task_id string | rollout_index int64 | status string | error string | wall_time_seconds float64 | created_at string | collection_id string | reward float64 | num_trajectories int64 | num_steps int64 | num_events int64 | events list |
|---|---|---|---|---|---|---|---|---|---|---|---|
textcraft_synth.val.12 | 0 | completed | null | 5.68575 | 2026-03-01T05:00:04.023151+00:00 | e43a5319-305c-45b9-a9b6-f514fe5790e6 | 1 | 2 | 11 | 17 | [
{
"type": "trajectory_created",
"ts": 1772341198.4024243,
"process_id": 3925654,
"collection_id": "e43a5319-305c-45b9-a9b6-f514fe5790e6",
"trajectory_id": "d7f07d99-b5c3-43d2-b713-86e0bf6abc5c",
"step_index": null,
"reward": null,
"finish_message": null,
"error_message": null,
... |
textcraft_synth.val.17 | 0 | completed | null | 46.730209 | 2026-03-01T05:14:13.958953+00:00 | 7b272a2e-f749-4c8f-92ff-874a3703af4c | 1 | 8 | 34 | 58 | [
{
"type": "trajectory_created",
"ts": 1772342007.288699,
"process_id": 3925654,
"collection_id": "7b272a2e-f749-4c8f-92ff-874a3703af4c",
"trajectory_id": "4b12e765-4d58-44d9-bda0-bfc318451e00",
"step_index": null,
"reward": null,
"finish_message": null,
"error_message": null,
... |
textcraft_synth.val.19 | 0 | completed | null | 4.233529 | 2026-03-01T02:53:19.886800+00:00 | 7f5084c8-88e8-49a6-88c3-2e81de1e31de | 1 | 2 | 10 | 16 | [
{
"type": "trajectory_created",
"ts": 1772333595.717941,
"process_id": 3925654,
"collection_id": "7f5084c8-88e8-49a6-88c3-2e81de1e31de",
"trajectory_id": "c93bd5dd-7d91-42ec-9d44-7a121457014b",
"step_index": null,
"reward": null,
"finish_message": null,
"error_message": null,
... |
textcraft_synth.val.23 | 0 | completed | null | 13.234536 | 2026-03-01T05:23:08.680313+00:00 | cadbb056-1c52-4719-ae14-78316d34ae97 | 1 | 42 | 167 | 293 | [{"type":"trajectory_created","ts":1772342575.4769948,"process_id":3925654,"collection_id":"cadbb056(...TRUNCATED) |
textcraft_synth.val.28 | 0 | completed | null | 3.55983 | 2026-03-01T05:13:27.190276+00:00 | ecbac6a7-0667-4def-b23d-4577f9968011 | 1 | 3 | 10 | 19 | [{"type":"trajectory_created","ts":1772342003.6951845,"process_id":3925654,"collection_id":"ecbac6a7(...TRUNCATED) |
textcraft_synth.val.31 | 0 | completed | null | 2,526.334131 | 2026-03-01T03:43:36.447317+00:00 | 7162fec4-cca8-40f5-952c-ef2e59e96047 | 1 | 5,223 | 19,699 | 35,368 | [{"type":"trajectory_created","ts":1772334083.3949838,"process_id":3925654,"collection_id":"7162fec4(...TRUNCATED) |
textcraft_synth.val.32 | 0 | completed | null | 8.987913 | 2026-03-01T03:51:23.676756+00:00 | b5944724-3116-4308-b477-f5b54a79e0e5 | 1 | 18 | 73 | 127 | [{"type":"trajectory_created","ts":1772337074.739066,"process_id":3925654,"collection_id":"b5944724-(...TRUNCATED) |
textcraft_synth.val.37 | 0 | completed | null | 269.629289 | 2026-03-01T02:45:39.934819+00:00 | b46a442b-0e47-48fd-a01c-9921aa6e227a | 1 | 1,135 | 4,399 | 7,804 | [{"type":"trajectory_created","ts":1772332869.1237059,"process_id":3925654,"collection_id":"b46a442b(...TRUNCATED) |
textcraft_synth.val.45 | 0 | completed | null | 16.38485 | 2026-03-01T04:45:15.760114+00:00 | 8c559f80-f9c8-46ef-8698-2b3a5289936a | 1 | 11 | 55 | 88 | [{"type":"trajectory_created","ts":1772340299.424118,"process_id":3925654,"collection_id":"8c559f80-(...TRUNCATED) |
textcraft_synth.val.51 | 0 | completed | null | 70.469349 | 2026-03-01T03:00:05.039698+00:00 | b9a8bb94-6526-475e-a5a5-ed2caa54af25 | 1 | 99 | 362 | 659 | [{"type":"trajectory_created","ts":1772333934.5522983,"process_id":3925654,"collection_id":"b9a8bb94(...TRUNCATED) |
textcraft-synth-recursive-agent
TextCraft (synthetic) rollouts from a recursive Qwen3-4B agent (CISPO-trained, depth-aware) that can spawn sub-agents. The agent was trained with a 40K context window; these rollouts were run without a context limit.
There is one row per rollout. The full event log for that rollout is in the events column.
import json
from datasets import load_dataset
ds = load_dataset("apurvaga/textcraft-synth-recursive-agent", split="train")
row = ds[0]
for e in row["events"]:
if e["type"] == "trajectory_step_added":
step = json.loads(e["step"]) # thought, code, output, error, reward, misc
Columns
| column | description |
|---|---|
task_id, rollout_index |
which task and rollout this row is |
status, error, wall_time_seconds, created_at |
from the rollout's metadata.json |
collection_id |
ID of the trajectory collection (root agent and its sub-agents) |
reward |
the root agent's final reward |
num_trajectories |
number of agents in the rollout (1 plus the number of sub-agents) |
num_steps, num_events |
step and event counts across all agents |
events |
the ordered event log (see below) |
Each entry in events has type, ts (Unix timestamp), process_id, collection_id, trajectory_id,
step_index, reward, finish_message, error_message, trajectory, task and step. Fields that don't
apply to an event type are null. trajectory, task, step and finish_message are JSON-encoded strings;
decode them with json.loads.
| event type | fields set |
|---|---|
trajectory_created |
trajectory (initial trajectory; parent_info is null for the root agent and set for sub-agents) |
trajectory_task_set |
task (goal, id, max_steps, misc) |
trajectory_step_added |
step_index, step (thought, code, output, error, reward, misc) |
trajectory_finished |
reward, finish_message, error_message |
Within a row, events interleaves events from the root agent and all of its sub-agents in time order. To get one agent's trajectory, filter by trajectory_id; each sub-agent's parent_info (in its trajectory_created event) links it to the agent that spawned it. Single-agent datasets have one trajectory per row. The task in trajectory_task_set is the
state at the start of the run (for TextCraft, task.misc.initial_inventory is the true starting inventory).
Viewing with platoon's visualization tool
The platoon viewer reads JSONL event logs. hf_to_events.py (in this repo) writes each row back out as
events_<task_id>_<collection_id>.jsonl, byte-for-byte identical to the original log:
pip install datasets
python hf_to_events.py apurvaga/textcraft-synth-recursive-agent ./events
uv run -m platoon.visualization.cli tail --dir ./events
tail loads every event at once, so you see the full trajectory trees immediately. To watch a single run play out step by step, use replay <file.jsonl> --delay 0.25 instead.
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