--- license: mit language: - en task_categories: - text-generation pretty_name: PrototypeBench v0.1 tags: - benchmark - llm-evaluation - llm-benchmark - coding-agent - agent-evaluation - swe-bench - fastapi - python - software-engineering - execution-based-evaluation - rlvr size_categories: - n<1K source_datasets: - original configs: - config_name: default data_files: - split: test path: "instances.jsonl" dataset_info: features: - name: instance_id dtype: string - name: repo dtype: string - name: pr_number dtype: int32 - name: pr_url dtype: string - name: pr_title dtype: string - name: base_commit dtype: string - name: head_commit dtype: string - name: problem_statement dtype: string - name: patch dtype: string - name: test_patch dtype: string - name: stack_domain dtype: string - name: contamination_tier dtype: string - name: created_at dtype: string - name: schema_version dtype: string --- # PrototypeBench v0.1 > **Can your agent ship a full-stack AI-native prototype?** PrototypeBench is an open benchmark for evaluating AI coding agents on **full-stack feature shipping**. Where SWE-Bench measures bug-fixing in mature Python libraries, PrototypeBench measures *"can the agent ship a full-stack feature on a modern AI-native stack?"* - **Project home**: https://github.com/prototypebench/prototypebench - **Website**: https://prototypebench.org - **License**: MIT - **Version**: v0.1 (initial corpus) - **Language**: English (problem statements), Python (backend code), TypeScript/JavaScript (frontend code, future) ## Dataset Summary 123 **PR-mined task instances** from active open-source repositories, each shaped for SWE-Bench-compatible execution-based scoring: | Stat | Value | |---|---:| | Total instances | **123** | | Sources | 3 (`fastapi/full-stack-fastapi-template`, `IBM/mcp-context-forge`, `usebruno/bruno`) | | `FAIL_TO_PASS` tests | 940 | | `PASS_TO_PASS` regression-guard tests | 31,945 | | Total test cases per full eval | **32,885** | | stack_domain | 71 backend_only + 52 frontend_only (fullstack instances in later versions) | | contamination_tier | 123 held_out (all post-2026-01-01) | | Schema version | 0.1 | **Comparison**: SWE-Bench Verified has 500 instances, SWE-Bench Lite 300, HumanEval 164. v1 public-beta targets 200–300. ## Scoring Execution-based binary scoring (no LLM-as-judge): ``` score(instance) = 1 iff FAIL_TO_PASS ⊆ passing_tests AND PASS_TO_PASS ⊆ passing_tests (no regression) 0 otherwise ``` **Judge**: `pytest` (backend) and `Playwright` (frontend, future). **Ground truth** = the actual merged PR diff (hidden from the agent). See the [methodology notes](https://github.com/prototypebench/prototypebench/blob/main/PLAN.md#52-오염-대응-contamination-mitigation). ## Usage ```python from datasets import load_dataset ds = load_dataset("banyaaiofficial/prototypebench-v1", split="test") for item in ds: print(item["instance_id"]) # e.g. "IBM__mcp-context-forge-4270" print(item["problem_statement"]) # NL task spec (PR body or closing issue) base_sha = item["base_commit"] # pre-PR commit — agent starts here # Agent produces a non-test unified diff against base_sha. # Score it with the companion harness: # pbench score --source --pr --patch-file agent_patch.diff ``` Each instance extends the SWE-Bench `instances.jsonl` schema with dual-test fields (`fail_to_pass.backend` / `.frontend`, `test_patch_backend` / `.frontend`) for future Playwright integration. Full schema: https://github.com/prototypebench/prototypebench/blob/main/schemas/task_instance.schema.json ## Source Composition | Source | Stars | License | Instances | F2P | P2P | Stack | |---|---:|---|---:|---:|---:|---| | [`fastapi/full-stack-fastapi-template`](https://github.com/fastapi/full-stack-fastapi-template) | 42.7k | MIT | 3 | 7 | 77 | backend_only | | [`IBM/mcp-context-forge`](https://github.com/IBM/mcp-context-forge) | 3.6k | Apache-2 | 68 | 682 | 31,567 | backend_only | | [`usebruno/bruno`](https://github.com/usebruno/bruno) | 44k | MIT | **52** | **251** | **301** | **frontend_only** (NEW v0.2) | All PRs are **merged PRs with maintainer-reviewed tests**. Task instances mine the natural atomic unit of change (one feature or fix at a time). `bruno` frontend instances are validated end-to-end via a Playwright + Electron runner (`harness/frontend_direct_runner.py`) — `docker run` of a custom `prototypebench/playwright-electron` image (Playwright base + GTK/NSS/ATK/Xvfb + chrome-sandbox SUID) that hosts bruno's own `webServer` config in-process. No external backend dependency. ## Data Fields See the task-schema doc for full field-by-field semantics. Highlights: - `instance_id` — stable unique ID (`owner__repo-`) - `base_commit` / `head_commit` — SHAs bounding the reference change - `problem_statement` — natural-language task spec (from closing issue body, else PR description) - `patch` — reference solution (non-test diff). **Hidden from the agent at evaluation time.** - `test_patch` — test-only diff that the harness applies before running the agent's patch - `fail_to_pass` — `{backend: [...], frontend: [...]}` — tests the agent must make pass - `pass_to_pass` — `{backend: [...], frontend: [...]}` — regression-guard tests (must not break) - `stack_domain` — `backend_only` | `frontend_only` | `fullstack` - `environment` — python_version, node_version, uv_lock_sha, etc. for reproducible builds - `contamination_tier` — `public` | `held_out` | `internal_only` ## Contamination & Fairness - **Held-out by construction**: all v0.2 instances are merged after 2026-01-01 (Claude Opus 4.7 cutoff). Submitters must disclose their model cutoff for point-count adjustment. - **Rotation**: held-out tier is rotated per leaderboard season (Phase 5). - **No vendor branding**: benchmark carries no vendor name. Hosted on `banyaaiofficial` for convenience only; the benchmark is project-neutral. ## Limitations - v0.2 adds frontend coverage but no `fullstack` instances yet (single PR touching both backend and frontend in a coordinated way — pending source diversification). - Two backend sources cover 71 instances; `bruno` covers 52 frontend instances — single-source frontend pool is the current trade-off (see [`PLAN.md` §3.3.1-3.3.2](https://github.com/prototypebench/prototypebench/blob/main/PLAN.md) for the OSS-landscape diagnosis behind it). - "test strength = benchmark quality": PRs with weak tests are filtered but not perfectly. Curator review recommended. - Execution-based scoring requires running tests (not instantaneous) — see the harness for Docker-based reproducible runs. - bruno frontend instances run inside an Electron-capable Playwright image with Xvfb; cold-start (`npm run setup` + workspace builds) adds ~3-5 min per phase. Caching across `base` and `head` phases via Docker named volumes is a v0.3 target. ## Related Benchmarks - [SWE-Bench](https://www.swebench.com/) — Python library bug-fixes (2,294 instances). PrototypeBench extends the pattern to modern AI-native full-stack apps. - [SWE-Bench Lite / Verified](https://www.swebench.com/lite.html) — curated subsets. - [Terminal-Bench](https://www.tbench.ai/) — CLI tasks. - [BigCodeBench](https://bigcode-bench.github.io/) — library-usage function-level tasks. ## Citation Citation format will be fixed at Phase 4 public launch. For now: ``` @misc{prototypebench_v02, title = {PrototypeBench v0.2: An AI-native Full-Stack Coding Agent Benchmark}, year = {2026}, url = {https://github.com/prototypebench/prototypebench}, note = {123 instances across 3 source repos (71 backend + 52 frontend); execution-based scoring (pytest + Playwright)} } ``` ## Changelog - **v0.2.2** (2026-05-24): fix — Playwright snapshot tests (`tests/snapshots/**`) on the bruno source are now P2P-only advisory. They're kept in F2P (where they're often the actual feature test — e.g. `#7948`'s "transient request quit flow" is checked via snapshot specs) but excluded from P2P (where they cause spurious failures from rendering / timing drift between base and score-time, even with byte-identical patches). Verified `bruno#7948` with byte-identical agent_patch: previously F2P 4/4 + P2P 13/14 = score 0; now F2P 4/4 + P2P 0/0 = score 1. Total P2P across 52 bruno instances: 327 → 301 (26 snapshot tests dropped). Schema unchanged. - **v0.2.1** (2026-05-24): fix — bruno frontend instances rebuilt with the corrected `test_patch_frontend` extraction. Earlier v0.2 captured only `tests/**/*.spec.ts` (Playwright specs), missing the co-located fixtures (`.bru` collections, `init-user-data/preferences.json`). Result: even a byte-identical copy of the reference patch could fail at score time because specs couldn't load their fixtures. Re-verified on `bruno#7947`: F2P 0/12 → 11/12 with a byte-identical agent_patch (the remaining 1/12 is a Playwright flake unrelated to the fix). Source extraction now uses `tests/**` (entire test subtree). Instance count unchanged (52 frontend). See [docs/phase3-fe-smoke-analysis.md](https://github.com/prototypebench/prototypebench/blob/main/docs/phase3-fe-smoke-analysis.md) for the diagnostic trail. - **v0.2** (2026-05-23): +52 frontend_only instances from `usebruno/bruno` via the new `playwright_direct` runner (custom Playwright+Electron image with Xvfb). Corpus 71 → 123. F2P 689 → 940, P2P 31,644 → 31,971. Frontend ratio 0% → 42%. Schema v0.1 unchanged. - **v0.1** (2026-04-20): initial corpus. 71 backend_only instances, all held_out. Schema v0.1.