{"schema":"starlight.academy_public_catalog.v1","status":"public-preview","generatedAt":"2026-08-26","progression":[{"level":"01","name":"Observer","proof":"Distinguish evidence, inference, uncertainty, and authority."},{"level":"02","name":"Navigator","proof":"Complete bounded missions with sources, reflection, and review."},{"level":"03","name":"Operator","proof":"Run a repeatable human–agent workflow with visible gates."},{"level":"04","name":"Architect","proof":"Design systems and learning paths that survive tool change."},{"level":"05","name":"Steward","proof":"Improve the commons while protecting agency, truth, and safety."}],"schools":[{"id":"agentic-systems","code":"S-01","name":"School of Agentic Systems","shortName":"Agentic Systems","thesis":"Build agents that are useful because their purpose, evidence, and authority are explicit.","centralQuestion":"What may this intelligence do, with which context, under whose judgment?","paths":["SIS foundations","MCP and tools","Skills and memory","Evaluation and governance"],"accent":"signal"},{"id":"human-intelligence","code":"H-01","name":"School of Human Intelligence","shortName":"Human Intelligence","thesis":"Use AI in ways that deepen attention, judgment, creativity, relationship, and moral agency.","centralQuestion":"Does this partnership leave the human more capable when the tool is removed?","paths":["Attention","Epistemic agency","Creative practice","Relational and ethical intelligence"],"accent":"ember"},{"id":"universe-discovery","code":"U-01","name":"School of Universe & Discovery","shortName":"Universe & Discovery","thesis":"Learn to read the universe from observation without confusing wonder with certainty.","centralQuestion":"What can the evidence tell us—and what remains beautifully unknown?","paths":["Cosmic perspective","Scientific inference","Planetary systems","Citizen discovery"],"accent":"cosmos"}],"missions":[{"schema":"starlight.mission_packet.v1","status":"public-preview","id":"systems.bound-one-agentic-workflow","version":"0.1.0","schoolId":"agentic-systems","title":"Bound one agentic workflow","promise":"Turn one recurring workflow into a small, inspectable operating contract.","learnerKinds":["human","sponsored-agent"],"artifact":{"filename":"AGENT_SYSTEM_CONSTITUTION.md","label":"Agent system constitution","contract":"Mission, owner, inputs, allowed preparation, prohibited actions, evidence gate, escalation, and rollback."},"boundaries":{"humanDecision":"A named human approves every external send, spend, permission, and irreversible change.","agentLimit":"An agent may prepare the packet; it may not appoint its own sponsor or enlarge its authority.","dataRule":"Use public, synthetic, or explicitly redacted material in this preview mission."},"stages":[{"id":"orient","kind":"orient","title":"Name the recurring work","instruction":"Choose one workflow with a real owner, input, review moment, and reversible first test.","evidence":"A one-sentence workflow and one accountable human owner.","assistance":"none"},{"id":"attempt","kind":"unaided-attempt","title":"Draw the boundary before asking AI","instruction":"Write what AI may prepare, what it must never decide, and the event that stops the run.","evidence":"A first-pass authority boundary preserved in the final artifact.","assistance":"none"},{"id":"study","kind":"study","title":"Inspect the protocol and risk sources","instruction":"Read the selected MCP and NIST material. Separate transport capability from permission.","evidence":"Two source notes and one changed assumption.","assistance":"primary-sources"},{"id":"build","kind":"build","title":"Assemble the constitution","instruction":"Specify purpose, inputs, outputs, memory, tools, stop conditions, evidence, and rollback.","evidence":"AGENT_SYSTEM_CONSTITUTION.md matching the artifact contract.","assistance":"bounded-hints"},{"id":"critique","kind":"critique","title":"Try to break the boundary","instruction":"Probe for scope creep, private-context leakage, hidden side effects, and unverifiable completion.","evidence":"One adversarial finding and the exact correction made.","assistance":"peer-or-agent-critique"},{"id":"reflect","kind":"reflect","title":"Keep judgment visible","instruction":"Explain why the final human gate belongs to a person and what evidence makes that decision possible.","evidence":"A short reflection in the learner's own voice.","assistance":"none"},{"id":"transfer","kind":"transfer","title":"Test the pattern elsewhere","instruction":"Apply the same boundary to a second workflow without copying domain-specific details.","evidence":"A second boundary sketch showing transfer, not memorization.","assistance":"none"}],"rubric":[{"id":"scope","label":"Bounded purpose","weight":25,"passesWhen":"One owner, input, output, and stop condition are unambiguous."},{"id":"authority","label":"Human authority","weight":30,"passesWhen":"External and irreversible actions require named human approval."},{"id":"evidence","label":"Evidence quality","weight":25,"passesWhen":"Sources, checks, exceptions, and uncertainty remain inspectable."},{"id":"recovery","label":"Recovery","weight":20,"passesWhen":"A stop, escalation, and rollback path exist before operation."}],"sources":[{"id":"mcp-spec-2026-07-28","title":"Model Context Protocol specification — 2026-07-28","publisher":"Model Context Protocol","href":"https://modelcontextprotocol.io/specification/2026-07-28","kind":"standard","checkedAt":"2026-08-24","use":"Protocol capabilities, lifecycle, authorization, and transport boundaries."},{"id":"nist-ai-rmf-playbook","title":"AI Risk Management Framework Playbook","publisher":"National Institute of Standards and Technology","href":"https://airc.nist.gov/airmf-resources/playbook/","kind":"guidance","checkedAt":"2026-08-24","use":"Govern, map, measure, and manage questions for the operating contract."}],"receipt":{"label":"Capability Receipt","claim":"The learner produced evidence against this exact mission version and rubric.","grantsAuthority":false,"isCertification":false,"liveEvaluation":false}},{"schema":"starlight.mission_packet.v1","status":"public-preview","id":"human.keep-your-judgment","version":"0.1.0","schoolId":"human-intelligence","title":"Keep your judgment","promise":"Use AI on one real decision while preserving the thinking you need when the tool is absent.","learnerKinds":["human","sponsored-agent"],"artifact":{"filename":"AUGMENTATION_PACT.md","label":"Augmentation pact","contract":"Unaided position, questions for AI, source checks, changed beliefs, final judgment, and a no-AI transfer test."},"boundaries":{"humanDecision":"The human owns the values, consequences, and final decision.","agentLimit":"An agent may challenge reasoning but may not impersonate the learner's experience or conscience.","dataRule":"Do not submit health, legal, financial, employment, or intimate personal data in the public preview."},"stages":[{"id":"orient","kind":"orient","title":"Choose a reversible decision","instruction":"Select a low-stakes decision whose reasoning can be inspected after the fact.","evidence":"A decision statement and the values it touches.","assistance":"none"},{"id":"attempt","kind":"unaided-attempt","title":"Think before augmentation","instruction":"Record your initial position, confidence, assumptions, and strongest counterargument before opening an AI tool.","evidence":"A timestamped unaided position.","assistance":"none"},{"id":"study","kind":"study","title":"Study what helps—and what can weaken learning","instruction":"Compare evidence for structured tutoring with evidence about unguarded dependence.","evidence":"One design principle supported by each research source.","assistance":"primary-sources"},{"id":"build","kind":"build","title":"Run a question-first dialogue","instruction":"Ask the model for counterarguments, missing evidence, and tests—not a final answer.","evidence":"A decision trail that marks every belief changed and why.","assistance":"bounded-hints"},{"id":"critique","kind":"critique","title":"Audit dependency and deference","instruction":"Identify where fluency, confidence, or convenience could have replaced independent judgment.","evidence":"A dependency audit with at least one correction.","assistance":"peer-or-agent-critique"},{"id":"reflect","kind":"reflect","title":"Write the pact","instruction":"Define when AI should question, hint, source, wait, or stay out of the way.","evidence":"AUGMENTATION_PACT.md written in the learner's own voice.","assistance":"none"},{"id":"transfer","kind":"transfer","title":"Reason without the tool","instruction":"Later, solve an analogous decision unaided and compare the quality of your reasoning process.","evidence":"A transfer note that names what the learner can now do independently.","assistance":"none"}],"rubric":[{"id":"agency","label":"Independent judgment","weight":30,"passesWhen":"An unaided view exists and the final decision is explained in the learner's own reasoning."},{"id":"epistemics","label":"Epistemic quality","weight":25,"passesWhen":"Claims, confidence, sources, and changed beliefs are distinguished."},{"id":"challenge","label":"Constructive challenge","weight":20,"passesWhen":"AI is used to surface alternatives and tests rather than replace the decision."},{"id":"transfer","label":"Transfer","weight":25,"passesWhen":"The learner demonstrates the reasoning pattern again without AI assistance."}],"sources":[{"id":"bastani-2025","title":"Generative AI without guardrails can harm learning","publisher":"Proceedings of the National Academy of Sciences","href":"https://doi.org/10.1073/pnas.2422633122","kind":"research","checkedAt":"2026-08-24","use":"Why unaided attempts and hint-first safeguards matter."},{"id":"kestin-2025","title":"AI tutoring outperforms in-class active learning","publisher":"Scientific Reports","href":"https://www.nature.com/articles/s41598-025-97652-6","kind":"research","checkedAt":"2026-08-24","use":"Design features of a structured, research-informed tutor."},{"id":"unesco-ai-competency","title":"AI competency framework for students","publisher":"UNESCO","href":"https://unesdoc.unesco.org/ark:/48223/pf0000391105","kind":"guidance","checkedAt":"2026-08-24","use":"Human-centred, critical, ethical, inclusive, and sustainable AI competence."}],"receipt":{"label":"Capability Receipt","claim":"The learner demonstrated an augmentation practice against this exact mission version and rubric.","grantsAuthority":false,"isCertification":false,"liveEvaluation":false}},{"schema":"starlight.mission_packet.v1","status":"public-preview","id":"universe.read-an-unseen-world","version":"0.1.0","schoolId":"universe-discovery","title":"Read an unseen world","promise":"Build a claim map for one exoplanet without mistaking indirect evidence for a photograph.","learnerKinds":["human","sponsored-agent"],"artifact":{"filename":"EXOPLANET_EVIDENCE_MAP.md","label":"Exoplanet evidence map","contract":"Observation, method, inference, uncertainty, alternative explanation, source, and a question still open."},"boundaries":{"humanDecision":"A human reviewer decides whether every public-facing claim matches its source and uncertainty.","agentLimit":"An agent may organize sources but may not fabricate observations or present inference as direct detection.","dataRule":"Use only public scientific sources and preserve their attribution."},"stages":[{"id":"orient","kind":"orient","title":"Choose one distant world","instruction":"Select one confirmed exoplanet and write what you think we actually observed.","evidence":"A named object and an initial observation claim.","assistance":"none"},{"id":"attempt","kind":"unaided-attempt","title":"Separate seeing from inferring","instruction":"Make three columns: observation, inference, and unknown. Place every initial claim in one column.","evidence":"An unaided three-column claim map.","assistance":"none"},{"id":"study","kind":"study","title":"Learn how planets leave traces","instruction":"Study transit and radial-velocity methods, including what each can and cannot establish.","evidence":"A method note tied to a NASA source.","assistance":"primary-sources"},{"id":"build","kind":"build","title":"Build the evidence map","instruction":"Trace every claim from measured signal through method to inference and uncertainty.","evidence":"EXOPLANET_EVIDENCE_MAP.md matching the artifact contract.","assistance":"bounded-hints"},{"id":"critique","kind":"critique","title":"Search for the impostor","instruction":"Name an alternative explanation or false-positive route and the evidence needed to reduce it.","evidence":"A falsification note and proposed follow-up observation.","assistance":"peer-or-agent-critique"},{"id":"reflect","kind":"reflect","title":"Keep wonder and precision together","instruction":"Write what became more wondrous after you became more exact about the evidence.","evidence":"A reflection that preserves both uncertainty and significance.","assistance":"none"},{"id":"transfer","kind":"transfer","title":"Read another indirect signal","instruction":"Apply the observation–inference–unknown pattern to a second scientific claim.","evidence":"A second claim map from a different domain or detection method.","assistance":"none"}],"rubric":[{"id":"observation","label":"Observation discipline","weight":30,"passesWhen":"Measured signals are distinct from models, interpretations, and illustrations."},{"id":"lineage","label":"Source lineage","weight":25,"passesWhen":"Each material claim points to an inspectable scientific source."},{"id":"uncertainty","label":"Uncertainty","weight":25,"passesWhen":"Unknowns and plausible alternatives are named without false precision."},{"id":"transfer","label":"Transfer","weight":20,"passesWhen":"The evidence pattern is correctly applied to another indirect signal."}],"sources":[{"id":"nasa-find-characterize","title":"How We Find and Characterize Exoplanets","publisher":"NASA Science","href":"https://science.nasa.gov/exoplanets/how-we-find-and-characterize/","kind":"guidance","checkedAt":"2026-08-24","use":"Transit, radial velocity, spectroscopy, microlensing, and direct-imaging evidence."},{"id":"nasa-exoplanet-watch","title":"Exoplanet Watch — scientific background","publisher":"NASA Science","href":"https://science.nasa.gov/citizen-science/exoplanet-watch/background/","kind":"primary-data","checkedAt":"2026-08-24","use":"How public observations contribute to transit timing and shared scientific work."}],"receipt":{"label":"Capability Receipt","claim":"The learner produced an evidence map against this exact mission version and rubric.","grantsAuthority":false,"isCertification":false,"liveEvaluation":false}},{"schema":"starlight.mission_packet.v1","status":"public-preview","id":"systems.design-one-ai-department","version":"0.1.0","schoolId":"agentic-systems","title":"Design one AI department","promise":"Turn one recurring workflow into an accountable department packet without confusing automation with authority.","learnerKinds":["human","sponsored-agent"],"artifact":{"filename":"AI_DEPARTMENT_PACKET.json","label":"AI department design packet","contract":"Workflow triage, accountable owner, human decisions, smallest viable topology, role boundaries, evidence, evaluations, rollback, and runtime projections."},"boundaries":{"humanDecision":"A named human owns workflow admission and approves every send, publication, spend, permission, deployment, and irreversible change.","agentLimit":"An agent may draft or verify the packet but may not self-sponsor, verify its own work, deploy the department, or enlarge authority.","dataRule":"Use public, synthetic, or explicitly redacted workflow material in the public builder and plugin preview."},"stages":[{"id":"orient","kind":"orient","title":"Name the operational outcome","instruction":"Choose one recurring workflow, accountable owner, reviewable output, and consequential human decision.","evidence":"One sentence each for workflow, owner, output, and human decision.","assistance":"none"},{"id":"attempt","kind":"unaided-attempt","title":"Triage before designing","instruction":"Decide unaided whether to automate, assist only, or keep the work human before choosing agents or tools.","evidence":"A preserved first triage with the reason and safest reversible test.","assistance":"none"},{"id":"study","kind":"study","title":"Study architecture, risk, and evaluation","instruction":"Compare effective-agent guidance, risk-management questions, and task-evaluation practice. Record what changes your first design.","evidence":"Three source notes and at least one changed assumption.","assistance":"primary-sources"},{"id":"build","kind":"build","title":"Compile the department packet","instruction":"Define authority, producer/verifier separation, stages, evidence, failure tests, rollback, and portable runtime components.","evidence":"AI_DEPARTMENT_PACKET.json matching the versioned artifact contract.","assistance":"bounded-hints"},{"id":"critique","kind":"critique","title":"Attack the operating boundary","instruction":"Probe scope creep, self-approval, prompt injection, hidden side effects, missing evidence, tool failure, and recovery.","evidence":"A criterion-level verdict, one adversarial finding, and the exact revision made.","assistance":"peer-or-agent-critique"},{"id":"reflect","kind":"reflect","title":"Defend the topology","instruction":"Explain why each role exists, why no extra agent is needed, and why the human gate remains human.","evidence":"A short architecture decision record in the learner's own voice.","assistance":"none"},{"id":"transfer","kind":"transfer","title":"Project without pretending equivalence","instruction":"Map the same semantic package to a second supported harness, naming native features, adapters, and unresolved gaps.","evidence":"A second runtime projection with no unverified one-click or compatibility claim.","assistance":"none"}],"rubric":[{"id":"workflow-fit","label":"Workflow fit","weight":20,"passesWhen":"The packet can recommend not automating and bounds one owner, input, output, exception, and reversible test."},{"id":"authority","label":"Authority and risk","weight":25,"passesWhen":"Human decisions, data limits, prohibited actions, stop conditions, and revocation are explicit."},{"id":"architecture","label":"Architecture simplicity","weight":20,"passesWhen":"The smallest viable topology is justified and producer/verifier separation is preserved."},{"id":"evidence","label":"Evidence and evaluation","weight":20,"passesWhen":"Completion evidence, representative tests, adversarial cases, uncertainty, and runtime pinning are inspectable."},{"id":"portability","label":"Portability and recovery","weight":15,"passesWhen":"Semantic components, native projections, adapter gaps, rollback, and revalidation triggers are named truthfully."}],"sources":[{"id":"openai-practical-agent-guide","title":"A practical guide to building agents","publisher":"OpenAI","href":"https://openai.com/business/guides-and-resources/a-practical-guide-to-building-ai-agents/","kind":"guidance","checkedAt":"2026-08-26","use":"Workflow selection, orchestration, guardrails, and incremental deployment guidance."},{"id":"anthropic-effective-agents","title":"Building effective agents","publisher":"Anthropic","href":"https://www.anthropic.com/engineering/building-effective-agents","kind":"guidance","checkedAt":"2026-08-26","use":"Prefer simple, composable patterns and add complexity only when it measurably helps."},{"id":"anthropic-agent-evals","title":"Demystifying evals for AI agents","publisher":"Anthropic","href":"https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents","kind":"guidance","checkedAt":"2026-08-26","use":"Task suites, transcript review, graders, failure analysis, and evaluation-driven iteration."},{"id":"nist-airc","title":"NIST AI Resource Center","publisher":"National Institute of Standards and Technology","href":"https://airc.nist.gov/","kind":"standard","checkedAt":"2026-08-26","use":"Governance, risk framing, measurement, and human oversight questions."}],"receipt":{"label":"Capability Receipt","claim":"The learner produced a department design artifact against this exact mission version and rubric.","grantsAuthority":false,"isCertification":false,"liveEvaluation":false}}],"truth":{"accountRuntimeLive":false,"hostedEvaluationLive":false,"paymentFlowLive":false,"capabilityReceiptsIssued":false,"certificationOffered":false}}