A label is a short declaration: who made this, when, and how much of it came from a human versus an AI. That's it.
Disclosure, not judgment.
A Provenance Label makes no claim about quality. It simply answers: what happened here, and who is accountable? Like a nutrition label — informative, not prescriptive.Two formats. Same information. Use whichever fits your context.
A label has four required fields and several optional ones. Required fields make it a valid label. Optional fields add context.
| Field | What it means |
|---|---|
| author | The human accountable for the content. Not the AI. Not the tool. You. |
| date | Date of completion or publication. Format: YYYY-MM-DD. |
| human | Your percentage of contribution. Must be an integer 0–100. |
| ai | AI's percentage. Must sum to 100 with human. |
| Field | What it means |
|---|---|
| tools | Which AI tools you used. Comma-separated if multiple. |
| note | One plain sentence describing how you worked together. |
| shared-by | If you're republishing someone else's work, your name goes here. |
| updated | Date of most recent substantive revision. |
| ref | Sources referenced during creation. Repeatable. |
Aim for honest, not perfect. No one is auditing your math. The point is a good-faith estimate of how the work actually came together.
Things to consider: Who initiated the content? Who made the decisions? Who edited, cut, and shaped the final output? What percentage of the final text, code, or image came directly from each contributor?
If you used an AI throughout a session, ask it to calculate at the end — it has context. You review, adjust, and approve. The final number is yours.
Wherever makes sense for your medium. Some common placements:
| Medium | Where | Format |
|---|---|---|
| Blog post | Footer or end of post | Long or short |
| Social post | Inline or as a note | Short |
| GitHub repo | README or .plgen file | Long or raw file |
| Academic paper | Acknowledgments or appendix | Long |
| Artwork | Artist statement or caption | Long |
Submitted labels receive a permanent short ID — for example, PL-000312 — that can be embedded in your content. Anyone can look it up to verify the original, timestamped disclosure.
Self-generated labels are free and unregistered. Registered labels get a permanent ID and public record. The difference is verifiability, not validity.
Full API reference, integration guides, and the open registry endpoint.
Registered labels display a computed confidence score — PLGen-C — alongside the label itself. It isn't a judgment on whether your work is good, or even whether the label is true. It's a measure of how much of the disclosure can currently be independently verified versus taken on your word.
The score is computed from a fixed set of observable signals — not estimated or judged by an AI. Each signal is checked independently and shown with a symbol:
| Symbol | Meaning |
|---|---|
| ✓ | Signal fully satisfied. |
| △ | Partially satisfied, or not yet independently confirmable. |
| ✗ | Not satisfied, or the information needed isn't present. |
A △ doesn't necessarily mean something's wrong. Some signals depend on session data that not every AI platform exposes yet — it means that piece can't be independently confirmed right now, not that the disclosure itself is false.
| Signal | What it checks |
|---|---|
| Session initialization | Whether the disclosure session was set up before the work began, versus reconstructed afterward. |
| Checksum integrity | Whether the label carries a token confirming it wasn't edited after the AI generated it. |
| Token/time plausibility | Whether the pace of AI output over the session is consistent with a human directing the work. |
| Membership depth | How many labels this member has registered previously. |
| Work URL resolution | Whether the linked work actually exists and is reachable. |
| Paste event ratio | How much of the human-provided input was pasted in versus typed directly. |
| Session gap detection | Whether there were unusually long pauses during the session. |
| Corroboration | Independent confirmation from an institution or other verified source, beyond self-report. |
The exact scoring weights and thresholds are intentionally not published. Publishing them would let the score be gamed rather than earned — what's shown here is what's measured, not how heavily each part counts toward the final number.
| Version | Date | Changes |
|---|---|---|
| v1.2 | 2026-06-01 | Non-persuadable split estimation — AI may not adjust contribution percentages based on user preference, only new factual information. ChatGPT Custom GPT deployed. |
| v1.1 | 2026-03-06 | Added work_title, human_role, ai_role fields to long format and JSON schema. Introduced plgen command set: init, generate, register, status, validate, formats, help, cancel. |
| v1.0 | 2026-02-17 | Initial release. Core label format, required and optional fields, short and long output formats. |