README.md

---
pretty_name: "TraceLab Coding Agent Workload Traces"
license: cc-by-4.0
tags:
  - agents
  - coding
  - traces
  - llm-serving
  - tabular
  - datasets
size_categories:
  - 100K<n<1M
source_datasets:
  - original
configs:
  - config_name: default
    default: true
    data_files:
      - split: train
        path: "data/v0.0.2/rounds/train.parquet"
  - config_name: tool_calls
    data_files:
      - split: train
        path: "data/v0.0.2/tool_calls/train.parquet"
  - config_name: timing_events
    data_files:
      - split: train
        path: "data/v0.0.2/timing_events/train.parquet"
---

# TraceLab Coding Agent Workload Traces

TraceLab is a sanitized, real-world workload trace of Claude Code and Codex. Each JSONL row
represents one LLM invocation and retains the serving-relevant structure needed to study sessions,
token accounting, prompt-cache behavior, tool calls, and timing.

- **665,453** agent steps
- **8,058** sessions
- **743,819** normalized tool calls
- **52** pseudonymous users
- Providers: Claude Code and Codex
- Release: **v0.0.2**

Project links:

- [Paper: TraceLab: Characterizing Coding Agent Workloads for LLM Serving](https://arxiv.org/abs/2606.30560)
- [GitHub repository](https://github.com/uw-syfi/TraceLab)
- [Interactive website](https://tracelab.cs.washington.edu/)
- [Pinned GitHub release v0.0.2](https://github.com/uw-syfi/TraceLab/releases/tag/v0.0.2)

## Load the dataset

```python
from datasets import load_dataset

dataset = load_dataset("UW-SyFI/TraceLab", split="train")
print(dataset.num_rows)
print(dataset.features)
```

The default config is the `rounds` table. Load the normalized child tables separately and join them
to rounds with `round_pk`:

```python
tool_calls = load_dataset("UW-SyFI/TraceLab", "tool_calls", split="train")
timing_events = load_dataset("UW-SyFI/TraceLab", "timing_events", split="train")
```

Pin the published snapshot for reproducible studies:

```python
dataset = load_dataset("UW-SyFI/TraceLab", revision="v0.0.2", split="train")
```

The repository also includes the query-ready DuckDB database as an auxiliary artifact:

```python
from huggingface_hub import hf_hub_download
import duckdb

database_path = hf_hub_download(
    repo_id="UW-SyFI/TraceLab",
    repo_type="dataset",
    filename="artifacts/v0.0.2/syfi_coding_trace.duckdb",
    revision="v0.0.2",
)
connection = duckdb.connect(database_path, read_only=True)
print(connection.execute("SELECT provider, count(*) FROM rounds GROUP BY provider").fetchall())
```

## Data format

The Viewer-friendly Parquet representation contains three relational tables with stable schemas:

- `default` / `rounds`: 665,453 LLM invocations with pseudonymous provider/session/round
  identifiers, model, token counts, cache-prefix accounting, source store, and `trace_key`.
- `tool_calls`: 743,819 normalized tool calls keyed to `rounds.round_pk`.
- `timing_events`: 2,688,829 ordered events keyed to `rounds.round_pk`.

Important token fields include:

- `input_tokens_total`: total input tokens reported for the invocation.
- `prefix_tokens`: provider-reported cached input tokens.
- `newly_append_tokens`: non-cached input tokens appended for the invocation.
- `output_tokens`: generated output tokens.

`tool_calls` contains privacy-safe structural metadata such as tool name, pseudonymous tool-call id,
timestamps, input/result character counts, latency, error status, executable labels, and command
skeletons. `timing_events.event_index` preserves event order within each round. Full tool inputs and
outputs are not published.

The original sanitized nested JSONL and the query-ready DuckDB remain available as auxiliary files.
They are byte-identical to the GitHub v0.0.2 release assets. The Parquet tables are deterministic
relational exports of that DuckDB for Hugging Face Data Studio and `load_dataset()`.

## Sanitization and responsible use

The public trace is generated by TraceLab's sanitization pipeline. User, project, session, round,
turn, tool-call, and process-session identifiers are replaced with stable pseudonyms. Local paths,
working directories, source session paths, tool inputs, prompts, responses, and full tool outputs are
removed. Custom executable and integration names are replaced with stable generic labels unless they
belong to an explicitly reviewed public allowlist.

This is a trace of real developer activity. Do not attempt to re-identify contributors or infer their
projects from the remaining workload structure.

## Known limitations

- Consecutive `round_index` values are consecutive normalized records, but should not always be
  interpreted as a single reconstructable linear conversation lineage.
- A small fraction of adjacent transitions report `prefix_tokens` larger than the immediately
  reconstructable previous context. For synthetic session-local KV-cache replay, conservatively cap
  the next reusable prefix at `previous.input_tokens_total + previous.output_tokens`. See
  [TraceLab issue #22](https://github.com/uw-syfi/TraceLab/issues/22).
- Provider tokenization, message framing, cache boundaries, retries, resumes, branches, compaction,
  and historical extractor behavior can affect adjacent-round accounting.
- The sanitized analytical rows intentionally do not contain the message text required for a
  conversational Agent Trace Viewer.

## Files and integrity

| File | SHA-256 |
|---|---|
| `data/v0.0.2/rounds/train.parquet` | `cb8c2b1d23307090c8057c747f955663bacde16a49f84a3c5071a1e2e96a7ab8` |
| `data/v0.0.2/tool_calls/train.parquet` | `7186e0d86d3d870e5b374cc29678a4754fcb789ebee4f5ad86461dd02db6f68b` |
| `data/v0.0.2/timing_events/train.parquet` | `a207499989d4f004a6807698c33ad6da57cd30fd45404188bf8593fc4d3b9296` |
| `data/v0.0.2/syfi_coding_trace.jsonl.gz` | `11ce51ec0a25e3d1d95b025bca2f7d1647e47571eb7cc968acd5fc64d4b4fb65` |
| `artifacts/v0.0.2/syfi_coding_trace.duckdb` | `a7bab286bc640844560850965ccf47975cf66407154132abaab90f27ec9be744` |

The JSONL and DuckDB files are byte-identical to the assets published in the TraceLab v0.0.2 GitHub
release.

## License

The released dataset is licensed under
[Creative Commons Attribution 4.0 International](LICENSE-DATASET.md). Please credit **TraceLab
(SyFI Lab, University of Washington)** and link to <https://tracelab.cs.washington.edu/>. TraceLab
source code is separately licensed under Apache-2.0 in the GitHub repository.

## Citation

```bibtex
@misc{zhu2026tracelabcharacterizingcodingagent,
  title         = {TraceLab: Characterizing Coding Agent Workloads for LLM Serving},
  author        = {Kan Zhu and Mathew Jacob and Chenxi Ma and Yi Pan and Stephanie Wang and Arvind Krishnamurthy and Baris Kasikci},
  year          = {2026},
  eprint        = {2606.30560},
  archivePrefix = {arXiv},
  primaryClass  = {cs.LG},
  url           = {https://arxiv.org/abs/2606.30560}
}
```