Communication Trace Record (CTR) v0.1 is a draft specification for recording communication-derived trace events across humans, AIs, and agents.
It defines a minimal, machine-readable event format for capturing how meaning is referenced, transformed, summarized, reused, and circulated.
This repository focuses on the recording layer of Communication Royalty OS. It does not directly calculate monetary royalties. Instead, it provides the trace basis that later systems may use for gratitude, credit, trust, audit, or royalty candidate review.
In AI-native environments, value is increasingly generated not only by static works, but by communication processes:
- referencing
- summarizing
- responding
- transforming
- reusing
- influencing downstream outputs
CTR v0.1 exists to make those communication-derived traces visible, structured, and interoperable.
The goal is not to charge for communication itself.
The goal is to record how communication contributes to later meaning generation, so that downstream systems can decide whether and how value should circulate.
This repository defines a trace record format for communication events.
CTR v0.1 covers:
- event-level communication trace records
- actor / counterparty / action modeling
- input and output context
- trace assessment
- governance metadata
- optional settlement hooks for downstream circulation layers
CTR v0.1 does not cover:
- direct message pricing
- automatic legal ownership determination
- mandatory monetary settlement
- full cryptographic signature infrastructure
- full provenance graph serialization in a single record
A Communication Trace Record answers a simple but important question:
What happened, who acted, what sources were involved, what output was produced, and how strongly did this event contribute to later meaning generation?
That makes CTR a foundational layer for:
- Communication Royalty OS
- gratitude systems
- trust systems
- attribution systems
- audit and accountability pipelines
- communication influence mapping
- Communication itself is not a billing target.
- Meaning generation is the primary value source.
- Trace does not automatically imply ownership.
- Trace does not automatically imply monetary royalty.
- The same trace may later map to gratitude, credit, trust, royalty, or none.
- Records should be machine-readable, human-auditable, and privacy-aware.
- Minimal viable interoperability is preferred over premature completeness.
.
├── spec/
│ └── communication-trace-record-v0.1.yaml
├── schemas/
│ └── communication-trace-record-v0.1.schema.json
├── examples/
│ └── communication-trace-record.sample.json
└── .github/
└── workflows/
└── validate-specs.yml
Start here
Read the files in this order:
spec/communication-trace-record-v0.1.yaml
Human-readable specification source.
schemas/communication-trace-record-v0.1.schema.json
Machine-validatable JSON Schema definition.
examples/communication-trace-record.sample.json
Example record that should validate successfully against the schema.
.github/workflows/validate-specs.yml
CI validation workflow for schema/sample consistency.
Specification overview
CTR v0.1 models a communication event as a structured record with these main sections:
record metadata
record_type, spec_version, record_id, trace_id, timestamps
actors
actor, optional counterparty
communication act
action
input context
input_context.sources, context hashes, source counts
output context
output type, output hashes, artifact references
trace assessment
trace strength, derivation level, return channel candidates
governance
consent, privacy, retention, access scope
settlement hooks
optional references for downstream gratitude / trust / royalty systems
evidence
log references, tool run IDs, hashes, notes
Relationship to CTID and adjacent layers
CTR v0.1 is closely aligned with CTID-style trace recording, but it is specialized for communication-derived meaning generation.
A useful way to see the stack is:
Layer 1: Recording
CTR / CTID-style trace records
Layer 2: Circulation
gratitude, credit, trust, royalty candidate allocation
Layer 3: Governance and visibility
dashboards, audit, policy, legal interpretation
In that sense, CTR v0.1 is a recording-layer spec that can later feed adjacent systems such as:
Gratitude Event Protocol
Trust Event Specification
Royalty Allocation Specification
communication influence graphs
audit and compliance pipelines
Example use cases
CTR v0.1 can be used to record events such as:
an AI summarizing a user’s conceptual note
an agent reusing prior discussion traces in a workflow
a system transforming retrieved documents into a structured answer
a tool chain producing a derived artifact from multiple communication inputs
a review pipeline marking a trace as a gratitude, credit, trust, or royalty candidate
Schema Usage
Requirements
Python 3.10+
jsonschema
Install the validator locally:
python -m pip install --upgrade pip
pip install jsonschema
Validate the CTR schema and sample locally
Run the following command from the repository root:
python - <<'PY'
import json
from jsonschema import Draft202012Validator
schema_path = "schemas/communication-trace-record-v0.1.schema.json"
sample_path = "examples/communication-trace-record.sample.json"
print("=== Validating Communication Trace Record v0.1 ===")
print(f"Schema: {schema_path}")
print(f"Sample: {sample_path}")
with open(schema_path, "r", encoding="utf-8") as f:
schema = json.load(f)
with open(sample_path, "r", encoding="utf-8") as f:
sample = json.load(f)
Draft202012Validator.check_schema(schema)
Draft202012Validator(schema).validate(sample)
print("OK: Communication Trace Record v0.1 sample is valid.")
PY
CI validation
This repository also validates the schema/sample pair in GitHub Actions through:
.github/workflows/validate-specs.yml
The workflow is expected to run on push and pull request events so that schema drift and sample mismatches are caught early.
Validation expectations
A valid CTR record should satisfy at least the following:
record_type must be communication_trace_record
spec_version must be v0.1
record_id must match the CTR identifier pattern
trace_id must match the CTID identifier pattern
trace_strength must be between 0 and 1
return_channels must be valid
none must not be combined with other return channels
model_name is required when actor.actor_type is ai or agent
privacy_level must be high or confidential when personal_data_included is true
Some higher-order checks, such as whether source_count exactly matches the real number of sources, may be better enforced in additional test code rather than pure JSON Schema.
Privacy note
CTR is designed to be privacy-aware.
Implementations are encouraged to prefer:
hashes over raw content
references over full payload retention
scoped identifiers over unnecessary identity exposure
redaction-friendly storage patterns
CTR should not be interpreted as a license to retain all communication content indefinitely.
Current status
Status: Draft
Version: v0.1
This version is intended as a minimal, interoperable first release for:
drafting
testing
schema validation
adjacent protocol integration
It should be treated as a stable draft for experimentation, not as a final legal or institutional standard.
Roadmap
Planned next steps may include:
stricter schema refinements
pass/fail compliance test vectors
explicit mapping to gratitude / trust / royalty layers
optional signature and verification fields
richer provenance linkage rules
dashboard-facing aggregation guidance
relationship documents to adjacent OS layers
Contributing
Contributions that improve clarity, interoperability, and validation rigor are welcome.
Especially useful contributions include:
schema corrections
better examples
compliance test vectors
validator improvements
documentation refinements
downstream mapping proposals
When proposing changes, try to preserve the core design principle:
communication is not the billing target; communication-derived meaning generation is the traceable value source
License
This repository is currently described as using the following license label in the spec metadata:
Kazene Royalty Core License
Make sure the repository-level LICENSE file matches the intended legal distribution model.
One-line summary
CTR v0.1 is a minimal recording-layer specification for tracing how communication generates value across humans, AIs, and agents.