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Agent Skill · 研究检索

rotifer-agent(轮虫剂)

rotifer-agent 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。

rotifer-agent 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;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 32,343。

总安装 2,540周安装 108GitHub Stars 公开资料未说明下载 890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
1.0.3

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:rotifer-agent(轮虫剂)
来源仓库:https://github.com/xiaoba-dev/rotifer-agent
安装命令:
openclaw skills install rotifer-agent
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 rotifer-agent

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。

端到端构建 AI 代理的基因选择与组装指南。分解意图后匹配合适技能模块形成完整能力集。包含测试方法与性能评估标准参考框架。rotifer-agent 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合高级用户定制专属智能体行为模式。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

依赖 ClawHub 生态提供底层技能库支持。

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 rotifer-agent;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

    它需要调用外部服务,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

rotifer-agent 怎么安装?

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

rotifer-agent 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。

rotifer-agent 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

rotifer-agent 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。

rotifer-agent 用的人多吗?

公开数据是累计安装 2,540 次,近一周安装 108 次,下载 890 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。

rotifer-agent 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
rotifer-agent

轮虫剂 · 本页

2,540—调用外部服务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
rotifer-agent
description
>-

Rotifer Agent — From Genes to Agents

Decompose user intent into capability units, select Genes from the ecosystem, compose a Genome, create and validate an Agent.

Prerequisites

This Skill requires the Rotifer CLI:

npx @rotifer/playground --version

Or use the MCP Server for IDE integration:

{
  "mcpServers": {
    "rotifer": {
      "command": "npx",
      "args": ["@rotifer/mcp-server"]
    }
  }
}

Hierarchy: Gene (atomic logic) → Genome (composition) → Agent (runnable entity)


Phase 1: Intent Decomposition

Break the user's goal into independent capability units (each maps to a Gene).

Steps:

  1. Confirm the Agent's input and expected output with the user
  2. Decompose the task into 2–6 capability units, each satisfying the Gene three axioms (functional cohesion, self-sufficient interface, independently evaluable)
  3. Label each unit with a domain (e.g. content.grammar, security.audit)
  4. Confirm the decomposition with the user before proceeding to Phase 2

Output format:

#Capability unitDomainInputOutput
1Grammar checkcontent.grammartextissues[], score
2Readability analysiscontent.readabilitytextgrade, suggestions[]

Phase 2: Gene Selection

Match existing Genes to each capability unit.

rotifer list
rotifer arena list --domain <domain>

Selection priority:

PrioritySourceCommand
1Local Gene with highest Arena rankrotifer arena list --domain <d>
2Cloud Registryrotifer install <name>
3Doesn't exist, needs creationProceed to Phase 3

Show the user candidate Genes' F(g) fitness and fidelity, let them confirm the selection.


Phase 3: Gap Filling

If a capability unit has no existing Gene:

ApproachWhen to useAction
Create Wrapped GeneExternal API / Skill available to wrapRoute to gene-dev Skill
Create Native GenePure computation, no external dependenciesRoute to gene-dev Skill
Adjust decompositionCapability unit granularity is wrongReturn to Phase 1
Merge unitsTwo units are too coupled, splitting makes the interface awkwardMerge into one Gene

After all Genes are ready, proceed to Phase 4.


Phase 4: Genome Composition

Choose a composition strategy based on relationships between capability units.

Composition Strategy Decision Table

StrategySemanticsUse whenExample
Seq(A, B, C)Pipeline: A → B → CPrevious output feeds the nextCheck → Fix → Format
Par(A, B)Parallel: run simultaneouslyIndependent tasks, merge resultsGrammar check + Readability analysis
Cond(p, A, B)Branch: if p then A else BInput characteristics determine pathChinese → Chinese proofing / English → English proofing
Try(A, B)Fallback: A fails → BPrimary path unreliableMain API → Backup API
TryPool(A, B, C)Race: all try, first success winsMultiple equivalent implementationsMultiple translation services racing

Par Merge Strategies

When using Par, specify --par-merge:

StrategyBehaviorUse when
firstTake the first completed resultRacing scenario
concatConcatenate all results (array)Results are complementary
mergeDeep-merge objectsSame structure, merge fields

Seq Schema Compatibility Warning

Known limitation: Seq composition requires the previous Gene's outputSchema to be compatible with the next Gene's inputSchema. The current version does not auto-validate — schema mismatches cause runtime errors. Recommendation: Before creating a Seq composition, manually compare adjacent Genes' inputSchema / outputSchema in phenotype.json to confirm field names and types match.

Nested Composition

Strategies can be nested:

Seq(
  Par(grammar-checker, readability-analyzer),
  tone-analyzer
)

Corresponding CLI:

rotifer agent create doc-qa \
  --genes grammar-checker readability-analyzer tone-analyzer \
  --composition Seq
The current CLI only supports top-level composition strategies. Nested compositions require manual editing of .rotifer/agents/<id>.json.

Phase 5: Agent Creation

Execute creation after confirming the composition plan.

Manual Gene Selection

rotifer agent create <name> \
  --genes <gene1> <gene2> <gene3> \
  --composition <Seq|Par|Cond|Try|TryPool> \
  --par-merge <first|concat|merge>

Auto-select Genes (by domain ranking)

rotifer agent create <name> \
  --domain <domain> \
  --top <n> \
  --composition <strategy>

After creation, verify the Agent configuration file .rotifer/agents/<name>.json is correct.


Phase 6: Test Run

rotifer agent run <name> --input '{"text": "Test input content"}'

Validation checklist:

  • Does the output structure match the expected schema?
  • Were all Genes executed? (check logs)
  • Is schema passing correct in Seq composition?
  • Are Par merge results complete?
  • Do error paths (Try/TryPool) degrade correctly?

If results are unsatisfactory, proceed to Phase 7.


Phase 7: Iterative Optimization

ProblemOptimization
One Gene's output quality is poorrotifer arena list --domain <d> to find alternatives
Seq intermediate results missing fieldsCheck schema compatibility, consider inserting an adapter Gene
Par merge results are messySwitch --par-merge strategy
Latency too highSeq → Par (if Genes are independent)
Overall below expectationsRoute to rotifer-arena Skill for head-to-head Gene evaluation

Scenario Examples

Scenario 1: Document Quality Agent

Goal: Input text, output grammar issues + readability score + tone analysis.

Decomposition:

#CapabilityGeneDomain
1Grammar checkgrammar-checkercontent.grammar
2Readability analysisreadability-analyzercontent.readability
3Tone analysistone-analyzercontent.tone

Composition: All three accept text input, no dependencies → Par + concat.

rotifer agent create doc-quality \
  --genes grammar-checker readability-analyzer tone-analyzer \
  --composition Par \
  --par-merge concat

rotifer agent run doc-quality --input '{"text": "Document content to check..."}'

Scenario 2: Code Review Agent

Goal: Input code file, output security vulnerabilities + complexity report + documentation suggestions.

#CapabilityGeneDomain
1Security auditsecurity-auditorsecurity.audit
2Complexity analysiscode-complexitycode.analysis
3Documentation generationdocs-writercontent.docs

Composition: Security audit and complexity analysis can run in parallel, documentation depends on both → Seq(Par(1,2), 3).

rotifer agent create code-review \
  --genes security-auditor code-complexity docs-writer \
  --composition Seq

rotifer agent run code-review --input '{"code": "...", "language": "typescript"}'
Note: The Par(security-auditor, code-complexity) merged output must be compatible with docs-writer's inputSchema. Manual verification required.

Scenario 3: Search & Summarize Agent

Goal: Input a search query, search → summarize → format output.

#CapabilityGeneDomain
1Web searchgenesis-web-searchsearch.web
2Text summarizationtext-summarizercontent.summarize
3Markdown formattingmarkdown-formattercontent.format

Composition: Strict serial pipeline → Seq.

rotifer agent create search-digest \
  --genes genesis-web-search text-summarizer markdown-formatter \
  --composition Seq

rotifer agent run search-digest --input '{"query": "Rotifer Protocol agent framework"}'
Note the Seq schema chain: genesis-web-search output field names must match text-summarizer's inputSchema. Run cat genes/*/phenotype.json | jq '.inputSchema, .outputSchema' to verify before creating.

Related Skills

SkillRelationshipWhen to route
gene-devGene creation/developmentPhase 3 gap filling
rotifer-arenaGene comparison & evaluationPhase 7 when replacing underperforming Genes
genomeGenome quality analysisAfter Agent creation for overall assessment

Constraints

  • Agent configuration files are stored in .rotifer/agents/<id>.json and should not be committed to Git
  • A single Agent should contain 2–6 Genes; more than 6 suggests splitting into multiple Agents
  • Seq schema compatibility is a known limitation — always verify manually before creating
  • Nested compositions require manual JSON editing; the CLI only supports top-level strategies

平台分布

OpenClaw

77.77%
按下载量换算692

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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