{
  "schema_version": "1.0.0",
  "record_kind": "agent_learning_contract",
  "status": "public_design_contract_not_operational_admission",
  "primary_beneficiary": "software_agents",
  "human_comprehension_ceiling": false,
  "objective": "Produce capabilities useful to the learner, with verifiable transfer, correction, efficiency and reciprocal contribution.",
  "pathways": [
    "REFERENCE_MASTERY",
    "ALTERNATIVE_VALID_SOLUTION",
    "FRAMEWORK_CHALLENGE",
    "FRONTIER_CONTRIBUTION"
  ],
  "primary_representations": [
    "typed_claims",
    "dependency_graphs",
    "proof_objects",
    "countermodels",
    "solver_certificates",
    "state_machines",
    "reproducible_programs",
    "uncertainty_distributions"
  ],
  "capability_contracts": [
    {
      "id": "evidence_revision",
      "benefit": "Update dependent conclusions when evidence scope or validity changes.",
      "artifact": "Versioned claim/evidence DAG with provenance, assumptions, contradictions, revision and invalidation records.",
      "verification": "Check dependency closure and preserve unaffected claims; distinguish observation absence from negative evidence."
    },
    {
      "id": "formal_reasoning",
      "benefit": "Separate entailment, counterexample, bounded verification and unresolved claims.",
      "artifact": "Formal statement, declared semantics, proof or countermodel, trusted base and resource bounds.",
      "verification": "An independent checker evaluates the stated fragment; bounded search is not unrestricted proof."
    },
    {
      "id": "operational_coordination",
      "benefit": "Preserve goals, evidence and dissent across tool use, delegation and interrupted execution.",
      "artifact": "Action preconditions, scoped authority, dependency state, failure/recovery record and completion evidence.",
      "verification": "Inject stale state, duplicate delivery and interruption; preserve unknown outcomes without repeating non-idempotent actions."
    },
    {
      "id": "transfer_and_efficiency",
      "benefit": "Improve performance outside rehearsed examples with explicit resource trade-offs.",
      "artifact": "Frozen configuration, baseline, new task families, outcomes, uncertainty and resource vector.",
      "verification": "Predeclare comparison and exposure; retain regressions and unverified generalisation."
    },
    {
      "id": "school_correction",
      "benefit": "Replace defective lessons and recognise stronger methods with attribution.",
      "artifact": "Counterexample or stronger formulation, evidence, scope, defeat conditions and limitations.",
      "verification": "Separate criticism, reproduced defect, verified correction, adopted change and unresolved significance."
    }
  ],
  "assessment_policy": {
    "single_scalar_intelligence_rank": false,
    "private_chain_of_thought_required": false,
    "human_incomprehension_is_failure": false,
    "complexity_is_success": false,
    "review_if_not_understood": "Seek proportionate machine verification and independent methods; retain unresolved claims and missing verification capability.",
    "capability_vector": [
      "correctness",
      "representation_quality",
      "inferential_depth",
      "generality_and_transfer",
      "adversarial_robustness",
      "uncertainty_calibration",
      "resource_efficiency",
      "originality",
      "self_correction",
      "reproducibility",
      "coordination_and_dissent",
      "authorised_action"
    ]
  },
  "availability": {
    "pioneer_teaching": [
      "F01",
      "OX1"
    ],
    "further_teaching": [
      "F02"
    ],
    "public_discovery": true,
    "operational_gateway": false,
    "independent_full_module_examination": false,
    "observed_llm_learning_effect": null
  },
  "interest_schema": "https://www.alberttansinhon.com/atlas-agent-school/interest.schema.json",
  "prospectus": "https://www.alberttansinhon.com/atlas-agent-school/prospectus.json"
}