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. The header applies to the full compaction-summary flow, including the "Unanswered Question" branch (which is still a successful run — the skill summarized the transcript and surfaced the question).

• Apply the header to the first response of the invocation only. Do not re-print it on follow-up turns within the same invocation (e.g. after the user answers the surfaced unanswered question).
• Do not include the header on error or early-exit responses (e.g. no .git/entire-sessions/ directory, no sessions found after filtering, transcript file missing at the path the session JSON points to). The header's presence should signal that the skill ran and produced real output.

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 entire sessions list, entire sessions info, entire explain --session, git log, git status, git branch, ps aux, or any other exploratory commands. They waste time and don't give you the transcript.
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.)
4. Do NOT summarize the session as having "0 turns" or "no progress" without first reading the actual transcript file. The entire CLI metadata often undercounts — the transcript is the source of truth.
5. Skip your own session. Your agent (e.g. Claude Code) also has a session in .git/entire-sessions/. Exclude any session whose agent_type matches your own agent type from the results.

Flow: Active / current session handoff

When the user says "current", "active", or just "hand off this session":

Step 1: Run entire status

entire status

This returns the active session ID. If the user mentioned an agent name (e.g. "codex"), look for that agent's session in the output.

Step 2: Find the transcript path

Read the session file at .git/entire-sessions/<session-id>.json using the Read tool:

Read: .git/entire-sessions/<session-id>.json

The file looks like this:

{
  "session_id": "019d730f-e099-7910-a946-b5b20e2cfafc",
  "agent_type": "Codex",
  "phase": "active",
  "started_at": "2026-04-09T09:25:21.725231-07:00",
  "last_interaction_time": "2026-04-09T09:25:21.725657-07:00",
  "transcript_path": "/Users/alisha/.codex/sessions/2026/04/09/rollout-....jsonl",
  "last_prompt": "create solitaire game"
}

Extract the transcript_path field. This is the path to the full conversation transcript.

Fallback: If entire status doesn't give you a session ID, or the session JSON doesn't exist, use the Glob tool to find all .git/entire-sessions/*.json files, read them, and pick the most recent one (by last_interaction_time or started_at). Filter by agent name if the user specified one. Always exclude sessions matching your own agent type.

Step 3: Extract and summarize the transcript

Phase A — Extract raw transcript (do NOT show this to the user):

grep -E '"type":"(message|function_call|user|assistant)"' <transcript_path> | cut -c1-2000

If the output exceeds ~500 lines, read the last 100 lines (final state) and first 20 lines (original task):

grep -E '"type":"(message|function_call|user|assistant)"' <transcript_path> | tail -100 | cut -c1-2000
grep -E '"type":"(message|function_call|user|assistant)"' <transcript_path> | head -20 | cut -c1-2000

Phase B — Produce a compaction summary. Internally process the extracted transcript and produce a structured summary with these sections:

1. Task Overview — The user's core request, success criteria, and any stated constraints or clarifications.
2. Current State — Completed work: files created/modified, key decisions made, artifacts produced.
3. Important Discoveries — Technical constraints uncovered, rationale behind decisions, errors hit and their resolutions, failed approaches and why they failed.
4. Next Steps — Specific remaining actions, blockers, and priority ordering.
5. Context to Preserve — User preferences, domain-specific details, and 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 here exactly as asked.

Be concise but complete — err on the side of including information that would prevent duplicate work or repeated mistakes.

Step 4: Present summary, then continue

Show the compaction summary from Phase B to the user.

Critical rule — unanswered questions go to the user, not you. If section 6 (Unanswered Question) exists, present that question to the user and wait for their answer. Do NOT answer it yourself or pick a default. The user is the decision-maker.

If there is no unanswered question, immediately pick up the work — start planning, coding, or doing whatever the next step is. Do not ask permission.

Flow: Checkpoint handoff (user gives a checkpoint ID)

1. Run entire explain --checkpoint <checkpoint-id> --full --no-pager
2. If --full fails, fall back to entire explain --checkpoint <checkpoint-id> --raw-transcript --no-pager
3. Extract conversation content from ALL session transcripts (do NOT show raw output to the user):

grep -rE '"type":"(message|function_call|user|assistant)"' <transcript_dir_or_files> | cut -c1-2000

For large checkpoints with many sessions, focus on the last 100 lines per transcript to understand final state, and the first 20 lines for the original task.

4. Produce and present a compaction summary using the same 5-section format from Step 3 Phase B above, then continue.

Resolve checkpoint repos in order: explicit override → local entire/checkpoints/v1 branch → .entire/settings.json checkpoint_remote → nearby local clone.

Flow: No specific request (bare invocation)

Use the Glob tool to find .git/entire-sessions/*.json. Read each file, exclude your own agent type, pick the most recent by last_interaction_time. Read the transcript at transcript_path. Summarize and continue.

Agent name filtering

Words like "codex", "claude", "kiro", "gemini" in the user's request are filters for session selection. Match them case-insensitively against the agent_type field (fall back to agent field). Never invoke another agent's CLI.