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Prompt Provenance

Validate examples License: MIT

A draft specification for versioned, lineaged, reviewable prompt records that travel with the prompt itself — not in a wiki, not in a spreadsheet.

Every team running LLMs in production hits the same problem: prompts are the most-edited, least-version-controlled artifact in the stack. The same prompt exists in three notebooks, two repos, and someone's Slack DM, with no record of who changed what, what they were trying to fix, and whether the new version actually passed the evals.

Prompt Provenance is a JSON document that fixes this. One record per prompt version, machine-readable, designed to live alongside the prompt content in any repo, registry, or artifact store.

The three pillars

Pillar What it does
Record Every prompt version gets a provenance document with a content hash, author chain, and approval state
Reference Every version cites its parent — a directed chain of derivations (forks, tunes, patches)
Review Every record carries the eval results that gated approval, including which suites ran and what they returned

Why not just put it in Git?

Git tracks file changes. It does not track:

  • Eval suites that ran against a prompt version — these are external artifacts living in CI logs, eval tooling, or a vendor dashboard
  • Approval chain — who reviewed, who approved, with what scope
  • Derivation type — was this a fork (new purpose), a tune (same purpose, better wording), or a patch (bugfix)
  • Cross-repo lineage — a prompt forked from a vendor's library into your internal repo can't be expressed in a single Git history
  • Deprecation — Git tells you what changed, not what is no longer fit for production

Prompt Provenance lives in Git, but adds the semantic layer Git can't represent on its own.

Why not LangChain Hub / PromptHub / vendor X?

Vendor prompt registries solve part of this for their customers. Prompt Provenance is an open, vendor-neutral format that any registry can emit, any CI system can validate, and any reader can audit without an account.

Quickstart

  1. Pick a stable prompt.id (kebab-case, unique within your org).
  2. Compute a content hash over the canonicalized prompt text (SHA-256 over the UTF-8 bytes with normalized line endings).
  3. Write a provenance document conforming to provenance.schema.json. Start from examples.
  4. Commit the provenance document alongside the prompt content. One file per version. Path convention: prompts/<id>/v<version>/provenance.json.
  5. (Optional) Publish a directory at /.well-known/prompts/<id>/latest.json pointing to the current production version.

Files in this repo

Status

v0.1 draft. Issues and pull requests welcome.

License

MIT-licensed. The specification text, JSON Schema, and example documents in this repository may be freely implemented, extended, redistributed, or incorporated into commercial or non-commercial products with attribution. Reference implementations of this spec (such as mcp-kinetic-gain) are licensed separately under AGPL-3.0.

Kinetic Gain Protocol Suite

A family of open specifications for the answer-engine era. Each spec is a self-contained JSON document format with its own JSON Schema and reference examples; together they compose into an end-to-end account of entity, agent, prompt, tool, and citation.

Spec What it does
AEO Protocol Entity declaration at /.well-known/aeo.json — authoritative claims, citation preferences, audit hooks
Prompt Provenance Versioned, lineaged, reviewable LLM prompt records
Agent Cards Declarative agent capability and refusal disclosure
AI Evidence Format Structured citations that travel with LLM-generated claims
MCP Tool Cards Per-tool disclosure layered on Model Context Protocol servers

Connect: LinkedIn · Kinetic Gain · Medium · Skills

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Prompt Provenance v0.1 draft. JSON document format for versioned, lineaged, reviewable LLM prompt records: content hash, parent chain, derivation type, eval results, approval state. Part of the Kinetic Gain Protocol Suite.

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