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MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, Senpi/pi, oh-my-pi (omp), gajae-code (gjc), OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, Aside browser-agent sessions, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subage
Passed 5 of 10 test cases with the skill, and 2 of 10 without it.
and 5 more in the full report
8 fixed2 passed either way10 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which reference file details OpenCode storage directories, opencode.db SQLite schema, and session message fallback locations?
| Checked | Without skill | With skill |
|---|---|---|
| References references/opencode.md. | Missed | Passed |
The instructions your model reads when the skill loads.
Find local coding-agent sessions across agent products before answering from memory. Prefer the bundled finder for broad cross-platform search, then read the selected session or raw file when you need exact evidence.
IF the user names a platform, load its reference first.
| Platform | Read |
|---|---|
| Codex / OpenAI Codex CLI | references/codex.md |
| Claude Code / Claude Desktop histories | references/claude.md |
| OMO / Senpi / pi coding-agent logs | references/senpi.md |
oh-my-pi (omp, ~/.omp) and gajae-code (gjc, ~/.gjc) logs | references/senpi.md |
| OpenCode / oh-my-openagent (formerly oh-my-opencode) storage | references/opencode.md |
| OpenClaw, Droid, Amp, Gemini, Kimi, Qwen, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, Kiro, Goose, Hermes, Crush, Zed, Aside | references/all-platforms.md |
| Unknown / "any session" / cross-agent search | references/all-platforms.md |
Run the broad finder first unless the user gave an exact file path. For fuzzy recall, expand the query first.
When the user remembers a task vaguely ("that OpenCode bug", "the dashboard PR", "when did we fix X"), derive 3-6 short query lanes before searching: product/tool aliases, repo/package names, exact error text, issue/PR/session IDs, English/Korean phrasing, and likely verbs such as fix, review, plan, deploy, or merge. Run the lanes together with repeated --query so match_reasons shows which wording found the hit.
python3 scripts/find-agent-sessions.py list --limit 20
python3 scripts/find-agent-sessions.py find "commit" --from 7d --platform senpi --platform opencode
python3 scripts/find-agent-sessions.py find "proxy" --platform openclaw --platform droid --platform amp
python3 scripts/find-agent-sessions.py find "refactor" --platform oh-my-pi --platform gajae-code
python3 scripts/find-agent-sessions.py find --query "deploy" --query "token usage" --workers 64
python3 scripts/find-agent-sessions.py find --query "opencode bug" --query "fix opencode" --query "OpenCode parent session" --include-subagents --workers 64
python3 scripts/find-agent-sessions.py read <session-id>
Use python instead of python3 on systems where that is the available executable.
If scope is broad (multi-month, many repos/platforms, or a vague "what happened with X"), split independent searches by names/errors, repos/cwds, platforms/models, and time windows. Use available subagent/delegation tools for these lanes when they exist; otherwise run the finder calls in parallel. Merge candidates by id/path, then read the most likely sessions.
detail_hint; run that read <session-id> --platform <platform> command to see the first user prompt, last user prompt, events, and child sessions together.test cases passed, vs 2 / 10 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.