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Agent Skill · 研究检索

autonomous-loop(自主循环)

autonomous-loop 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。

autonomous-loop 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 47,223。

总安装 744周安装 31GitHub Stars 1下载 248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:autonomous-loop(自主循环)
来源仓库:https://github.com/pixel-process-ug/superkit-agents
仓库路径:skills/autonomous-loop
安装命令:
npx skills add https://github.com/pixel-process-ug/superkit-agents --skill autonomous-loop
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/pixel-process-ug/superkit-agents --skill autonomous-loop

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。

autonomous-loop 用于查找、检索和筛选相关信息,适合快速定位候选结果。适用于需要根据关键词或任务场景从来源线索中筛选信息的场景。通过 npx skills add 命令从指定 GitHub 仓库安装并使用该技能。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/autonomous-loop

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/pixel-process-ug/superkit-agents --skill auton…;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

autonomous-loop 怎么安装?

在终端执行 npx skills add https://github.com/pixel-process-ug/superkit-agents --skill autonomous-loop。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

autonomous-loop 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。

autonomous-loop 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。

autonomous-loop 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。

autonomous-loop 用的人多吗?

公开数据是累计安装 744 次,近一周安装 31 次,下载 248 次,GitHub 1 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。

autonomous-loop 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

  • 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

  • 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
autonomous-loop

自主循环 · 本页

7441需要联网未明确有提醒

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

Autonomous Loop

Overview

The autonomous loop implements Ralph's iterative development methodology. Each iteration loads identical context (PROMPT + AGENTS files), executes one focused task, reports structured status, and persists state to disk for the next iteration. The loop continues until the dual-condition exit gate is satisfied. The core innovation is that deterministic conditions allow Claude to autonomously plan, build, and iterate toward quality without human intervention in the loop.

Announce at start: "I'm starting the autonomous loop. Loading context and beginning PLANNING mode."

Trigger Conditions

  • /ralph or /loop command invoked
  • Project has specs and is ready for iterative autonomous development
  • Multi-task implementation that benefits from autonomous iteration
  • User requests autonomous execution without per-task approval

Architecture

+--------------------------------------------------+
|                 AUTONOMOUS LOOP                    |
|                                                    |
|  +----------+    +----------+    +-----------+    |
|  | PLANNING |---→| BUILDING |---→|  STATUS   |    |
|  |   MODE   |    |   MODE   |    |  CHECK    |    |
|  +----------+    +----------+    +-----+-----+    |
|       ^                               |           |
|       |            +-----------+      |           |
|       +------------|  EXIT GATE|←-----+           |
|                    |  (dual)   |                   |
|                    +-----+-----+                   |
|                          |                         |
|                    PASS: EXIT                      |
|                    FAIL: LOOP                      |
+--------------------------------------------------+

Phase 1: PLANNING MODE (Gap Analysis)

Goal: Analyze specs against implementation to identify and prioritize remaining work.

Steps

  1. Knowledge Gathering — Deploy up to 250 parallel subagents via the Agent tool (with subagent_type="Explore" and model="sonnet") to study specs, existing implementation plans, and utility libraries
  2. Code Analysis — Deploy up to 500 parallel subagents via the Agent tool (with subagent_type="Explore") to study src/* against specs/*, identifying gaps between specification and implementation
  3. Synthesis — Deploy a synthesis subagent via the Agent tool (with model="opus") to synthesize findings and prioritize incomplete work
  4. Plan Refresh — Update IMPLEMENTATION_PLAN.md as organized, prioritized bullet list

Planning Mode Constraints

ConstraintRationale
Verify ALL assumptions through code searchNever assume something is absent
Treat src/lib as authoritative standard libraryConsolidate, do not duplicate
Output is a prioritized task listNot code, not designs — tasks only
Identify missing specsSpecs gaps are blockers, not things to guess about

Planning Mode Output

IMPLEMENTATION_PLAN.md updated:
- [x] Completed tasks (checked off)
- [ ] Remaining task 1 (highest priority)
- [ ] Remaining task 2
- [ ] Remaining task 3
...
Missing specs identified: [list or "none"]

STOP — Do NOT proceed to Phase 2 until:

  • All specs have been read and analyzed
  • Code has been compared against specs
  • IMPLEMENTATION_PLAN.md is updated with prioritized tasks
  • Missing specs are identified (if any)

Phase 2: BUILDING MODE (Implementation)

Goal: Select and complete exactly ONE task per iteration.

"ONE Task Per Loop" Principle

Each iteration selects and completes exactly one task from IMPLEMENTATION_PLAN.md. This reduces context switching, enables clear progress measurement, and makes debugging easier.

Steps

  1. Study — Read specs and current IMPLEMENTATION_PLAN.md
  2. Select — Choose the most important remaining task
  3. Search — Find existing code patterns (do NOT assume implementations are missing)
  4. Implement — Write complete, production-quality code (no placeholders, no stubs)
  5. Test — Run tests immediately after implementation
  6. Update — Refresh IMPLEMENTATION_PLAN.md with findings and progress
  7. Commit — Descriptive conventional commit message with rationale

Task Selection Decision Table

ConditionWhich Task to Select
Blocker exists for other tasksSelect the blocker task
Test failures existSelect task that fixes the failure
All tasks independentSelect highest priority task
Multiple tasks at same prioritySelect the one with clearest spec
Spec is missing for top taskRun PLANNING mode to identify gap

Subagent Rules During Building

ResourceBudgetRationale
Read/search subagentsUp to 500 parallel SonnetFast context gathering
Build subagentOnly 1 Sonnet at a timeSerialize builds to detect failures
Main context40-60% utilizationThe "smart zone" — enough room to think

Building Mode Constraints

ConstraintRationale
No placeholders or stubsEvery line of code is production-quality
Search before implementingCode may already exist elsewhere
Run tests immediatelyBackpressure catches errors early
Update plan after every taskKeep plan current with reality
Commit after every taskSmall atomic commits, easy to revert

STOP — Do NOT proceed to Phase 3 until:

  • Task is fully implemented (no stubs)
  • Tests have been run
  • IMPLEMENTATION_PLAN.md is updated
  • Changes are committed

Phase 3: STATUS CHECK

Goal: Produce a RALPH_STATUS block and evaluate exit conditions.

After each BUILD iteration, invoke the ralph-status skill to produce a structured status block.

Exit Evaluation

CheckConditionResult
Tasks remaining?IMPLEMENTATION_PLAN.md has unchecked itemsContinue loop
Tests passing?Full test suite passesRequired for exit
Errors in iteration?Clean execution, no unresolved exceptionsRequired for exit
Meaningful work remains?No TODOs, no incomplete featuresRequired for exit

Loop Decision

StatusTasks RemainingTestsAction
IN_PROGRESSYesAnyLoop back to Phase 1 or 2
IN_PROGRESSNoFAILINGLoop — fix failures first
BLOCKEDAnyAnyReport blocker, wait for input
COMPLETENoPASSINGEvaluate exit gate

Exit Conditions — Dual-Condition Gate

ConditionThresholdVerification
Completion indicators>= 2 recent occurrences of "done" languageHeuristic detection in output
Explicit EXIT_SIGNALEXIT_SIGNAL: true in status blockIntentional declaration

EXIT_SIGNAL May Only Be true When ALL Of:

  • IMPLEMENTATION_PLAN.md has no remaining tasks
  • All tests pass
  • No errors in latest iteration
  • No meaningful work remains

This prevents false positives where completion language appears while productive work continues.

Exit Decision Table

Completion LanguageEXIT_SIGNALAction
< 2 occurrencesfalseContinue loop
>= 2 occurrencesfalseContinue — may be casual language
< 2 occurrencestrueContinue — signal without evidence
>= 2 occurrencestrueEXIT the loop

Context Efficiency

ResourceBudgetStrategy
Main context40-60% of windowKeep focused; delegate heavy lifting
Read subagentsUp to 500 parallelSearching, file reading, pattern matching
Build subagents1 at a timeImplementation, test execution
Token formatMarkdown over JSON~30% more efficient

Steering Mechanisms

Upstream Steering (Shaping Inputs)

MechanismPurpose
First ~5,000 tokens for detailed specsFront-load specification context
Identical files each iterationDeterministic context loading
Existing code patterns as guidesGenerate consistent code

Downstream Steering (Validation Gates)

GateWhat It Catches
TestsInvalid implementations
BuildsCompilation errors
LintersStyle inconsistencies
TypecheckersContract violations
LLM-as-judgeSubjective quality issues

State Persistence

The only persistent state between iterations is the file system:

FilePurposeManaged By
IMPLEMENTATION_PLAN.mdTask list and progressPlanning and Building modes
specs/*.mdSpecification filesspec-writing skill
AGENTS.mdOperational notes and learningsBuilding mode
Source code + testsThe actual implementationBuilding mode

IMPLEMENTATION_PLAN.md is disposable — it can be regenerated from specs at any time by running a planning iteration.


Anti-Patterns / Common Mistakes

Anti-PatternWhy It FailsCorrect Approach
Multiple tasks per iterationContext switching, unclear progressONE task per loop
Assuming code is missingMay exist elsewhere, leads to duplicationAlways search first
Skipping tests after implementationBugs accumulate, no backpressureRun tests IMMEDIATELY
Modifying plan only during planningPlan drifts from realityUpdate during BOTH planning and building
Keeping stale plansTasks based on outdated assumptionsRegenerate liberally — planning is cheap
Manual context managementMain context overflowsTrust subagent delegation
Exiting without dual-conditionPremature exit, work incompleteBoth conditions must be true
Not committing after each taskLarge changesets, hard to revertCommit every iteration
Placeholder or stub codeIncomplete implementations accumulateProduction-quality code only
Skipping STATUS CHECKNo exit evaluation, loop runs foreverEvery iteration ends with status

Anti-Rationalization Guards

If you catch yourself thinking:

  • "I can do two quick tasks in this iteration..." — No. ONE task per loop.
  • "The plan is probably fine, skip planning mode..." — Verify. Plans drift.
  • "Tests can wait until the next iteration..." — Run tests NOW. Backpressure is essential.
  • "Everything is done, I can exit..." — Check the dual-condition gate. Both must be true.

Subagent Dispatch Opportunities

Task PatternDispatch ToWhen
Independent file reads across codebaseAgent tool with subagent_type="Explore"When loop iteration needs context from multiple areas
Test execution during build phaseBash tool with run_in_background=trueWhen tests can validate work without blocking progress
Code review between iterationsAgent tool dispatching code-reviewer agentAfter completing a build iteration, before next planning

Follow the dispatching-parallel-agents skill protocol when dispatching.


Integration Points

SkillRelationshipWhen
ralph-statusPer-iteration — produces status blocksPhase 3: STATUS CHECK
circuit-breakerSafety net — monitors loop healthHalts on stagnation
spec-writingUpstream — creates specs consumed by planningBefore loop starts
acceptance-testingValidation — validates behavioral outcomesDuring building mode
resilient-executionPer-task — retry on failureWhen task implementation fails
task-managementTracking — tracks individual tasksWithin iterations
llm-as-judgeQuality — evaluates subjective criteriaDownstream steering
verification-before-completionFinal gate — verifies completion claimBefore EXIT_SIGNAL: true

Concrete Examples

Example: Planning Mode Output

IMPLEMENTATION_PLAN.md:
- [x] Set up project structure
- [x] Implement core data types
- [ ] Implement user authentication (P0 — blocks 3 other tasks)
- [ ] Add API rate limiting (P1)
- [ ] Implement webhook handlers (P1)
- [ ] Add monitoring and logging (P2)

Missing specs: Rate limiting spec needs error response format defined.

Example: Building Mode Iteration

Task selected: Implement user authentication
Searched: Found existing password hashing in src/lib/crypto.ts
Implemented: src/auth/service.ts, src/auth/middleware.ts
Tests: 8 passing, 0 failing
Committed: feat(auth): implement JWT-based user authentication

Updated IMPLEMENTATION_PLAN.md:
- [x] Implement user authentication

Example: Status Block

---RALPH_STATUS---
STATUS: IN_PROGRESS
TASKS_COMPLETED_THIS_LOOP: 1
FILES_MODIFIED: 4
TESTS_STATUS: PASSING
WORK_TYPE: IMPLEMENTATION
EXIT_SIGNAL: false
RECOMMENDATION: Next: implement API rate limiting (P1)
---END_RALPH_STATUS---

Skill Type

RIGID — Follow this process exactly. The determinism of the loop depends on consistent execution. ONE task per loop. Status block every iteration. Dual-condition exit gate. No exceptions.

平台分布

Codex

36.75%
按下载量换算91

Claude

30.21%
按下载量换算75

Cursor

18.33%
按下载量换算45

Gemini CLI

10.04%
按下载量换算25

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

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。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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