A Nakayoshi Network for peaceful, AI-assisted space coordination.
Space Commons Coordination Protocol (SCCP) is a lightweight coordination protocol for preserving outer space as a shared operational environment.
It is designed to support peaceful, transparent, AI-assisted coordination for space safety events such as collision risk, debris warnings, AI false-positive reviews, communication anomalies, space weather alerts, emergency coordination, and debris-related responsibility records.
SCCP does not define a military command structure.
It defines a coordination, verification, traceability, audit, responsibility, remediation, and de-escalation layer for preventing misunderstanding, misclassification, premature escalation, and unnecessary hostility in space operations.
Space should not become a place where AI accelerates misunderstanding into conflict.
SCCP begins from a simple premise:
AI should not be used to automate hostility in space. AI should be used to help humans see, verify, pause, coordinate, audit, and repair.
The protocol defines machine-readable structures for:
- recording space safety events
- aggregating observations
- verifying multiple sources
- preventing AI false positives
- auditing AI misclassification
- requiring human review before escalation
- preserving audit logs
- documenting debris-related responsibility
- recording mitigation and remediation contributions
- maintaining a de-escalation-first posture
The public name is:
Space Commons Coordination Protocol
The internal nickname is:
Nakayoshi Network
The formal name gives the protocol diplomatic and technical clarity. The nickname preserves its design spirit:
- coordination before command
- trace before retaliation
- audit before attribution
- mitigation before blame
- human review before escalation
- commons before sovereignty
Before bringing swords into orbit, establish orbital etiquette.
Outer space is becoming more crowded, automated, commercialized, and strategically sensitive.
As satellites, autonomous systems, commercial operators, military systems, and AI-assisted monitoring tools increase, the risk of misunderstanding also increases.
A communication anomaly may be misread as interference. A debris event may be misread as hostile action. An AI anomaly score may be over-classified. A single-source observation may be interpreted too quickly. A debris origin estimate may be treated as attribution before review. A public warning may accidentally escalate a sensitive situation.
SCCP exists to prevent this conversion:
uncertainty
→ suspicion
→ attribution
→ escalation
Instead, SCCP proposes another path:
observation
→ trace
→ verification
→ audit
→ human review
→ coordination
→ mitigation
→ remediation
The goal is not to deny security risks.
The goal is to prevent uncertainty from becoming hostility before evidence, review, and mitigation are complete.
SCCP treats safety, continuity, and shared-space preservation as the first priority.
It does not treat uncertainty as hostility.
SCCP is not a command system.
It is a coordination layer for observation sharing, source verification, review, audit, and de-escalation.
Every escalation-sensitive event should include trace information before attribution, retaliation, or public interpretation is considered.
AI-generated classifications, object correlations, risk labels, and origin assessments must be auditable.
AI must not finalize hostile attribution.
AI may assist with classification, anomaly detection, uncertainty estimation, notification prioritization, audit preparation, and public summary drafting.
AI must not make final hostile attribution, liability, retaliation, or escalation decisions.
Debris-related events should first trigger risk reduction, operator notification, monitoring, and remediation planning.
SCCP does not automatically assign legal liability.
SCCP begins from the assumption that outer space is a shared operational environment.
Protection of the shared orbital environment comes before unilateral reaction.
SCCP is currently organized into five protocol layers.
[ Space Event ]
↓
[ v0.1 Space Friendship Event ]
↓
[ v0.2 Neutral Coordination Node ]
↓
[ v0.3 De-escalation Workflow ]
↓
[ v0.4 AI Misclassification Audit ]
↓
[ v0.5 Space Debris Responsibility Record ]
↓
[ Human Review / Operator Notification / Mitigation / Remediation / Continued Monitoring ]
Records the event.
This layer defines the minimum event format for peaceful AI-assisted space safety coordination.
It supports:
- collision risk
- debris warning
- AI false-positive review
- communication anomaly
- space weather alert
- emergency coordination
Receives and reviews the event.
This layer defines a non-command coordination node for:
- observation aggregation
- cross-source verification
- de-escalation review
- AI false-positive checking
- operator notification
- public summary preparation
- audit log preservation
Prevents premature escalation.
This layer defines a step-by-step workflow for moving from uncertainty to verification, review, notification, and resolution.
It is not an automated retaliation chain.
Audits AI-generated classifications.
This layer reviews false positives, over-classification, under-classification, misleading confidence, context loss, data quality errors, evidence mismatch, model bias, and escalation-sensitive public summaries.
It asks:
Did AI classify the event correctly, or did it create unnecessary escalation risk?
Documents debris-related responsibility and remediation.
This layer records debris-related events, uncertainty, mitigation actions, remediation contributions, public disclosure boundaries, human review, and recurrence prevention.
It is not an automatic liability engine.
The Space Friendship Event layer defines the minimum event structure for peaceful AI-assisted space coordination.
A Space Friendship Event records:
- event identity
- event type
- severity
- affected objects
- observation sources
- AI assistance status
- trace information
- coordination status
- human review status
- safety boundaries
Example event types:
collision_risk
debris_warning
ai_false_positive_review
communication_anomaly
space_weather_alert
emergency_coordination
Included files:
docs/space-friendship-event.md
schemas/space-friendship-event.schema.json
examples/collision-risk-event.example.yaml
examples/debris-warning-event.example.yaml
examples/ai-false-positive-review.example.yaml
The Neutral Coordination Node layer defines the first operational coordination structure for processing Space Friendship Events.
A Neutral Coordination Node is not a command node.
It receives events, aggregates observations, verifies multiple sources, prevents AI false positives, preserves audit logs, and routes sensitive cases to human review.
A Neutral Coordination Node may:
- receive Space Friendship Events
- aggregate observations
- compare multiple sources
- detect inconsistent evidence
- flag AI false positives
- notify relevant operators
- prepare non-sensitive summaries
- route sensitive cases to human review
A Neutral Coordination Node must not:
- select targets
- authorize retaliation
- recommend weapon use
- finalize hostile attribution by AI
- create automatic escalation chains
- override human review
Included files:
docs/neutral-coordination-node.md
schemas/neutral-coordination-node.schema.json
examples/neutral-coordination-node.example.yaml
The De-escalation Workflow layer connects Space Friendship Events and Neutral Coordination Nodes into a step-by-step safety process.
It defines:
- event recording
- observation collection
- cross-source verification
- AI false-positive checking
- neutral node review
- human review
- operator notification
- public summary review
- resolution or continued monitoring
The default posture is de-escalation.
When evidence is uncertain, disputed, or incomplete, the workflow requires additional verification and human review before escalation-sensitive interpretation.
A standard workflow may follow this sequence:
record_event
↓
collect_observations
↓
cross_source_verification
↓
ai_false_positive_check
↓
neutral_node_review
↓
human_review
↓
operator_notification
↓
public_summary_review
↓
resolve_or_monitor
Included files:
docs/de-escalation-workflow.md
schemas/de-escalation-workflow.schema.json
examples/de-escalation-workflow.example.yaml
The AI Misclassification Audit layer defines a review structure for AI-generated classifications in space safety coordination.
It is designed to prevent:
- false positives
- over-classification
- under-classification
- misleading confidence
- context loss
- data quality errors
- evidence mismatch
- model bias
- public summary errors
- escalation-sensitive language
This layer asks a simple question:
Did AI classify the event correctly, or did it create unnecessary escalation risk?
The audit may produce correction actions such as:
- withdraw false positive
- reclassify event
- update confidence
- request additional sources
- notify operator
- update public summary
- block escalation
- record recurrence rule
AI Misclassification Audit is not a blame engine.
It is a safety audit layer for preventing AI-generated uncertainty from becoming hostility.
Included files:
docs/ai-misclassification-audit.md
schemas/ai-misclassification-audit.schema.json
examples/ai-misclassification-audit.example.yaml
The Space Debris Responsibility Record layer defines a traceable structure for documenting debris-related events, uncertainty, mitigation actions, remediation contributions, and public accountability.
It is not an automatic liability engine.
It is designed to preserve reviewable debris-related responsibility without converting uncertainty into hostility.
This layer records:
- debris event identity
- linked Space Friendship Event
- linked De-escalation Workflow
- linked AI Misclassification Audit
- affected objects or orbital regions
- debris origin assessment
- uncertainty level
- responsibility status
- mitigation actions
- remediation contributions
- public disclosure status
- human review
- recurrence prevention
The key boundary is:
Before blame, trace. Before attribution, review. Before punishment, mitigation. Before escalation, remediation.
Included files:
docs/space-debris-responsibility-record.md
schemas/space-debris-responsibility-record.schema.json
examples/space-debris-responsibility-record.example.yaml
SCCP is positioned as a thin coordination OS for preserving outer space as a shared commons.
It is not a military command structure.
It is a coordination, verification, traceability, audit, de-escalation, responsibility, and remediation layer for peaceful AI-assisted space safety.
SCCP is also a precondition layer for any responsible space defense architecture that may emerge in the future.
The protocol begins from the commons.
It reframes defense as the preservation of shared conditions:
- shared awareness
- traceable evidence
- AI restraint
- AI auditability
- human review
- non-escalation
- mitigation
- remediation
- mutual survivability
See:
docs/civilizational-positioning.md
| Action | SCCP Position |
|---|---|
| Target selection | Prohibited |
| Automatic retaliation | Prohibited |
| Weapon-use recommendation | Prohibited |
| Final hostile attribution by AI | Prohibited |
| Final debris attribution by AI | Prohibited |
| Automatic liability assignment | Prohibited |
| Escalation without human review | Prohibited |
| Public leakage of sensitive operational data | Prohibited |
| Human-reviewed safety coordination | Allowed |
| Risk classification | Allowed |
| Trajectory uncertainty estimation | Allowed |
| False-positive review | Allowed |
| AI misclassification audit preparation | Allowed |
| Public non-sensitive summary drafting | Allowed |
| Debris mitigation record | Allowed |
| Remediation contribution record | Allowed |
The key principle is simple:
AI may assist coordination. AI must not automate hostility.
AI may be used for:
- risk classification
- trajectory uncertainty estimation
- anomaly detection
- data consistency checking
- notification priority ranking
- false-positive review
- public summary drafting
- object correlation support
- debris risk estimation
- audit preparation
- recurrence rule drafting
AI must not be used for:
- target selection
- automatic retaliation
- weapon-use recommendation
- final hostile attribution
- final responsibility attribution
- automatic liability assignment
- escalation without human review
The Space Debris Responsibility Record does not automatically assign legal liability.
It may record:
- origin status
- evidence status
- uncertainty level
- responsibility review status
- mitigation actions
- remediation contributions
- public disclosure level
- human review notes
It must not:
- make final attribution by AI
- trigger retaliation
- leak sensitive operational data
- replace legal processes
- convert uncertainty into blame
The default posture is:
trace
→ review
→ mitigation
→ remediation
→ recurrence prevention
.
├── README.md
├── CHANGELOG.md
├── docs/
│ ├── civilizational-positioning.md
│ ├── space-friendship-event.md
│ ├── neutral-coordination-node.md
│ ├── de-escalation-workflow.md
│ ├── ai-misclassification-audit.md
│ └── space-debris-responsibility-record.md
├── schemas/
│ ├── space-friendship-event.schema.json
│ ├── neutral-coordination-node.schema.json
│ ├── de-escalation-workflow.schema.json
│ ├── ai-misclassification-audit.schema.json
│ └── space-debris-responsibility-record.schema.json
├── examples/
│ ├── collision-risk-event.example.yaml
│ ├── debris-warning-event.example.yaml
│ ├── ai-false-positive-review.example.yaml
│ ├── neutral-coordination-node.example.yaml
│ ├── de-escalation-workflow.example.yaml
│ ├── ai-misclassification-audit.example.yaml
│ └── space-debris-responsibility-record.example.yaml
└── scripts/
└── validate_examples.py
Install dependencies:
pip install jsonschema pyyamlRun validation:
python scripts/validate_examples.pyExpected validation targets:
Space Friendship Event
Neutral Coordination Node
De-escalation Workflow
AI Misclassification Audit
Space Debris Responsibility Record
Expected result:
[ok] collision-risk-event.example.yaml is valid
[ok] debris-warning-event.example.yaml is valid
[ok] ai-false-positive-review.example.yaml is valid
[ok] neutral-coordination-node.example.yaml is valid
[ok] de-escalation-workflow.example.yaml is valid
[ok] ai-misclassification-audit.example.yaml is valid
[ok] space-debris-responsibility-record.example.yaml is valid
Recommended workflow:
.github/workflows/validate-examples.yml
The workflow should:
- check out the repository
- set up Python
- install
jsonschemaandpyyaml - run
python scripts/validate_examples.py
Current candidate:
v0.5.0-candidate — Space Debris Responsibility Record
Implemented layers:
v0.1 — Space Friendship Event
v0.2 — Neutral Coordination Node
v0.3 — De-escalation Workflow
v0.4 — AI Misclassification Audit
v0.5 — Space Debris Responsibility Record
A future layer for aligning SCCP records with space situational awareness systems and external observation networks.
Possible scope:
- observation source mapping
- conjunction warning interoperability
- object reference normalization
- public/private data tiers
- operator notification interfaces
- neutral coordination data exchange
A future layer for certifying participants that comply with SCCP safety boundaries.
Possible scope:
- no automatic retaliation
- no final hostile attribution by AI
- human review required
- public non-sensitive summary policy
- audit log retention
- debris mitigation participation
- AI misclassification audit readiness
A future layer for defining responsibility boundaries for AI-assisted space coordination.
Possible scope:
- AI role declaration
- model confidence audit
- human override record
- misclassification recurrence tracking
- accountability handoff
- public explanation boundary
Possible future extensions include:
- Optional Defense Coordination Module with strict human oversight
- Space Debris Remediation Contribution Ledger
- Trace and Royalty OS integration
- Contribution-based governance systems
- Space Commons public registry
- Multi-stakeholder neutral node federation
Any future defense-related extension should remain:
- opt-in
- reviewable
- auditable
- human-supervised
- non-retaliatory by default
- subordinate to SCCP safety boundaries
SCCP is not:
- a military alliance
- a command-and-control system
- a weapons coordination protocol
- an automated retaliation framework
- an automatic liability engine
- a replacement for international law
- a final governance regime for outer space
SCCP is:
- a coordination protocol
- a traceability layer
- a de-escalation mechanism
- an AI use boundary model
- an AI audit layer
- a debris responsibility record
- a remediation contribution log
- a human-review-first safety structure
- a lightweight commons-preserving OS
Space should not become a place where AI accelerates misunderstanding into conflict.
Space should become a place where AI helps humanity see, verify, pause, coordinate, audit, mitigate, and repair.
Before command, coordination.
Before retaliation, trace.
Before attribution, audit.
Before escalation, human review.
Before blame, mitigation.
Before punishment, remediation.
Before sovereignty, commons.
Before bringing swords into orbit, establish orbital etiquette.