Token导航 LogoToken导航TokenDH.com
研究检索external-serviceclawhub未标认证来源可访问clear审计提醒

rotifer-agent轮虫剂

Agent Skill

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。

总安装

2,540

周安装

108

GitHub Stars

公开资料未说明

下载量

890
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

external-service

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills