continue-from-accepted

name

continue-from-accepted

description

Continue iterative work from the last ACCEPTED result plus only the new requested change, instead of replaying the conversation. Use during long multi-turn editing of a document, config, or code file; when the user says "keep going from what we had", asks for a follow-up change to something already approved, or is near plan/token limits in an iterative session. Saves one integrity-checked accepted result, builds a minimal continuation prompt, and never carries rejected drafts or transcript history forward.

Continue from accepted

Carry forward the result, not the history that produced it. After a user accepts a version, later changes need only (accepted result + new change) — not the transcript, not rejected drafts, not the reasoning that got there.

State rules (read first)

• The state file is EPHEMERAL working state, not a durable store. Keep it under the OS temp directory: <tmp>/continue-from-accepted/<task-slug>.json (resolve <tmp> via python3 -c "import tempfile;print(tempfile.gettempdir())"). Do NOT create per-repo state directories. Durable facts belong in the memory system; the deliverable itself belongs in the repo. This skill's state is a session-scoped snapshot, nothing more.
• Only acceptance promotes. Save when the user accepts a version (explicitly, or by asking for a further change that keeps the rest). A rejected result is never saved. No accepted result yet → work normally.
• One current result. Each new acceptance replaces the previous state. No history accumulates.
• No secrets in state. If the accepted result contains credentials, do not save it; continue without this skill.

Workflow

Resolve <skill-dir> from where this skill is installed. Do this yourself — never ask the human to run these commands, restate prior work, or manage the state file.

1. On acceptance — save:

python3 <skill-dir>/scripts/state_delta.py save \
  --state <tmp>/continue-from-accepted/<task-slug>.json \
  --accepted-file <path-to-accepted-result>

2. On the next change — build the continuation prompt:

python3 <skill-dir>/scripts/state_delta.py packet \
  --state <tmp>/continue-from-accepted/<task-slug>.json \
  --change "<the user's new requested change>" \
  --max-packet-bytes 16000 \
  --output <tmp>/continue-from-accepted/<task-slug>-packet.txt

Use the packet as the working input (e.g. as a fresh subagent's prompt) instead of re-sending conversation history. The packet instructs the worker: continue from the accepted result, apply only the new change, return the updated result only.

3. Check without exposing content: state_delta.py inspect --state <file> prints byte count + sha256 only.

Failure handling

• The state file is sha256-integrity-checked on load; a hash mismatch means the file was modified outside save — discard it and re-save from the actual accepted artifact. Do not hand-edit state files.
• If packet refuses because the result exceeds the byte cap: select only the relevant passages of the accepted result for this change (search tooling), don't raise the cap reflexively.
• Never retry a token-limit or usage-limit failure unchanged. Reduce the input, pick a cheaper path, or stop and say so.

Provenance

scripts/state_delta.py extracted UNCHANGED from the token-saver skill (Unlock AI / Ringer, 2026) — reviewed: pure stdlib, no network, no telemetry. sha256: 0c2d953c5712cbf5d125cbb1dbdbf29eb851f067b783fc9f8b897729858b0c7b The original's per-repo .token-saver/ state convention was dropped deliberately: it conflicts with the fleet rule against inventing new state stores. Temp-dir state is this skill's policy, set here, not in the script.