Chain Of Custody Provenance

Token- or block-level provenance: which inputs, tools, prompt sections, and turns produced each output segment. Use when debugging AI failures or audit requirements. Scope boundary: claim-level sources → `journalistic-attribution`; orient logging → `ooda-adaptive-context`.

CatCorner22 Updated

File contents

Chain of custody provenance

#4 · Domain: Law enforcement / forensics · Category: quality-control · Difficulty: 🔴 High

Core principle

Unbroken chain of who handled what, when, and why — tampering voids admissibility.

AI problem addressed

Outputs lack traceability to influencing context and tools.

Implementation

Tag each output block with:

  • Source inputs consulted
  • Tool calls (with version)
  • Prompt section applied
  • Prior turns referenced
  • Timestamp and model version Trace backward from disputed segment to breaking link.

Boundaries

  • Prototype as prompt scaffold (🟢) before full pipeline middleware (🟡/🔴)
  • Category router: ai-transfer-quality-control
  • Catalog: ai-transfer-ecosystem-primer
  • Runtime plugin id: chain_of_custody
  • Also implements: black_box
  • Merge notes: Also absorbs black_box: immutable session recorder on the same chain.

CatCorner22/Cursor_Skills/tree/main/skills/ai-transfer/chain-of-custody-provenance commit a5764665f5

Frequently asked questions

npx skillmds@latest add catcorner22/chain-of-custody-provenance