Use when the user wants to continue work from one agent in another agent, inspect recent sessions, or summarize a saved session or checkpoint for handoff

Hand Off Session Response Format Begin the first response to this skill invocation with the line: Entire Session Handoff: followed by a blank line, then the content. Apply the header to the first response of the invocation only — not on follow up turns and not on error / early exit responses (no sessions found, transcript missing). Its presence signals the skill ran and produced real output. The "Unanswered Question" branch still gets the header. STOP — Read these rules before doing ANYTHING 1. Do NOT ask clarifying questions. Auto detect the session and read the transcript. 2. Do NOT run git log , git status , git branch , ps aux , or any other exploratory commands. Use only the entire CLI commands listed below. 3. Do NOT say "Would you like me to continue?" or "Let me know if you want me to pick this up." Just read the transcript and start working. Exception: if the previous agent asked the user a question that was never answered, you MUST ask the user that question before proceeding. Required CLI: entire 0.6.2+ ( session list json , session info transcript , session current json transcript , checkpoint explain json transcript raw transcript session index N ). If a flag is rejected, tell the user to upgrade and stop. Flow: Active session handoff (default — also covers bare invocation and "current"/"active") Step 1: Resolve the canonical worktree path If the output is valid JSON, read its worktree path field — that is the canonical worktree root for this invocation, set by Entire itself. Use it verbatim in the next step (no cwd heuristic needed; symlinks, /private/var / /var quirks, and subdirectory invocation are all handled). If the output is not JSON (Entire prints No active session found in this worktree. when nothing is active), set the canonical worktree path to null and rely on the bidirectional prefix match fallback in Step 2. Step 2: Pick the session Each entry has session id , agent , status , worktree path , started at , last active , turns , last prompt , files touched . Apply filters in this order: 1. Worktree scope. If you got a canonical worktree path in Step 1, keep entries where worktree path equals it exactly. Otherwise, keep entries where cwd starts with worktree path or worktree path starts with cwd . If either filter yields zero entries, fall back to the unscoped list — better to summarize a slightly off session than to refuse the handoff. 2. User named agent filter (optional). If the user said "codex", "claude", "kiro", "gemini", etc., keep only entries whose agent matches case insensitively as a substring (so gemini matches Gemini CLI ). 3. Drop self. Drop entries where agent matches the agent currently running this skill (e.g. Claude Code , Codex , Cursor , Gemini CLI , Copilot CLI , Factory AI Droid , OpenCode ). If this empties the list , undo this filter and keep self — the user is asking you to summarize your own current session for compaction. Note that fact in the announcement (Step 5). 4. Pick most recent. Sort by last active (fall back to started at ) descending; take the first. If filtering still leaves zero entries (truly nothing in the list, even self), print a one line error (no header) and stop. Step 3: Stream the raw transcript Snapshot is bounded to the file size at command start. Output is JSONL for most agents and a single JSON document for Gemini CLI. Step 4: Extract conversation content JSONL agents (Claude Code / Codex / Cursor / Copilot CLI / Factory AI Droid / OpenCode): Gemini CLI (single JSON document — no JSONL grep): The top level shape varies by Gemini CLI version, but messages live under one of messages , contents , history , or turns . Each entry has a role ( user / model / function / tool ) and a content payload under one of parts[].text , content , or text . Extract role + text in chronological order: If neither shape works, fall back to the Read tool on the JSON file and locate the message array by inspection. Do not show the raw extracted lines to the user. They are inputs for Step 5. Step 5: Announce, summarize, present Announcement. First line of the body: Handing off <agent session — <turns turns, last active <relative time , ID <first 8 of session id . If the picked session is your own (Step 2 self filter fallback), prepend a one clause note: Self handoff (no other sessions in this worktree) . This gives the user a chance to catch a wrong pick before reading the summary. Summary structure (skip any section with no genuine content — do not hallucinate filler): 1. Task Overview — the user's core request, success criteria, stated constraints. 2. Current State — completed work: files created/modified, key decisions, artifacts produced. 3. Important Discoveries — technical constraints found, rationale behind decisions, errors hit and how they were resolved, failed approaches and why. 4. Next Steps — specific remaining actions, blockers, priority ordering. 5. Context to Preserve — user preferences, domain details, commitments made during the session. 6. Unanswered Question (only if applicable) — if the previous agent's last message asked the user a question or presented options that were never answered, capture it exactly as asked. A one bug fix session might legitimately have only Task Overview + Current State + Next Steps. A pure research session might have only Task Overview + Important Discoveries. Empty sections are a feature; pad them only if you have real content. Continue. Show announcement + summary. If section 6 exists, ask the user that question and wait. Do NOT pick a default. Otherwise, immediately pick up the work — plan, code, or whatever the next step is. Do not ask permission. Flow: Checkpoint handoff (user gives a checkpoint ID) Step 1: Enumerate sessions The envelope's sessions array lists every session that contributed. Multi session checkpoints are common (parallel agents, retries, multi phase work) and earlier sessions often carry the rationale, failed approaches, and user constraints that the latest session takes for granted. Step 2: Pick which sessions to stream 1 session. Stream the normalized compact transcript: 2–8 sessions. Iterate every index 0..N 1. Do not rely on the transcript default (latest session only): More than 8 sessions. Sort the sessions array by timestamp ( started at or whichever field the envelope provides) descending and take the 8 most recent. Note the cap in the announcement: <M of N sessions summarized; oldest <M N elided as too old to matter. This keeps the skill bounded while still covering the recent rationale layer. raw transcript keeps the per agent raw bytes so the same JSONL grep extraction works. Index 0 is the first session chronologically. Step 3: Extract, announce, summarize, continue Run the Step 4 extraction (head + tail per file) on each /tmp/handoff ckpt .jsonl , then merge into a single five section summary. Treat earlier sessions as the source of "Important Discoveries" and "Context to Preserve"; the latest session feeds "Current State" and "Next Steps". Empty section rule from the active session flow applies. Then announce + present per Step 5 of the active session flow, with the announcement adapted to checkpoint context ( Handing off checkpoint <short id — <M sessions, <total turns turns total. ).

session-handoff