| # AgentPulse — Data and Code Release |
|
|
| **NeurIPS 2026 Datasets & Benchmarks Track companion artifact.** |
|
|
| This bundle contains all data, code, and reproduction scripts for the |
| AgentPulse evaluation framework described in the paper |
| *AgentPulse: A Continuous Multi-Signal Framework for Evaluating AI Agents in Deployment*. |
|
|
| License: **CC BY 4.0** (see `LICENSE`). |
|
|
| --- |
|
|
| ## Contents |
|
|
| ``` |
| AgentPulse-Data-v6/ |
| ├── README.md ← this file |
| ├── LICENSE ← CC BY 4.0 |
| ├── croissant.json ← Croissant metadata (JSON-LD) |
| ├── data/ |
| │ ├── csv/ ← 18 CSV exports of every relevant DB table |
| │ └── sqlite/ ← (optional) full SQLite database, if present |
| ├── code/ |
| │ ├── collectors/ ← 18 signal-collector implementations |
| │ ├── scoring/ ← NLP pipeline + factor composite + data quality |
| │ ├── pipeline/ ← scheduler / orchestration |
| │ ├── config.py ← global pipeline configuration |
| │ ├── main.py ← entrypoint (`python main.py --serve`, etc.) |
| │ └── requirements.txt ← Python dependencies |
| ├── paper/ |
| │ ├── neurips_agentpulse.tex ← LaTeX source |
| │ ├── neurips_agentpulse.pdf ← compiled paper |
| │ ├── neurips_2026.sty ← NeurIPS 2026 style file |
| │ ├── checklist_.tex ← NeurIPS Paper Checklist |
| │ ├── regen_figures.py ← regenerates all 5 paper figures from the data |
| │ └── fig*.{png,pdf} ← compiled figures |
| └── docs/ |
| └── schema.md ← per-table column documentation |
| ``` |
|
|
| --- |
|
|
| ## Data tables (`data/csv/`) |
|
|
| | File | Rows | Description | |
| |-----------------------------------|---------|-------------| |
| | `agent_scores.csv` | 13,504 | Composite + per-factor scores per agent per category, time-stamped. The headline scoring output. | |
| | `agent_signals_raw.csv` | 3,283 | Raw per-signal observations per agent (pre-aggregation). | |
| | `agent_benchmark_signals.csv` | 1,563 | Published benchmark scores (SWE-bench, GAIA, WebArena, HumanEval+, τ-bench). | |
| | `agent_github_history.csv` | 62 | GitHub stars / contributors / commits time-series. | |
| | `agent_pypi_history.csv` | 1,440 | PyPI / npm download history. | |
| | `sentiment_scores.csv` | 60,639 | NLP-scored texts (VADER + TextBlob + FinBERT + DistilBERT-SST2 ensemble). | |
| | `data_quality.csv` | 38,965 | Composite quality score per text (uniqueness × bot × credibility × specificity). | |
| | `models.csv` | 148 | Agent + model registry with vendor / category metadata. | |
| | `bluesky_signals.csv` | 35,326 | Per-platform raw text + engagement. | |
| | `reddit_signals.csv` | 2,413 | "" | |
| | `hn_signals.csv` | 21,205 | "" | |
| | `stackoverflow_signals.csv` | 571 | "" | |
| | `github_signals.csv` | 23,288 | "" | |
| | `github_discussions_signals.csv` | 2,090 | "" | |
| | `devto_signals.csv` | 596 | "" | |
| | `mastodon_signals.csv` | 1,160 | "" | |
| | `v2ex_signals.csv` | 1,794 | "" | |
| | `devtools_signals.csv` | 89 | VS Code / IDE marketplace install counts. | |
|
|
| All CSVs are UTF-8 encoded with a header row. Timestamps are ISO-8601 |
| in UTC. See `docs/schema.md` for full column documentation. |
|
|
| --- |
|
|
| ## Reproducing paper results |
|
|
| ```bash |
| cd code/ |
| pip install -r requirements.txt |
| |
| # Reproduce all figures (writes into ../paper/) |
| python ../paper/regen_figures.py |
| |
| # Re-derive composite scores from raw signals |
| python -m scoring.agent_scoring_v2 --rebuild |
| |
| # Re-run the full pipeline end-to-end (continuous mode) |
| python main.py |
| ``` |
|
|
| The cross-factor predictive validity result (Table 3, ρₛ=0.52, p<0.01, |
| n=35) is computed in `code/scoring/agent_scoring_v2.py` and can be |
| re-derived directly from `data/csv/agent_scores.csv` and external |
| adoption proxies. |
|
|
| --- |
|
|
| ## Provenance |
|
|
| All signals are collected from public APIs with documented rate-limits |
| under each API's terms of service. Specifically: |
|
|
| - **GitHub**: REST + GraphQL APIs (60 req/hr unauth, 5,000 req/hr authed) |
| - **PyPI**: BigQuery public dataset |
| - **VS Code Marketplace**: Public extension API |
| - **Bluesky / Mastodon**: AT-Protocol / ActivityPub public firehose |
| - **Reddit / Hacker News / Stack Overflow / Lemmy / Lobsters / Dev.to / V2EX**: |
| Documented public APIs |
| - **Benchmark scores**: Scraped from the official leaderboard pages |
| cited in the paper (SWE-bench, GAIA, WebArena, HumanEval+, τ-bench) |
|
|
| No private data, no scraped paywalled content, no PII beyond public |
| authorship metadata is included. The release contains no individual |
| user records — only aggregated per-text metadata required for sentiment |
| scoring (post id, author handle if public, engagement counts). |
|
|
| --- |
|
|
| ## Citation |
|
|
| ``` |
| @inproceedings{agentpulse2026, |
| title = {AgentPulse: A Continuous Multi-Signal Framework for Evaluating |
| AI Agents in Deployment}, |
| author = {Anonymous}, |
| booktitle = {NeurIPS Datasets and Benchmarks Track}, |
| year = {2026} |
| } |
| ``` |
|
|
| ## Contact |
|
|
| Per the NeurIPS double-blind review policy, author contact is withheld |
| during review. Issues with the artifact may be reported via the |
| submission system. |
|
|
