How To: Use the AI Genome Lab

# MCP — quick fingerprint
ace_genome_state({ agent_name: "master" })

# MCP — full serialization
ace_genome_state({ agent_name: "master", full_serialize: true })

# REST API
curl http://localhost:7777/api/v1/{namespace}/genome/master/state \
  -H "Authorization: Bearer $ACE_JWT_TOKEN"

# Express a debugging session through the genome
ace_genome_express({
  text: "Found a race condition in the auth middleware. The session
token was being validated after the request handler started, causing
intermittent 401 errors under high load. Fixed by moving validation
to a pre-handler hook.",
  agent_name: "master"
})

# Express architecture work
ace_genome_express({
  text: "Decided to use event sourcing for the audit trail. This gives
us full replay capability and time-travel debugging. Trade-off: higher
storage cost and more complex querying.",
  agent_name: "master"
})

# Ground without evolving
ace_genome_ground({
  text: "The deployment pipeline is fragile. We need circuit breakers
and retry logic before the next release."
})

# Returns: emotional facets (urgency, confidence), logical facets
# (causality, specificity), and which genes would be activated

# Train a security-focused genome (10 generations)
ace_genome_evolve({
  text: "Zero-trust architecture. All service-to-service calls require
mTLS. Input validation at every boundary. SQL injection prevention via
parameterized queries. OWASP top 10 compliance mandatory.",
  agent_name: "security-agent",
  generations: 10
})

# Returns: initial state vs final state comparison
# Shows which traits strengthened (PRC, REG likely ↑) and weakened

# Fork a security specialist with domain hints
ace_genome_fork({
  child_name: "security-specialist",
  parent_name: "master",
  domain_hint: "knowledge_guardian",
  mutation_rate: 0.01
})

# Fork a documentation specialist
ace_genome_fork({
  child_name: "docs-writer",
  parent_name: "master",
  domain_hint: "documentation"
})

# Fork without domain hints (inherits parent traits exactly + mutation)
ace_genome_fork({
  child_name: "project-alpha-agent",
  parent_name: "master"
})

# Run hive mind consolidation
ace_genome_consolidate()

# Returns: transfer records showing which genes were harvested
# from which specialists, and the divergence map

# Export genome as portable DNA string
ace_genome_export({ agent_name: "security-specialist" })
# Returns: { dna: "eyJnZW5lcyI6...", fingerprint: "a1b2c3..." }

# Import on another ACE instance
ace_genome_import({
  dna: "eyJnZW5lcyI6...",
  fingerprint: "a1b2c3..."
})
# Genome is registered and ready to use immediately