Update /log skill to use transcript backups via Sonnet subagent; add switch-mode

- skills/log/SKILL.md: pre-gathers unprocessed transcript metadata (compact
  JSON via list-transcripts-here.sh) rather than full content; spawns a
  Sonnet subagent (not Haiku — gotcha detection requires judgment) to read
  JSONL backups, write a companion -transcripts.md log, and mark backups
  processed in tracking.json; adds Agent and Bash(bash|pwd|python3) to
  allowed-tools
- skills/switch-mode/SKILL.md: add previously untracked skill to repo

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

skills/log/SKILL.md

@@ -4,7 +4,7 @@ description: >
   End-of-session logging. Captures key decisions, gotchas, open questions, and discussion
   points into memory/log/ for later reflection. Run before ending a session to preserve
   context. Fast and low-friction -- just run /log.
-allowed-tools: Read, Write, Glob, Bash(date *), Bash(ls *), Bash(cat *), Bash(find *), Bash(rm *), Bash(mkdir *)
+allowed-tools: Read, Write, Glob, Agent, Bash(date *), Bash(pwd), Bash(ls *), Bash(cat *), Bash(find *), Bash(rm *), Bash(mkdir *), Bash(python3 *), Bash(bash *)
 ---
 
 # Session Log Skill
@@ -17,6 +17,9 @@ You are capturing key points from the current session into a structured log file
 !`date +%Y-%m-%d`
 !`date +%Y%m%d-%H%M%S`
 
+### Current project directory
+!`pwd`
+
 ### Existing log files
 !`ls -1 memory/log/ 2>/dev/null || echo "No log directory yet"`
 
@@ -29,16 +32,19 @@ You are capturing key points from the current session into a structured log file
 ### Current MEMORY.md index
 !`cat MEMORY.md 2>/dev/null || echo "No MEMORY.md found"`
 
+### Unprocessed transcript backups for this project (metadata only)
+!`bash ~/.claude/scripts/list-transcripts-here.sh 2>/dev/null || echo "[]"`
+
 ## Instructions
 
-Review the **full conversation history** in your context window and extract the key points worth preserving. Not every session needs a log — if the session was trivial (a typo fix, a quick question), say so and skip.
+Review the **full conversation history** in your context window and extract key points worth preserving. Not every session needs a log — if the session was trivial (a typo fix, a quick question), say so and skip.
 
-### Step 1: Create the log directory if needed
+The "Unprocessed transcript backups" above shows metadata (filenames, timestamps) for any pre-compaction snapshots not yet captured in a log. **Do NOT read the transcript content yourself** — that is handled by a subagent in Step 2 to avoid context overflow.
+
+### Step 1: Create the log directory and write the in-context log
 
 If `memory/log/` does not exist, create it with `mkdir -p memory/log/`.
 
-### Step 2: Write the log file
-
 Generate the filename as `memory/log/YYYY-MM-DD.<HHMMSS>.md` using the pre-gathered date and timestamp values.
 
 Write the file using this format:
@@ -72,9 +78,82 @@ Write the file using this format:
 
 **Guidelines:**
 - Omit empty sections entirely rather than leaving them blank
-- The `[topic]` tag on gotchas should match existing memory topic names where possible (e.g., `[k8s]`, `[cilium]`, `[ansible]`, `[sops]`, `[helm]`). Use new tags for new topics.
+- The `[topic]` tag on gotchas should match existing memory topic names where possible (e.g., `[k8s]`, `[cilium]`, `[ansible]`, `[sops]`, `[helm]`)
 - Keep entries concise — this is raw material for `/reflect-logs`, not a polished document
-- Include enough context that each entry makes sense on its own without the full conversation
+- Include enough context that each entry makes sense without the full conversation
+
+### Step 2: Dispatch transcript analysis subagent (if unprocessed transcripts exist)
+
+If the pre-gathered transcript list is non-empty and contains backup files that `exists: true`:
+
+Spawn a **Sonnet** subagent (model: sonnet) with the following prompt. Sonnet is used (not Haiku) because gotcha detection requires judgment about backtracking, failed attempts, and domain-specific failure modes — Haiku tends to miss these. Fill in the bracketed values from the pre-gathered data:
+
+---
+**Subagent prompt template:**
+
+You are processing pre-compaction transcript backups into a structured session log.
+
+**Project directory:** [CWD from pre-gathered context]
+**Log directory:** memory/log/ (relative to project dir — write files there using absolute path)
+**Log filename:** [SAME HHMMSS timestamp as Step 1, but with suffix -transcripts, e.g. memory/log/YYYY-MM-DD.HHMMSS-transcripts.md]
+**Transcripts to process:** [paste the JSON array from the pre-gathered list]
+
+## Your task
+
+For each backup file listed above (where `exists: true`):
+
+1. Extract the conversation using:
+   ```
+   python3 ~/.claude/scripts/extract-transcripts.py --extract <backup_name>
+   ```
+   Run this as a Bash command and read the output.
+
+2. If the transcript has >40 turns, process it in two passes:
+   - First half of turns in one read
+   - Second half in a second run (re-run --extract and skip to turn N)
+   Note: the --extract command outputs all turns; read the full output but focus analysis on substance.
+
+3. After reading all transcripts, write a single log file at the absolute path:
+   `[PROJECT_ABS_PATH]/memory/log/YYYY-MM-DD.HHMMSS-transcripts.md`
+
+   Use this format:
+   ```markdown
+   # Transcript Log — YYYY-MM-DD (pre-compaction backups)
+
+   ## Sources
+   - <backup_name> (session <session_id>, saved <saved_at>)
+
+   ## Summary
+   <!-- What was worked on across the captured sessions -->
+
+   ## Decisions
+   - Decision: <what> — Rationale: <why>
+
+   ## Gotchas Discovered
+   - **[topic]** Symptom: <what happened> — Fix: <what resolved it>
+
+   ## Open Questions
+   - <question>
+
+   ## Key Context
+   - <fact>
+
+   ## Process Notes
+   - <note>
+   ```
+
+4. After writing the log, mark all processed transcripts:
+   ```
+   python3 ~/.claude/scripts/extract-transcripts.py --mark-all-processed "[CWD]" --log-file "memory/log/YYYY-MM-DD.HHMMSS-transcripts.md"
+   ```
+
+5. Report: transcript(s) processed, log file written, any issues encountered.
+
+**Allowed tools for the subagent:** Read, Write, Bash(python3 *), Bash(mkdir *)
+
+---
+
+Spawn this subagent with `model: sonnet` and wait for it to complete before continuing.
 
 ### Step 3: Prune old logs
 
@@ -91,6 +170,6 @@ After writing the log file, check for old logs that should be pruned:
 ### Step 4: Summary
 
 Print a brief summary:
-- Log file created (with path)
-- Number of entries by section
+- In-context log file created (with path)
+- Whether a transcript analysis subagent was dispatched (and which backups it processed)
 - Any files pruned or warnings issued