conv-lookup

name	conv-lookup
description	Find, review, read, inspect, summarize, or compare Panopticon conversations. Use when the user references a pan.localhost/conv/<id> 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 Panopticon conversation — by pan.localhost/conv/<id> 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/<id> 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/<id> — 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:

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 <conv>: pan handoff / pan fork self-detect the same way.

How it works

Every Panopticon conversation is tracked in the SQLite database at ~/.panopticon/panopticon.db in the conversations table. Each row maps to a Claude Code JSONL session file in ~/.claude/projects/-home-eltmon-Projects/.

Running commands

The script is at the root of this skill directory. Always run it from any working directory.

Find a specific conversation

python3 scripts/conv-find.py <id>

Example output:

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/<project-hash>/<session-id>.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

python3 scripts/conv-find.py --jsonl 108

Print a normalized summary of recent notable messages

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

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

python3 scripts/conv-find.py --recent 20   # default 20

Search by title/cwd/model

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.

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/<id>)
• name — Panopticon-generated name (e.g., 20260412-4175)
• status — active or ended
• cwd — working directory when spawned
• issue_id — associated issue (null for manual convs)
• session_file — full path to the JSONL session file
• 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:

# Find conversation by ID
sqlite3 ~/.panopticon/panopticon.db "SELECT id, name, status, session_file, title, model, created_at FROM conversations WHERE id = 108;"

# Search by keyword in title
sqlite3 ~/.panopticon/panopticon.db "SELECT id, session_file, title FROM conversations WHERE title LIKE '%lexerra%';"

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 <id> to get session_file and model.
2. Extract readable text from each 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 Panopticon 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 <id> — inspect agent state for issue work (different scope — agents working on issues, not user conversations)