Signal discovery

Work from the remove-ai-watermarks repository root. This skill discovers and closes library coverage gaps. Implementation, tests, fixtures, and documentation changes belong in this library; do not patch a downstream consumer to compensate for a detector or cleaner gap.

Treat retained inputs as sensitive and read-only. Keep reports, contact sheets, sidecars, and derived samples under the library's gitignored .local-eval/. Never commit a retained input or an artifact derived from one.

Before acting, read:

• .claude/rules/development.md;
• docs/verification-plan.md;
• docs/supported-signals.md and docs/watermarking-landscape.md;
• references/coverage-and-cadence.md.

Choose the run

Do not call corpus_gap_scan.py a complete signal audit. Select every mode the question requires:

1. Fresh discovery finds new providers, serializations, labels, and formats in objects added since the preceding review.
2. Historical replay reruns current code on the complete retained history. Use it after detection-path or format-support changes and on the periodic backstop defined in the reference.
3. Removal parity proves that every detected removable signal is cleared without violating the signal family's fidelity invariant.
4. Calibration or provider oracle is required where the corpus has no self-evident answer key. Never treat a local negative as proof that a proprietary watermark is absent.

Start by inventorying the current code, not a remembered list. Enumerate image and video visible-mark registries, metadata readers and strippers, local invisible decoders, explicit invisible vendor routes, supported containers, and the stable signal families emitted by identify. Reconcile that inventory with the coverage matrix before interpreting any green result. A hand-written marker list or report family map that omits a current registry member is itself a finding.