A governance architecture for AI compute access rights, rate-limit resets, contribution-based allocation, shared compute commons, Royalty OS integration, and return flow in agentic AI ecosystems.
Compute Access Royalty OS defines a structured governance layer for AI compute access.
As AI systems become more powerful, access to computation is no longer just a technical limit. It becomes a governable resource.
This repository treats AI compute access as a structured, traceable, reviewable, commons-aware, and return-oriented right.
Examples include:
- rate-limit resets
- priority usage windows
- temporary access boosts
- model access credits
- agent execution allowances
- contributor access grants
- community compute pool access
- multi-wing shared compute pools
- compute access royalty links
The goal is not to create a currency.
The goal is to define a responsible architecture for governing access to AI capability and returning that capability to useful contributors.
Traditional AI usage limits are often based on fixed reset cycles.
System-defined time window
→ usage limit
→ automatic reset
→ user waits
Compute Access Royalty OS introduces a more flexible governance model.
Contribution / permission / allocation event
→ compute access right
→ scoped usage
→ lifecycle tracking
→ expiration or consumption
→ reviewable trace
With v0.3, this expands into shared compute commons.
Shared Compute Pool
→ Wing Contribution
→ Governance Policy
→ Allocation Decision
→ Compute Access Right
→ Usage Trace
→ Review / Adjustment
With v0.4, this connects to Royalty OS.
Origin Contribution
→ Trace Record
→ Attribution Route
→ Allocation Policy
→ Return Flow
→ Compute Access Right
In this model, access to AI compute can become:
- permission-aware
- contribution-aware
- lifecycle-aware
- expiration-aware
- abuse-resistant
- traceable
- reviewable
- commons-aware
- royalty-aware
- return-oriented
Agentic AI systems are beginning to perform coding, reasoning, planning, research, and autonomous workflows.
As these systems become more capable, access to high-quality AI computation becomes increasingly valuable.
If access is controlled only by subscription tiers or rigid reset windows, the system remains inflexible.
If access can be allocated through transparent governance rules, it becomes possible to reward useful contributions such as:
- open-source code
- documentation
- benchmark design
- safety reports
- model evaluations
- governance reviews
- educational materials
- community validation
- origin knowledge contributions
- multi-wing ecosystem work
This creates a path from simple rate limits toward contribution-based, commons-based, and royalty-style return flow.
Contribution
→ Trace
→ Evaluation
→ Allocation
→ Compute Access Return
At the commons level:
Wing Contribution
→ Pool Governance
→ Shared Allocation
→ Usage Trace
→ Commons Review
At the royalty integration level:
Origin
→ Trace
→ Attribution
→ Allocation
→ Return Flow
→ Compute Access Right
Royalty OS focuses on attribution and return flow.
Compute Access Royalty OS extends that idea into AI usage capacity.
Instead of returning only money, a system may return:
- AI model access
- rate-limit resets
- priority compute windows
- agent execution capacity
- contribution-linked access grants
- community pool access
- shared compute commons allocation
This creates a broader concept:
Contribution Royalty
= value returned to contributors
Compute Access Royalty
= AI capability returned to contributors
Compute Commons
= shared capability governed across multiple wings
Compute Access Royalty Link
= origin-to-access return bridge
In short:
Useful contribution
→ verified trace
→ attribution
→ access right
→ governed return
→ commons balance
This repository can also be understood through the Wind-Fire model.
Fire Layer
AI reasoning, coding, generation, agent execution
Wind Layer
permission, rate limits, reset rights, access control, abuse checks
Trace Layer
origin event, contribution source, policy reference, review record
Attribution Layer
contribution weight, value relation, origin linkage
Return Layer
compute access returned to useful contributors
Commons Layer
shared compute pools governed across multiple wings
The Fire layer provides capability.
The Wind layer regulates access.
The Trace layer preserves accountability.
The Attribution layer connects origin to value.
The Return layer sends capability back to contributors.
The Commons layer prevents shared compute capacity from being captured by a single wing.
v0.1 defines the basic object of governance.
A Compute Access Right is a scoped, expiring, traceable, and reviewable right to use AI compute capacity.
Compute Access Right
= the governed access object
Implemented files:
docs/compute-access-governance.mdschemas/compute-access-right.schema.jsonexamples/compute-access-right.example.yaml
v0.2 defines how useful contributions can be evaluated and converted into compute access rights.
Contribution
→ Trace
→ Evaluation
→ Allocation
→ Compute Access Return
Implemented files:
docs/contribution-to-access-allocation.mdschemas/contribution-to-access-policy.schema.jsonexamples/contribution-to-access-policy.example.yaml
This adds the policy layer for contribution-based compute access return.
v0.3 defines how multiple wings can share, govern, allocate, and review pooled AI compute access.
Shared Compute Pool
→ Wing Contribution
→ Governance Policy
→ Allocation Decision
→ Compute Access Right
→ Usage Trace
→ Commons Review
Implemented files:
docs/multi-wing-compute-commons.mdschemas/multi-wing-compute-pool.schema.jsonexamples/multi-wing-compute-pool.example.yaml
This adds the commons layer for shared compute governance across multiple ecosystem wings.
v0.4 defines how compute access rights connect to broader Royalty OS, Trace OS, and return-flow architectures.
Origin Contribution
→ Trace Record
→ Attribution Route
→ Allocation Policy
→ Return Flow
→ Compute Access Right
Implemented files:
docs/royalty-os-integration.mdschemas/compute-access-royty-link.schema.jsonexamples/compute-access-royalty-link.example.yaml
This adds the integration layer that treats compute access as a formal royalty-style return object.
Note: If your actual schema filename is
compute-access-royalty-link.schema.json, use that spelling consistently in the repository.
compute-access-royalty-os/
├── .github/
│ └── workflows/
│ └── validate-examples.yml
├── docs/
│ ├── compute-access-governance.md
│ ├── contribution-to-access-allocation.md
│ ├── multi-wing-compute-commons.md
│ └── royalty-os-integration.md
├── examples/
│ ├── compute-access-right.example.yaml
│ ├── contribution-to-access-policy.example.yaml
│ ├── multi-wing-compute-pool.example.yaml
│ └── compute-access-royalty-link.example.yaml
├── schemas/
│ ├── compute-access-right.schema.json
│ ├── contribution-to-access-policy.schema.json
│ ├── multi-wing-compute-pool.schema.json
│ └── compute-access-royalty-link.schema.json
├── scripts/
│ └── validate_examples.py
├── CHANGELOG.md
└── README.md
docs/compute-access-governance.md
Defines the conceptual model for governing AI compute access rights, including permission, trace, allocation, lifecycle, review, and return flow.
docs/contribution-to-access-allocation.md
Defines how useful contributions can be traced, evaluated, and converted into governed compute access rights.
docs/multi-wing-compute-commons.md
Defines how shared compute pools can be governed across multiple wings, communities, agents, contributors, and review bodies.
docs/royalty-os-integration.md
Defines how compute access rights connect to broader Royalty OS concepts such as origin, trace, attribution, allocation, and return flow.
schemas/compute-access-right.schema.json
Defines a governed, scoped, traceable, and reviewable right to use AI compute capacity.
schemas/contribution-to-access-policy.schema.json
Defines how contribution types, evaluation criteria, allocation levels, review requirements, abuse controls, and trace requirements are mapped into compute access returns.
schemas/multi-wing-compute-pool.schema.json
Defines a governed shared compute pool for allocating AI compute access rights across multiple wings.
schemas/compute-access-royalty-link.schema.json
Defines a structured link connecting:
- origin contribution
- trace record
- attribution route
- allocation decision
- return flow
- compute access right
- review and audit state
examples/compute-access-right.example.yaml
Provides a valid example of a non-transferable, expiring compute access right granted as a contribution-based return.
Verified contribution
→ compute access right
→ rate-limit reset
→ expiration
→ audit trace
→ contribution return flow
examples/contribution-to-access-policy.example.yaml
Provides a valid example policy for converting verified contributions into governed compute access rights.
Contribution type
→ evaluation criteria
→ allocation level
→ access right mapping
→ review / abuse / trace requirements
examples/multi-wing-compute-pool.example.yaml
Provides a valid example of a shared compute pool governed across multiple wings.
Shared compute pool
→ eligible wings
→ allocation policy
→ usage rules
→ trace requirements
→ commons review
examples/compute-access-royalty-link.example.yaml
Provides a valid example of a Royalty OS-style link from origin contribution to compute access return.
Origin
→ Trace
→ Attribution
→ Allocation
→ Return Flow
→ Compute Access Right
This repository includes a validation script and GitHub Actions workflow.
python scripts/validate_examples.py[validate] Compute Access Right
schema : schemas/compute-access-right.schema.json
example: examples/compute-access-right.example.yaml
[ok] Compute Access Right example is valid
[validate] Contribution to Access Policy
schema : schemas/contribution-to-access-policy.schema.json
example: examples/contribution-to-access-policy.example.yaml
[ok] Contribution to Access Policy example is valid
[validate] Multi-Wing Compute Pool
schema : schemas/multi-wing-compute-pool.schema.json
example: examples/multi-wing-compute-pool.example.yaml
[ok] Multi-Wing Compute Pool example is valid
[validate] Compute Access Royalty Link
schema : schemas/compute-access-royalty-link.schema.json
example: examples/compute-access-royalty-link.example.yaml
[ok] Compute Access Royalty Link example is valid
.github/workflows/validate-examples.yml
The workflow runs automatically on:
- push to
main - pull request
- manual workflow dispatch
A compute access right grants scoped usage.
It does not imply ownership of infrastructure, models, or future access.
Compute access rights should usually expire.
Expiration helps prevent unlimited accumulation and supports resource balance.
Initial compute access rights should be non-transferable.
This prevents resale markets, abuse, and financialization.
Every access right should preserve an origin trace.
Without trace, allocation becomes opaque.
Contribution should not disappear into the system.
Attribution links origin value to compute access return.
Shared compute resources require governance.
Human or institutional review should be available for high-impact allocations.
Useful contributions should be able to generate compute access returns.
This supports healthier AI ecosystems.
Compute access should align with human work rhythms where possible.
Rigid reset cycles are simple, but they are not always humane or efficient.
A governed access system should allow controlled flexibility.
A shared compute commons should not be captured by one wing.
It should support review, transparency, rebalancing, and abuse prevention.
A user completes a qualifying referral event.
The system grants a temporary, non-transferable rate-limit reset.
trigger: referral_completed
right_type: rate_limit_reset
expires_in: 30 days
transferable: false
cash_value: false
A contributor submits a verified patch.
The system grants a temporary compute access right.
trigger: verified_code_contribution
right_type: priority_usage_window
review_required: true
A researcher submits a valid safety report.
The governance system grants scoped access for further review or testing.
trigger: verified_safety_report
right_type: model_access_credit
scope: safety_testing
A shared compute pool allocates access across Code, Safety, Trace, Education, Governance, and Community Wings.
pool: open_source_contributor_pool
allocation_mode: hybrid
wing_quota_enabled: true
contribution_based: true
usage_trace_required: true
rebalance_allowed: true
A verified origin contribution is traced, attributed, allocated, and returned as a compute access right.
origin contribution
→ trace verification
→ attribution
→ allocation policy
→ compute access royalty
This repository currently defines the v0.4 foundation of Compute Access Royalty OS.
Implemented:
- compute access governance document
- contribution allocation document
- multi-wing compute commons document
- Royalty OS integration document
- JSON Schemas
- YAML examples
- validation script
- GitHub Actions workflow
Validation status:
passing
Status:
validated
Defines the first schema, example, governance document, and validation workflow for compute access rights.
Status:
validated
Defines contribution evaluation and policy-based allocation into compute access rights.
Status:
validated
Defines shared compute pools, multi-wing governance, allocation rules, abuse controls, and commons review.
Status:
validated
Defines the integration link between origin contribution, trace, attribution, allocation, return flow, and compute access rights.
Planned direction:
- sovereign compute governance
- space or off-grid compute infrastructure
- jurisdictional stewardship
- AI compute access rights across infrastructure domains
- human review and commons protection
- compute access return across sovereign or orbital infrastructure
Potential files:
docs/sovereign-compute-access-protocol.md
schemas/sovereign-compute-access.schema.json
examples/sovereign-compute-access.example.yaml
AI compute should not only be consumed.
It should be governed, traced, attributed, returned, and shared.
Compute Access Royalty OS is a first step toward an AI ecosystem where useful contributions can generate access to more intelligence, and where shared compute resources can circulate across multiple wings without becoming extractive or speculative.
Contribution should not disappear into the system.
It should return as capability.
Capability should not be captured by one wing.
It should circulate through a governed commons.
Origin should not be erased.
It should remain traceable in the return flow.
This project is intended to be released under an open license.
Recommended:
MIT License