rotifer-agent

End-to-end guide for building AI Agents from Genes: intent decomposition, Gene selection, Genome composition, Agent creation, and testing. Use when the user mentions "build Agent", "compose Genes", "Agent composition", "agent create", "agent run", "Genome", "assemble Agent", "Agent architecture", "composition strategy", "Seq", "Par", "Cond", "Try", "TryPool", "synthesize Agent".

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Install skill "rotifer-agent" with this command: npx skills add xiaoba-dev/rotifer-agent

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

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