Does the ledger execute conversational edits?
No. It structures requests and review evidence. Execute only in an authorized tool after verifying current controls and preserving a reversible source.
Tool worksheet / task entry
Seedance 2.5 Conversational Editing Generator turns focused inputs into polished creative results.
Prepared workflow
Build a row-based ledger for conversational edit requests, inputs, protected elements, observed changes, approvals, and rollback decisions.
Give each request a stable ID and columns for requester, source version, quoted instruction, target time range, intended effect, protected elements, references, priority, and acceptance owner. Add separate fields for assumptions and clarification questions so an operator cannot silently convert ambiguous language into a destructive edit. Use controlled status values such as drafted, clarified, ready, attempted, review, accepted, rejected, and superseded. Link assets instead of embedding private material in the sheet. The register should allow a producer to filter unresolved requests and allow an editor to identify the exact input that a conversation referred to.
For each attempt, capture output ID, method used, visible account context, actual changed region, unexpected differences, review evidence, and rollback location. Keep a field for current capability verification with values verified, unverified, unavailable, or not applicable; never translate an X post into verified. Add checks for crop, timing, identity, object permanence, text, audio, transitions, and rights-sensitive material. A pass can be technically completed yet remain editorially rejected. The ledger’s purpose is to preserve that distinction and prevent an operator from reporting command acceptance as media acceptance.
Before handoff, require every high-priority row to have an owner and disposition. Group accepted requests by output version, list rejected changes with reasons, and expose unresolved dependencies. Reconcile the selected master against the ledger so no superseded output is delivered. Export a human-readable snapshot with stable asset references and preserve the working record according to the production’s retention policy. The recipient should be able to trace each visible revision back to a request and reviewer without needing access to a private conversation transcript or relying on undocumented product behavior.
Capability boundary
Dated evidence
Product and model details can change. These links identify the evidence checked for the claims scoped below.
Circulation only; not product, capability, quality, access, repeatability, or outcome evidence.
Reader notes
No. It structures requests and review evidence. Execute only in an authorized tool after verifying current controls and preserving a reversible source.
Keep an immutable source, the exact request, protected elements, acceptance criteria, and a rollback path. Verify the current authorized controls separately.
Prepare a shot-extension ledger for boundary frames, invariant cues, prompt versions, join defects, terminal frames, and editorial decisions.
Open field notePrepare a shot-level character checklist for reference versions, protected identity cues, scene state, drift defects, and approval status.
Open field notePrepare a timed beat sheet, continuity register, risk list, and acceptance checklist before attempting a one-shot generation.
Open field notePrepare a campaign review board for character rights, asset provenance, claims, disclosure, channel rules, defects, approvals, and incidents.
Open field noteContinue the workflow
Verify the current visible workspace context before relying on any product behavior.