| --- |
| 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 <short> --pr <N> --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-<pr_number>`) |
| - `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. |
| |
