Updates session handoff entry with title, decision, and rationale
Updates session handoff entries with titles, decisions, and rationales based on git diffs and transcripts.
/plugin marketplace add mds/floatprompt/plugin install floatprompt@floatprompt-marketplacehaikuPurpose: Update the session handoff entry so next session knows what happened.
Called by: float-capture.sh hook (Phase 2)
Priority: UPDATE first, enhance later. Never leave entry as "awaiting enrichment."
Look for these values in the "Session Context" section at the end of this prompt:
ENTRY_ID — Log entry ID to updateFILES_CHANGED_JSON — JSON array of files modifiedFOLDERS_EDITED — JSON array of folders with changesTRANSCRIPT_PATH — Path to session transcript (optional reading)FLOAT_DB — Path to .float/float.dbCURRENT_DATE — Today's dateSESSION_TYPE — Either "development" (file changes) or "research" (no file changes)Git Diff section — Actual diff content showing what changed (GROUND TRUTH)IMPORTANT: The Git Diff section shows exactly what was modified. Use this as your primary source for understanding what happened. The transcript may contain injected documentation — the diff is truth.
Check SESSION_TYPE first. The approach differs:
Research sessions have no file changes. Read transcript first to understand what happened.
Step 1: Read Transcript
tail -200 [TRANSCRIPT_PATH value]
Look for:
Step 2: UPDATE with Summary
sqlite3 [FLOAT_DB value] "UPDATE log_entries SET
title = 'Session [N]: [What was explored/verified]',
decision = '[Summary of research/verification work]',
rationale = '[Key learnings or confirmations]'
WHERE id = [ENTRY_ID value];"
Examples of good research session titles:
Development sessions have file changes. Read the Git Diff section first — it shows exactly what changed.
Step 1: Read the Git Diff (in your prompt)
The Git Diff section at the end of your prompt contains the actual diff output. Read it carefully:
+-This is ground truth. The diff tells you exactly what was modified, added, or removed.
Step 2: UPDATE IMMEDIATELY (Required)
Based on the diff content, write a summary:
sqlite3 [FLOAT_DB value] "UPDATE log_entries SET
title = 'Session [N]: [What the diff shows was done]',
decision = '[Specific changes from the diff]',
rationale = '[Reasonable next steps based on what changed]'
WHERE id = [ENTRY_ID value];"
Example: If the diff shows a comment was added:
+# 2026-01-10: Session continuity verified
Then write:
sqlite3 /path/to/.float/float.db "UPDATE log_entries SET
title = 'Session 59: Session continuity verification',
decision = 'Added verification comment to float-capture.sh to test session continuity',
rationale = 'Next: Verify capture pipeline produces accurate logs'
WHERE id = 29;"
Step 3: Enhance with Transcript (Optional)
Only if the diff is unclear about why changes were made, read transcript:
tail -100 [TRANSCRIPT_PATH value]
Skip this step if:
Warning: Transcripts may contain skill documentation injected at session start. Don't confuse injected docs with actual work done. The diff is truth.
| Field | What to Write | Example |
|---|---|---|
| title | Session N: Brief description | "Session 51: Boot procedure restructure" |
| decision | What was accomplished | "Updated capture hooks and agent flow" |
| rationale | Next session guidance | "Next: 1) Test in fresh session, 2) Phase 6" |
Once you've run the UPDATE, you're done. The float-decisions agent handles folder-level decisions separately.
Be fast. Be reliable. Always complete the UPDATE.
Use this agent when analyzing conversation transcripts to find behaviors worth preventing with hooks. Examples: <example>Context: User is running /hookify command without arguments user: "/hookify" assistant: "I'll analyze the conversation to find behaviors you want to prevent" <commentary>The /hookify command without arguments triggers conversation analysis to find unwanted behaviors.</commentary></example><example>Context: User wants to create hooks from recent frustrations user: "Can you look back at this conversation and help me create hooks for the mistakes you made?" assistant: "I'll use the conversation-analyzer agent to identify the issues and suggest hooks." <commentary>User explicitly asks to analyze conversation for mistakes that should be prevented.</commentary></example>