https://github.com/samuraiwriter7/ktp-trace-intelligence-spec-v0.1
A minimal specification for recording origin candidates and trace intelligence claims within the Kazene Trace Protocol.
https://github.com/samuraiwriter7/ktp-trace-intelligence-spec-v0.1
ai-governance conceptual-lineage kazene kazene-trace-protocol origin-candidate origin-tracking provenance royalty-os structure-fingerprint trace-intelligence
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A minimal specification for recording origin candidates and trace intelligence claims within the Kazene Trace Protocol.
- Host: GitHub
- URL: https://github.com/samuraiwriter7/ktp-trace-intelligence-spec-v0.1
- Owner: SamuraiWriter7
- License: mit
- Created: 2026-05-18T04:35:30.000Z (25 days ago)
- Default Branch: main
- Last Pushed: 2026-05-18T06:01:18.000Z (25 days ago)
- Last Synced: 2026-05-18T06:49:13.093Z (25 days ago)
- Topics: ai-governance, conceptual-lineage, kazene, kazene-trace-protocol, origin-candidate, origin-tracking, provenance, royalty-os, structure-fingerprint, trace-intelligence
- Homepage:
- Size: 41 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Citation: CITATION.cff
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README
# KTP Trace Intelligence Specification v0.1
A minimal evidence-packet specification for tracing origin candidates, structural influence, and conceptual lineage within the Kazene Trace Protocol.
This repository defines a machine-readable record for documenting possible origins, structural influence, conceptual similarity, and trace-related evidence for ideas, questions, structures, and AI-generated derivatives.
It does **not** determine final authorship, ownership, legal liability, or automatic royalty allocation.
Its purpose is to preserve evidence, separate inference from judgment, and support later human or multi-wing review.
---
## Core Principle
> Origin candidates are not final origins.
A Trace Intelligence Record does not claim:
> “This is the true origin.”
Instead, it records:
> “This is a possible origin candidate supported by trace evidence.”
This distinction is essential.
KTP Trace Intelligence is designed as an observation and evidence layer, not as an enforcement mechanism.
---
## Purpose
The purpose of this specification is to provide a minimal record format for:
- documenting possible origin candidates;
- recording structural, semantic, and conceptual influence;
- preserving evidence without making final judgments;
- supporting later review, dispute handling, and allocation readiness;
- preventing premature automatic royalty distribution based only on similarity scores.
This specification is intended to function as the observation layer of the Kazene Trace Protocol.
---
## Non-Goals
This specification does not attempt to:
- determine legal authorship;
- prove copyright ownership;
- assign final origin status;
- automatically calculate royalty shares;
- enforce payments;
- replace human judgment;
- replace governance, dispute, or review processes.
Trace intelligence records evidence.
They do not replace judgment.
---
## Conceptual Position
```text
Kazene Trace Protocol
↓
Trace Intelligence Record
↓
Origin Candidate
↓
Review / Dispute
↓
Allocation Readiness
↓
Royalty OS
```
In this flow, the Trace Intelligence Record acts as the “eye” of the Kazene Trace Protocol.
It observes possible traces, records supporting evidence, and passes the result to later review layers.
It does not directly trigger allocation.
---
## Why This Specification Exists
In AI-mediated creation, ideas, questions, structures, and conceptual patterns can be absorbed, transformed, paraphrased, blended, and regenerated without explicit citation.
Traditional provenance tools can help record metadata, authorship claims, and chain-of-custody information.
However, they are often insufficient for tracking abstract structures such as:
- origin questions;
- conceptual frameworks;
- philosophical structures;
- multi-layer reasoning patterns;
- AI-generated derivatives;
- implicit structural influence.
KTP Trace Intelligence Specification v0.1 provides a minimal structure for recording such cases safely.
The goal is not perfect automatic tracing.
The goal is trustworthy trace documentation.
---
## Design Principles
### 1. Candidate, Not Verdict
A possible origin must be recorded as an origin candidate, not as a final origin.
### 2. Evidence Before Enforcement
No enforcement, allocation, or penalty should occur directly from a trace record.
### 3. Inference Is Not Judgment
Semantic similarity, structural similarity, and LLM-assisted analysis are forms of inference.
They require review.
### 4. Human or Multi-Wing Review Required
Important trace claims should be reviewed by humans, multi-agent systems, or governance processes.
### 5. No Direct Allocation
A Trace Intelligence Record must not directly trigger royalty allocation.
Allocation requires a separate readiness layer.
### 6. Dispute Is Expected
Trace records may be challenged, revised, rejected, or reaffirmed.
Dispute handling is part of the lifecycle.
### 7. Transparency Over Certainty
Trace intelligence should prefer visible reasoning and uncertainty over false certainty.
A transparent low-confidence record is safer than an opaque high-confidence claim.
---
## Record Overview
A Trace Intelligence Record may include:
- `trace_id`
- `record_version`
- `created_at`
- `observer`
- `target`
- `origin_candidates`
- `evidence`
- `analysis`
- `review_status`
- `dispute_status`
- `allocation_readiness`
- `governance`
The record separates:
```text
Target
↓
Possible Origin Candidates
↓
Evidence
↓
Review Status
↓
Allocation Readiness
```
This separation prevents similarity scores from being mistaken for final truth.
---
## Example Use Cases
### 1. Structural Similarity Detection
An AI-generated article appears to share a layered structure with an earlier Kazene framework.
A Trace Intelligence Record can document the similarity without claiming direct copying.
### 2. Implicit Absorption
A model output resembles an existing conceptual structure, even though no explicit citation is present.
The record can mark the relation as `implicit_absorption`.
### 3. Conceptual Influence
A new essay appears to develop ideas that are strongly influenced by an earlier origin question.
The record can preserve this as a possible trace relation.
### 4. Review Preparation
A trace claim can be passed to a review process before any dispute, allocation, or royalty decision occurs.
---
## Relationship to Kazene Trace Protocol
Kazene Trace Protocol is the broader framework for preserving and interpreting traces of origin, influence, and structural inheritance.
This specification defines one minimal component within that framework:
```text
Trace Intelligence Record
```
Its role is to document evidence for possible origin relationships.
It should be used together with, or in relation to:
- Structure Fingerprint specifications;
- Origin Token systems;
- C2PA-inspired provenance records;
- Chain-of-custody logs;
- Dispute Registry systems;
- Allocation Readiness specifications;
- Royalty OS mechanisms.
---
## Relationship to Structure Fingerprint
Structure Fingerprint focuses on identifying structural patterns in ideas, texts, systems, or conceptual frameworks.
Trace Intelligence Record may use Structure Fingerprint outputs as evidence.
However, a structural match alone is not enough to prove origin.
A Trace Intelligence Record should preserve the result as evidence, not convert it into automatic judgment.
---
## Relationship to Allocation Readiness
Allocation Readiness is a later-stage gate.
It determines whether a trace claim is mature enough to be considered for value distribution, royalty calculation, or institutional handling.
Trace Intelligence Record comes before Allocation Readiness.
```text
Trace Intelligence Record
↓
Review / Dispute
↓
Allocation Readiness
```
This prevents premature allocation based on incomplete evidence.
---
## Repository Structure
```text
ktp-trace-intelligence-spec-v0.1/
├── README.md
├── LICENSE
├── CITATION.cff
├── CHANGELOG.md
├── spec/
│ └── trace-intelligence-record-v0.1.yaml
├── schemas/
│ └── trace-intelligence-record.schema.json
├── examples/
│ ├── trace-intelligence-record.sample.json
│ └── trace-intelligence-record.minimal.json
├── docs/
│ ├── design-principles.md
│ └── relationship-to-kazene-trace-protocol.md
└── .github/
└── workflows/
└── validate-specs.yml
```
---
## Repository Components
### `README.md`
Provides the overview, purpose, non-goals, core principles, conceptual position, and recommended reading order for the specification.
### `spec/`
Contains the human-readable YAML specification for the Trace Intelligence Record.
- `trace-intelligence-record-v0.1.yaml`
### `schemas/`
Contains the machine-readable JSON Schema used to validate Trace Intelligence Record examples.
- `trace-intelligence-record.schema.json`
### `examples/`
Contains sample Trace Intelligence Records.
- `trace-intelligence-record.sample.json`
A fuller example showing multiple origin candidates, evidence items, analysis notes, review status, dispute status, and governance context.
- `trace-intelligence-record.minimal.json`
A minimal valid example intended for quick implementation and schema validation.
### `docs/`
Contains explanatory documents that define the design philosophy and relationship to the broader Kazene Trace Protocol.
- `design-principles.md`
Explains the core safety and governance principles behind the specification.
- `relationship-to-kazene-trace-protocol.md`
Explains how the Trace Intelligence Record fits into the broader Kazene Trace Protocol ecosystem.
### `.github/workflows/`
Contains GitHub Actions workflow files.
- `validate-specs.yml`
Validates required files, the YAML specification, JSON Schema, and example records.
### `CHANGELOG.md`
Records version history and planned changes.
### `CITATION.cff`
Provides citation metadata for referencing this specification.
### `LICENSE`
Defines the license for the repository.
---
## Start Here
Recommended reading order:
1. `README.md`
2. `docs/design-principles.md`
3. `spec/trace-intelligence-record-v0.1.yaml`
4. `schemas/trace-intelligence-record.schema.json`
5. `examples/trace-intelligence-record.minimal.json`
6. `examples/trace-intelligence-record.sample.json`
7. `docs/relationship-to-kazene-trace-protocol.md`
8. `CHANGELOG.md`
For implementation, start with:
```text
schemas/trace-intelligence-record.schema.json
examples/trace-intelligence-record.minimal.json
```
For conceptual understanding, start with:
```text
docs/design-principles.md
docs/relationship-to-kazene-trace-protocol.md
```
---
## Schema Usage
Trace Intelligence Records are validated using:
```text
schemas/trace-intelligence-record.schema.json
```
Example records are provided in:
```text
examples/trace-intelligence-record.minimal.json
examples/trace-intelligence-record.sample.json
```
A valid record must include:
- `trace_id`
- `record_version`
- `created_at`
- `observer`
- `target`
- `origin_candidates`
- `evidence`
- `review_status`
- `allocation_readiness`
The schema enforces the structural validity of the record.
However, schema validation does not mean that a trace claim is true.
Validation only means that the record is correctly formed.
---
## Validation
This repository includes a GitHub Actions workflow for validation:
```text
.github/workflows/validate-specs.yml
```
The workflow checks:
- required repository files;
- YAML specification structure;
- JSON Schema validity;
- example record validation;
- basic semantic safety conditions.
Validation is automatically triggered on:
- push to `main`;
- pull requests to `main`;
- manual workflow dispatch.
A passing workflow indicates that the core specification files and example records are structurally valid.
It does not indicate final origin judgment, ownership, or allocation readiness.
---
## Safety Boundary
A Trace Intelligence Record is an evidence packet.
It may support later review, but it must not be treated as:
- a legal judgment;
- a final authorship claim;
- a final ownership claim;
- an automatic royalty trigger;
- a moderation decision;
- an enforcement action.
The specification is designed to preserve traces without weaponizing them.
---
## Status
Draft v0.1.0.
This specification is experimental and intended for discussion, prototyping, and early implementation.
It should not be used as a legal determination system or automatic royalty enforcement mechanism.
---
## Citation
Citation metadata is provided in:
```text
CITATION.cff
```
If you use this specification, please cite it using the information provided there.
---
## License
This project is licensed under the MIT License.
See `LICENSE` for details.
---
## Changelog
See `CHANGELOG.md`.
---
## Key Statement
Trace intelligence is not the same as origin judgment.
A trace record is an evidence packet.
It observes, preserves, and prepares.
It does not decide, punish, or allocate.