--- name: conv-lookup description: Find, review, read, inspect, summarize, or compare Overdeck conversations. Use when the user references a pan.localhost/conv/ URL, a conversation ID (e.g. "conv 371", "conversation 108"), a fuzzy reference ("that GPT conversation", "the last Sonnet session"), or asks to review/read/look at/check/summarize/compare conversations. Maps conversation IDs to Claude Code JSONL session files and parses session content. Read-only. triggers: - review conversation - read conversation - look at conversation - look at that conversation - check conversation - inspect conversation - summarize conversation - compare conversations - what was in conversation - that conversation - pan.localhost/conv - conv/ - conv - conversation --- # Conversation Lookup Use this skill whenever the user references a Overdeck conversation — by `pan.localhost/conv/` URL, numeric id, conversation name, or a fuzzy reference like "that GPT conversation". Handles single-conversation review, recent-conversation listing, search, and side-by-side comparison. ## When to use - User asks about a specific conversation ID (e.g., "check conv/108", "what was happening in conversation 42?") - User pastes a `https://pan.localhost/conv/` URL and asks you to review, read, or look at it - User wants to compare two conversations (e.g., voice/style diff across models) - User wants to resume or summarize a past conversation - User asks for recent conversation history - Need to find the JSONL session file for a conversation to analyze its content > **Do not** try `WebFetch` on `pan.localhost/conv/` — the dashboard is an SPA and WebFetch will return empty page chrome. Always go through the script / DB. ## "Which conversation am I in?" If you are an agent inside a conversation and need to know *your own* conversation (e.g. to hand it off), **do not** run `pan conv scan` / `list` / `show` and guess. Run: ```bash pan conv current # alias: pan conv whoami ``` This resolves the current conversation deterministically from the session you are running in (PAN-1520) — no guessing. To hand off or fork your own conversation, just omit ``: `pan handoff` / `pan fork` self-detect the same way. ## How it works Every Overdeck conversation is tracked in the SQLite database at `~/.panopticon/panopticon.db` in the `conversations` table. Use the first-class CLI resolver to map a conversation ID to its Claude Code JSONL transcript: ```bash pan conv jsonl # alias: pan conv transcript pan conv jsonl --json ``` `pan conv jsonl` is the canonical resolver. It reads the conversation's `claude_session_id` + `cwd`, resolves through the shared Overdeck transcript-path helper, preserves the one-level `~/.claude/projects/*/.jsonl` fallback, and reports one of: - `ok` — path exists on disk - `expired` — Claude session id is known, but the JSONL is not present on disk - `unknown` — no `claude_session_id` is recorded for this conversation `conv-find.py --jsonl ` delegates to `pan conv jsonl --json `; do not reimplement path encoding, derivation, or glob fallback in the skill script. **The `session_file` column is deprecated (PAN-451) and NULL for all conversations created since 2026-05.** Never conclude "no session file recorded" from a NULL `session_file` — resolve through `pan conv jsonl` instead. Plain `pan conv jsonl ` prints the absolute path to stdout and exits 0 only when status is `ok`; it exits 1 for `expired` and `unknown`. `pan conv jsonl --json ` always prints a JSON object containing `status`, `path`, `conversationId`, `claudeSessionId`, and `cwd`; read the `status` field rather than the process exit code in JSON mode. ## Running commands The script is at the root of this skill directory. Always run it from any working directory. ### Find a specific conversation ```bash python3 scripts/conv-find.py ``` Example output: ```text Conversation #108 Name: 20260412-4175 Status: ended Model: claude-opus-4-6 Effort: medium CWD: ~/Projects Issue: N/A Title: Lexerra game rules query out of scope Cost: $22.90 Created: 2026-04-12T01:44:30.908Z Ended: 2026-04-12T17:00:06.619Z Session file: ~/.claude/projects//.jsonl Session messages: 130 By role: assistant=62, user=68 Tool uses: 41 First prompt: I don't have any information about a game called "Lexerra"... Last prompt: That means the new code is running but still producing nonsense words... Last assistant: I traced the remaining nonsense generation to... ``` ### Get only the JSONL path Prefer the canonical resolver directly: ```bash pan conv jsonl 108 pan conv transcript 108 # alias ``` The skill helper delegates to the same command: ```bash python3 scripts/conv-find.py --jsonl 108 ``` ### Print a normalized summary of recent notable messages ```bash python3 scripts/conv-find.py --summary 108 ``` This includes recent messages with: - line number in the JSONL - role - tool names used in that message - normalized text snippet ### Output machine-readable JSON ```bash python3 scripts/conv-find.py --json 108 python3 scripts/conv-find.py --recent 20 --json python3 scripts/conv-find.py --search gpt-5.4 --json ``` For a single conversation, `--json` includes: - database metadata - a `session_summary` object with normalized session info ### List recent conversations ```bash python3 scripts/conv-find.py --recent 20 # default 20 ``` ### Search by title/cwd/model ```bash python3 scripts/conv-find.py --search lexerra python3 scripts/conv-find.py --search gpt-5.4 ``` ## Session parsing behavior The script now tolerates the JSONL message shape variations seen in real Claude Code sessions. ### Supported shapes `message.content` may be: - a plain string - a list of strings - a list of typed blocks Typed blocks may include: - `text` - `thinking` - `tool_use` - `tool_result` The parser normalizes these into: - text fragments - tool names - role/timestamp/line metadata ## Parsing session content manually If you still need custom parsing, do not assume `message.content` is always a list of dict blocks. ```python import json, pathlib path = pathlib.Path(session_file) for line in path.read_text().splitlines(): if not line.strip(): continue try: obj = json.loads(line) except json.JSONDecodeError: continue msg = obj.get("message") if not isinstance(msg, dict): continue content = msg.get("content") # content may be a string, list[str], or list[dict] ``` ## Key database columns The `conversations` table has these useful columns: - `id` — numeric conversation ID (the number in `/conv/`) - `name` — Overdeck-generated name (e.g., `20260412-4175`) - `status` — `active` or `ended` - `cwd` — working directory when spawned - `issue_id` — associated issue (null for manual convs) - `claude_session_id` — Claude Code session UUID; `pan conv jsonl` combines this with `cwd` to resolve the JSONL path (see "How it works") - `session_file` — **deprecated (PAN-451)**: full JSONL path on legacy rows only; NULL since 2026-05 - `title` — auto/AI-set title from first message - `title_seed` — original user message that started the conversation - `total_cost` — cached total cost in USD - `model` — model used (e.g., `claude-opus-4-6`, `gpt-5.4`) - `effort` — effort level (`low`, `medium`, `high`) - `created_at`, `ended_at` — timestamps ## Quick SQL queries For direct database queries, use Python's built-in sqlite3 CLI — the standalone `sqlite3` binary is NOT installed on all machines: ```bash # Find conversation by ID python3 -m sqlite3 ~/.panopticon/panopticon.db "SELECT id, name, status, claude_session_id, cwd, title, model, created_at FROM conversations WHERE id = 108;" # Search by keyword in title python3 -m sqlite3 ~/.panopticon/panopticon.db "SELECT id, claude_session_id, cwd, title FROM conversations WHERE title LIKE '%lexerra%';" ``` (`python3 -m sqlite3 ""` requires Python ≥3.12, which is the baseline here. If a plain `sqlite3` binary happens to be on PATH it works the same.) ## Comparing two conversations When the user wants a voice/approach/regression diff between two conversations: 1. Resolve both via `python3 scripts/conv-find.py --json ` to get `resolved_session_file`, `session_file_status`, and `model`. 2. Extract readable text from each resolved session file (use `--summary`, or jq for full text). 3. Present side-by-side labelled by model, so style differences are obvious. Typical use cases: "how did GPT-5.4 handle this vs Sonnet?", "compare conv 365 and 366", "why does the GPT version feel clunkier?". ## See Also - `unarchive-conversation` — restore an archived Overdeck conversation to active state (write operation; use this if the conversation you're reviewing is archived and you want it live in Mission Control) - `pan show ` — inspect agent state for *issue* work (different scope — agents working on issues, not user conversations)