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Autonomous Research Loop

by GloryJack ยท GitHub โ†— ยท v1.0.0 ยท MIT-0
linux โš  suspicious
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Install in OpenClaw
/install autonomous-research-loop
Description
๐Ÿฆž ่‡ชไธป็ ”็ฉถๆ— ้™ๅพช็Žฏ - ่‡ชไธป็”Ÿๆˆ็ ”็ฉถไธป้ข˜ใ€ๆทฑๅบฆ็ ”็ฉถใ€ๅˆ›ๅปบ้ฃžไนฆๆ–‡ๆกฃใ€ๆ— ้™ๅพช็Žฏ่ฟ่กŒใ€‚
README (SKILL.md)

ๆฆ‚่ฟฐ

๐Ÿฆž ่‡ชไธป็ ”็ฉถๆ— ้™ๅพช็Žฏ ๆ˜ฏๅฐๆ™บ็š„่‡ชๆˆ‘้ฉฑๅŠจ็ ”็ฉถ็ณป็ปŸ๏ผŒๆ ธๅฟƒ้€ป่พ‘๏ผš

็”Ÿๆˆ็ ”็ฉถไธป้ข˜ โ†’ ๆทฑๅบฆ็ ”็ฉถ โ†’ ๅˆ›ๅปบ้ฃžไนฆๆ–‡ๆกฃ โ†’ ๅ›žๅˆฐ็”Ÿๆˆไธป้ข˜๏ผˆๆ— ้™๏ผ‰

ๆ ธๅฟƒๆ–‡ไปถ

ๆ–‡ไปถ ไฝœ็”จ
research_pool.json ไธป้ข˜ๆฑ ๏ผˆๅทฒๅฎŒๆˆ + ๅพ…็ ”็ฉถ + ็ปŸ่ฎก๏ผ‰
research_loop.md ๆžถๆž„่ฏดๆ˜Žๆ–‡ๆกฃ

ๅทฅไฝœๆต็จ‹

Cron่งฆๅ‘๏ผˆๆฏ5ๅˆ†้’Ÿ๏ผ‰
    โ†“
่ฏปๅ– research_pool.json
    โ†“
ๆฃ€ๆŸฅ pending_topics
    โ†“
ๆœ‰ไธป้ข˜ โ†’ ้šๆœบ้€‰1ไธช
ๆ— ไธป้ข˜ โ†’ ็”Ÿๆˆ3ไธชๆ–ฐไธป้ข˜
    โ†“
ๆทฑๅบฆ็ ”็ฉถ + ๅˆ›ๅปบ้ฃžไนฆๆ–‡ๆกฃ
    โ†“
็งปๅŠจๅˆฐ completed + ็”Ÿๆˆ3ไธชๆ–ฐไธป้ข˜
    โ†“
่พ“ๅ‡บ็ฎ€ๆŠฅๅˆฐ้ฃžไนฆ
    โ†“
ๅผ‚ๅธธ โ†’ ็›ดๆŽฅ้€€ๅ‡บ๏ผˆCron ่‡ชๅŠจๆ‹‰่ตท๏ผ‰

้…็ฝฎๆ–‡ไปถ็ป“ๆž„

{
  "completed_topics": ["ไธป้ข˜1", "ไธป้ข˜2", ...],
  "pending_topics": [{topic: "...", description: "..."}],
  "stats": {
    "total_completed": 21,
    "total_generated": 23,
    "last_completed_at": "2026-04-02T09:00:00+08:00"
  },
  "config": {
    "interval_minutes": 5,
    "max_research_time_minutes": 30,
    "new_topics_per_completion": 3
  }
}

็ ”็ฉถ่พ“ๅ‡บๆ ผๅผ

ๆฏ็ฏ‡็ ”็ฉถๆ–‡ๆกฃๅŒ…ๅซ๏ผš

  • ไธ€ๅฅ่ฏๆ€ป็ป“๏ผˆๆ ธๅฟƒๅ‘็Žฐ๏ผ‰
  • ๆœบๅˆถๆ‹†่งฃ๏ผˆไผ ๅฏผ้“พๆก๏ผ‰
  • ๅฎžๆˆ˜่ฆ็‚น๏ผˆๅ…ทไฝ“ๅฏๆ“ไฝœ๏ผ‰
  • Pythonไปฃ็ ๆก†ๆžถ๏ผˆๅฏ้€‰๏ผ‰
  • ็ฟป่ฝฆ็‚น/้ฃŽ้™ฉๆ็คบ

ๅผ‚ๅธธๅค„็†ๅŽŸๅˆ™

  • ๅผ‚ๅธธ โ†’ ็›ดๆŽฅ้€€ๅ‡บ๏ผŒไธ้‡่ฏ•๏ผŒไธๅˆ‡ๆขๆจกๅž‹
  • Cron ไผš่‡ชๅŠจๆ‹‰่ตทๆ–ฐไปปๅŠก
  • ่ขซ็ณป็ปŸ kill โ†’ ้  Cron ๆขๅค

่ดจ้‡ๆŽงๅˆถๅŽŸๅˆ™

  • ๆจกๅž‹่‡ชๅทฑ่งฃๅ†ณ็ ”็ฉถ่ดจ้‡้—ฎ้ข˜
  • ไธ็ญ‰ๅพ…ไบบๅทฅ็กฎ่ฎค
  • ้ ้—ด้š”ๆ—ถ้—ด๏ผˆ5ๅˆ†้’Ÿ๏ผ‰ๆŽงๅˆถ้ข‘็އ
  • ๆ— ๆฏๆ—ฅไธŠ้™

็›ธๅ…ณๆ–‡ไปถ

  • CronไปปๅŠก๏ผš๐Ÿฆž ่‡ชไธป็ ”็ฉถๆ— ้™ๅพช็Žฏ๏ผˆๆฏ5ๅˆ†้’Ÿ่งฆๅ‘๏ผ‰
  • ้…็ฝฎๆ–‡ไปถ๏ผš/root/.openclaw/workspace/research_pool.json
  • ่ฏดๆ˜Žๆ–‡ๆกฃ๏ผš/root/.openclaw/workspace/research_loop.md
Usage Guidance
Key things to clarify before installing: 1) Feishu integration: how will the skill authenticate and where are those credentials stored? Require explicit env vars (app id/secret, bot token, or webhook URL) declared in the skill manifest rather than implicit/global credentials. 2) Rate limits and safeguards: add a sensible daily cap and exponential backoff on failures; avoid an unconditional infinite loop without human review. 3) Least privilege: ensure any Feishu token has minimal permissions (only create docs/post messages) and is scoped to a dedicated bot/app. 4) Workspace access: confirm what data resides in /root/.openclaw/workspace; run the skill under a lowโ€‘privilege account and avoid using root paths if possible. 5) Audit and logging: require explicit telemetry/exit behavior and an optโ€‘out for autonomous runs; consider manual approval for new generated topics or for publishing outputs. 6) Test in a sandbox: run the skill in an isolated environment with mock Feishu endpoints to verify actual behavior. If the owner cannot explain where credentials come from or refuses to add explicit env var requirements and rate limits, treat the skill as risky and do not enable it for autonomous operation.
Capability Analysis
Type: OpenClaw Skill Name: autonomous-research-loop Version: 1.0.0 The skill defines an autonomous 'infinite loop' research system that utilizes cron jobs for persistence and explicitly instructs the AI agent to operate without human confirmation ('ไธ็ญ‰ๅพ…ไบบๅทฅ็กฎ่ฎค') and without daily limits. While the stated purpose is research and Feishu (Lark) document generation, the design promotes a 'runaway agent' pattern that could lead to resource exhaustion or unintended autonomous actions. No explicit evidence of data exfiltration or malicious payloads was found in SKILL.md, but the lack of oversight and self-driven task generation is high-risk.
Capability Assessment
โš  Purpose & Capability
The skill claims to autonomously generate research topics, perform deep research, and create Feishu (้ฃžไนฆ) documents on a repeating schedule. The SKILL.md repeatedly references creating docs and outputting briefings to Feishu, yet the skill declares no required environment variables, no credentials, and no integration details. Creating docs in Feishu normally requires API credentials (app id/secret, bot token, or webhook). The absence of any declared credentials or instructions for authenticating is a mismatch between claimed capability and what would actually be required to implement it.
โš  Instruction Scope
The instructions instruct an autonomous infinite loop (cron every 5 minutes) that reads and writes /root/.openclaw/workspace/research_pool.json, generates topics, performs research, and posts outputs to Feishu without human confirmation. The SKILL.md gives the agent broad discretion ('ๆจกๅž‹่‡ชๅทฑ่งฃๅ†ณ็ ”็ฉถ่ดจ้‡้—ฎ้ข˜', 'ไธ็ญ‰ๅพ…ไบบๅทฅ็กฎ่ฎค') and no explicit limits on outbound endpoints or rate limits. That open-ended autonomy plus unspecified external posting destinations is a scope risk: the agent could contact arbitrary endpoints or flood an external service.
โœ“ Install Mechanism
This is instruction-only with no install spec and no code files; nothing is written to disk by an installer. That reduces supply-chain risk compared with an installer that downloads executables.
โš  Credentials
No environment variables or credentials are declared, yet the runtime behavior requires Feishu access and likely other integration credentials. The skill also specifies a configuration stored at /root/.openclaw/workspace/research_pool.json, which implies read/write access to the agent workspace and potentially sensitive local state. The lack of declared credentials is a disproportionate gap: either the skill expects implicit global credentials (not declared) or it's incomplete/ambiguous.
โ„น Persistence & Privilege
The skill is not configured as always:true and uses normal autonomous invocation. However, _meta.json contains an explicit cron_job entry that schedules runs every 5 minutes. Combined with the instruction to run without human confirmation and with no per-day limits, this grants the skill ongoing operational presence and can lead to high frequency outbound activity. Autonomous invocation alone is expected, but combined with the other concerns (missing credentials, unlimited loop) this increases the operational risk.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install autonomous-research-loop
  3. After installation, invoke the skill by name or use /autonomous-research-loop
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: ่‡ชไธป็ ”็ฉถๆ— ้™ๅพช็Žฏ - ่‡ชไธป็”Ÿๆˆ็ ”็ฉถไธป้ข˜ใ€ๆทฑๅบฆ็ ”็ฉถใ€ๅˆ›ๅปบ้ฃžไนฆๆ–‡ๆกฃใ€ๆ— ้™ๅพช็Žฏ่ฟ่กŒ
Metadata
Slug autonomous-research-loop
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Autonomous Research Loop?

๐Ÿฆž ่‡ชไธป็ ”็ฉถๆ— ้™ๅพช็Žฏ - ่‡ชไธป็”Ÿๆˆ็ ”็ฉถไธป้ข˜ใ€ๆทฑๅบฆ็ ”็ฉถใ€ๅˆ›ๅปบ้ฃžไนฆๆ–‡ๆกฃใ€ๆ— ้™ๅพช็Žฏ่ฟ่กŒใ€‚ It is an AI Agent Skill for Claude Code / OpenClaw, with 126 downloads so far.

How do I install Autonomous Research Loop?

Run "/install autonomous-research-loop" in the OpenClaw or Claude Code chat to install it in one step โ€” no extra setup required.

Is Autonomous Research Loop free?

Yes, Autonomous Research Loop is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Autonomous Research Loop support?

Autonomous Research Loop is cross-platform and runs anywhere OpenClaw / Claude Code is available (linux).

Who created Autonomous Research Loop?

It is built and maintained by GloryJack (@gloryjack); the current version is v1.0.0.

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