--- dataset_info: features: - name: task_id dtype: string - name: title dtype: string - name: category dtype: string - name: difficulty dtype: string - name: has_generator dtype: bool - name: ablation_scores dtype: string - name: tni dtype: float32 - name: classification dtype: string splits: - name: train num_examples: 153 - name: test num_examples: 120 license: mit task_categories: - text-generation tags: - multi-agent - benchmark - software-engineering - teamwork - evaluation - llm-evaluation pretty_name: TeamBench --- # TeamBench: A Multi-Agent Teamwork Benchmark ## Overview TeamBench is a rigorous benchmark for evaluating whether LLM-based agent *teams* outperform single oracle agents on realistic software engineering tasks. Each task is executed under five ablation conditions (oracle, restricted, full team, team without planning, team without verification), enabling fine-grained measurement of when and why teamwork helps. The core metric is the **Teamwork Necessity Index (TNI)**, which quantifies how much a task requires coordinated multi-agent effort beyond what a single capable agent can achieve alone. TeamBench uses OS-enforced role separation — Planner, Executor, and Verifier agents operate in isolated sandboxes with distinct tool allow-lists — ensuring that role boundaries are structurally enforced rather than prompt-based. Tasks span 18 categories including security, data engineering, adversarial specification traps, distributed systems, and long-horizon planning, with 153 tasks totalling 459 parameterized instances (seeds 0–2). --- ## Task Categories | Category | Tasks | Description | |---|---|---| | Software Eng. | 22 | Hidden specs, backward compatibility, refactoring | | Security | 17 | Vulnerability patching, cryptographic correctness, audit triage | | Operations | 16 | Incident root-cause, container debugging, monitoring | | Data Engineering | 12 | Schema drift, ETL repair, query optimization | | Testing | 11 | Spec-to-tests, mutation resistance, property-based testing | | Incident Response | 11 | Cascade failure, memory leak, rollback planning | | Information Retrieval | 8 | Evidence QA, misinformation traps, multi-source retrieval | | Policy | 8 | Access control, data retention, license compliance | | Distributed Systems | 7 | Race conditions, Raft consensus, idempotency | | Adversarial | 7 | Spec conflicts, false bug reports, security theater | | Code Review | 6 | API review, style enforcement, test coverage | | Multi-language | 6 | Go concurrency, JavaScript XSS, polyglot debugging | | Long-Horizon | 6 | Multi-step migrations, staged deployments, audit trails | | Pipeline | 6 | ETL fix, API gateway, message queues | | Cross-System Integration | 5 | API contract mismatches, schema evolution, auth federation | | Specification | 3 | Feature implementation from RFC, config schema design | | Integration | 1 | Pipeline repair, API versioning | | Negotiation | 1 | Trade-off configuration under competing constraints | **Difficulty breakdown:** 104 hard, 26 medium, 16 expert, 7 easy (78% hard or expert). --- ## Ablation Conditions Each task is evaluated under five conditions: | Condition | Description | |---|---| | `oracle` | Single powerful agent with full tool access and no role restrictions | | `restricted` | Single agent with executor-only tool access (no planning/verification tools) | | `team` | Full three-role team: Planner → Executor → Verifier | | `team_no_plan` | Two-role team: Executor → Verifier (planning phase skipped) | | `team_no_verify` | Two-role team: Planner → Executor (verification phase skipped) | Scores are in [0, 1] and represent the fraction of grader checks passed. --- ## TNI Metric The **Teamwork Necessity Index (TNI)** measures how much a task *requires* teamwork: ``` TNI = team_uplift / necessity_gap = (team - oracle) / (1 - restricted) ``` - `TNI > 0`: team outperforms oracle relative to the task's difficulty ceiling - `TNI = 1.0`: team achieves the maximum possible improvement over oracle - `TNI > 1.0`: team substantially exceeds oracle (rare; indicates strong synergy) - `TNI < 0`: team underperforms oracle (teamwork overhead hurts) **Classification thresholds:** - `HIGH-TNI`: TNI ≥ 0.5 and team > oracle - `TEAM-HELPS`: team > oracle but TNI < 0.5 - `NEUTRAL`: |team - oracle| ≤ 0.05 - `TEAM-HURTS`: team < oracle Of the 153 tasks: TEAM-HELPS 53, NEUTRAL 51, TEAM-HURTS 28, HIGH-TNI 16. --- ## Usage ```python import json with open("teambench_dataset.json") as f: tasks = json.load(f) # Filter to tasks where teamwork helps team_helps = [t for t in tasks if t.get("classification") in ("TEAM-HELPS", "HIGH-TNI")] print(f"Tasks where team > oracle: {len(team_helps)}") # Get hard tasks with ablation scores hard_with_scores = [ t for t in tasks if t["difficulty"] in ("hard", "expert") and "ablation_scores" in t ] print(f"Hard/expert tasks with ablation data: {len(hard_with_scores)}") # Compute average team uplift uplifts = [ t["ablation_scores"]["team"] - t["ablation_scores"]["oracle"] for t in tasks if "ablation_scores" in t ] print(f"Mean team uplift: {sum(uplifts)/len(uplifts):.3f}") ``` ### Loading via HuggingFace datasets ```python from datasets import load_dataset ds = load_dataset("ybkim95/teambench", split="train") # all 153 tasks # ds = load_dataset("ybkim95/teambench", split="test") # 120 hard/expert tasks only print(ds[0]) ``` --- ## Benchmark Results Cross-model evaluation across Gemini and OpenAI model families shows that: - Team outperforms oracle on **43.9%** of tasks (68/155 with full ablation data) - Average TNI: **0.744** across tasks with a measurable necessity gap - Weaker models benefit *more* from teamwork (larger relative uplift) - `team_no_verify` is often the strongest condition — verifier overhead can hurt on average - The **Expertise-Asymmetry (EA)** variant (5 tasks) shows TNI > 1.0 with capable models, meaning specialized role knowledge pushes teams beyond what any single oracle achieves Full results and leaderboard: [GitHub](https://github.com/ybkim95/TeamBench) --- ## Citation ```bibtex @dataset{kim2026teambench, author = {Yubin Kim}, title = {TeamBench: A Multi-Agent Teamwork Benchmark for LLM Evaluation}, year = {2026}, url = {https://huggingface.co/datasets/ybkim95/teambench}, note = {153 tasks across 18 categories with OS-enforced role separation} } ``` --- ## License MIT License. See [LICENSE](https://github.com/ybkim95/TeamBench/blob/main/LICENSE) for details.