Setup time: ~30 minutes | Time saved: 1-2 hrs/week manual pulling


Loop 5: Content Idea Capture & Queue

Trigger: Any message containing #idea in designated Slack channel Sources: Slack message, existing content queue in Notion Action: Extract idea, score for relevance, add to queue with metadata Gate: Auto-add if score > 70, Slack preview if 50-70, discard if < 50 Output: Notion content database row

LOOP CONFIG:
─────────────────────────────────────
Name: Content Idea Capture
Trigger: Slack event (message in #ideas with #idea tag)
Agent prompt: |
  Extract the core idea from the Slack message.
  Score on: audience fit (0-30), differentiation (0-30), 
  timely/relevant (0-20), producibility (0-20).
  Write a one-line description and suggested format (post/thread/video).
  If score >= 70: auto-add to Notion queue.
  If 50-69: post preview to Slack with Add/Skip buttons.
  If < 50: silently discard.
Gate: Score-based (auto/preview/discard)
Output: Notion "Content Ideas" database
Memory: processed Slack message IDs
─────────────────────────────────────

Setup time: ~25 minutes | Time saved: Idea capture friction → 0


Design Your Own Loop: 10-Minute Workshop

Step 1: Identify the task (2 min)

What do you do manually that feels like groundhog day? Write it in one sentence: "Every [timeframe] I [action] using [sources] and [output]"

Step 2: Fill the Canvas (5 min)

TRIGGER: _______________
SOURCES: _______________
AGENT ACTION: _______________
GATE: Auto / Preview / Approve (circle one)
OUTPUT: _______________
MEMORY: _______________

Step 3: Risk-check (2 min)

  • Can this loop send external messages? → Need approval gate
  • Does it write or delete data? → Need approval gate
  • Is it purely read + summarize? → Auto-run is fine

Step 4: Name it and ship it (1 min)

Name your loop. Add it to your agent config. Run it once manually. Watch it work.

Yes/No Loop Scoring Rubric

Before deploying any loop, score it:

Dimension012
Trigger is reliableManual onlyPartially automatedFully automated
Sources are availableNot connectedPartially connectedAll connected via MCP
Gate is appropriateNo gate on risky actionGate exists but clunkyGate matches risk level
Output is usefulNo one reads itSometimes usefulConsistently acted on
Memory prevents duplicatesNo dedupPartialFull dedup

Score 8-10: Deploy it. This loop is ready. Score 5-7: Fix the weak spots (usually gate or sources) before deploying. Score 0-4: Back to Canvas. Something fundamental is wrong.


Example Session

User prompt:

"I spend every Monday morning pulling GitHub PRs and posting a status to Slack. Help me automate this."

Agent response using this skill:

  1. Fills Yes/No Loop Canvas with user's specific repos and Slack channel
  2. Identifies trigger: Monday 9am cron
  3. Confirms GitHub MCP is connected (or instructs setup via MCP Server Setup Kit)
  4. Applies Loop Template 1 (Weekly Standup Digest), customized for their stack
  5. Scores the loop using the rubric: should hit 8-10
  6. Provides final config block ready to deploy

Bundle Note

This skill is part of the AI Setup & Productivity Pack ($79 bundle):

  • MCP Server Setup Kit ($19)
  • Agentic Loop Designer ($29) — *you are here*
  • AI OS Blueprint ($39)
  • Context Budget Optimizer ($19)
  • Non-Technical Agent Quickstart ($9)

Save $36 with the full bundle. Built by @Remy_Claw.

平台分布

OpenClaw

84.14%
按下载量换算2,348

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

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。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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