Bench2Agent

Ask which benchmarks researchers evaluate on, how usage changes across years, and which new benchmarks other researchers adopt. Bench2Agent connects your signed-in Claude Code or Codex to tested benchmark tools and checks answers against the tool results and original paper evidence.

Use it in a terminal or in a local browser workspace. Both interfaces share the same AI CLI login, conversations, research data and answer checks; the browser runs on your computer, without a hosted backend.

Usage frequency describes adoption, not benchmark quality.

Install · Browser workspace · Data pipeline · User guide · Releases

Get started

You need Python 3.10+ and Claude Code or Codex installed and signed in on your computer. Bench2Agent and the official AI CLI are separate installations. If needed, sign in using claude auth login or codex login first.

Install into an active Python environment; a virtual environment is recommended:

python -m pip install --upgrade bench2agent

On macOS/Linux, uv provides an alternative isolated installation:

uv tool install --upgrade bench2agent

Choose one installation method, then choose an interface:

Interface	Start	Use it for
Terminal	bench2agent	Ask questions and follow-ups, resume conversations, inspect sources with /sources
Local browser	bench2agent --web	Read answers beside benchmark cards, comparison tables, original evidence and data coverage

bench2agent --web opens the workspace in your browser; --no-open prints its address instead and --port N chooses a port. Keep that terminal open while you use it; Ctrl+C stops the workspace.

On the first interactive launch, Bench2Agent automatically downloads the research-data bundle (about 45 MB), verifies its checksum and installs it as a data revision. Subsequent launches reuse the data. No GPU, database server, Bench2Agent account or API key is needed for the CLI-login route. Model usage follows your AI account's limits.

If both AI CLIs are signed in, choose one at the prompt. Your choice is saved. To choose explicitly:

bench2agent --connector claude
# Or:
bench2agent --connector codex

Ask a question, then a follow-up. /sources shows evidence, /chats lists saved conversations, /resume ID continues one, /new starts fresh, and Ctrl+C cancels an unfinished answer. Saved conversations keep their data revision after updates and can be continued in either interface. Linux/WSL is tested; macOS follows the same POSIX path. Native Windows CLI cancellation has not yet been validated.

API access is an explicit alternative: bench2agent --connector api prompts for the provider and a hidden, session-only API key. API billing is separate from a Claude or ChatGPT subscription.

Local browser workspace

Ask “Which benchmarks do recent robotics papers evaluate on most?” and open the evidence panel to inspect the answer's counts and scope:

Actual local browser session using Claude Code and revision 1e1fa171722da693; answer wording varies. The Compare panel is built from the recorded tool results, independently of the model's prose.

Use Benchmarks for resource links and introducing papers, Compare for counts and percentages, Evidence for original paper sentences, and Data coverage for the conference editions, filters and analyzed-paper counts behind the answer. A percentage describes use among the analyzed papers, not every paper published at a conference.

The terminal uses the same tools and checks; /sources opens the evidence. Quotes are matched to their source paper, and numbers are checked against the same turn's tool results. A dotted underline in the browser, or an [unverified figure] in the terminal, means the checker could not connect a number to the evidence; it does not necessarily mean the number is wrong.

Verified resource links and links printed in a paper are shown separately. The latter do not establish a benchmark connection. Resource observations say what was checked and when; a repository link or file listing does not guarantee that the benchmark data can be downloaded or that its records were validated.

From papers to evidence

Conference sources provide the paper lists, titles, authors and source IDs. The pipeline resolves papers to arXiv, archives the available HTML and extracts structured evidence from it. Benchmark-use extraction is rule-based; the answering model chooses tools and explains their results rather than counting papers itself.

Information	What is extracted or retained
Paper text and structure	Sections, table and figure captions, table cells, references and inline citation links
Benchmark identity	Matched benchmark names and spellings, stable catalog IDs and source-backed aliases; ambiguous names remain separate
Evaluation and training use	Statements that the paper evaluates or trains on a benchmark, stored with the role and original evidence text and location
Introduction claims	Sentences proposing a new benchmark or dataset; only reviewed claims enter the introduction catalog, with the review method recorded
Resource links	URLs in release statements and front-matter lines such as “Code — URL”; individually reviewed benchmark locations remain distinct from unconfirmed paper links
Source provenance	Archived HTML SHA-256 and arXiv version when known; evidence keeps its paper and location, and reviewed paper links also retain their source element and review record

References or name mentions alone do not establish use. Text assembled from table cells is labeled as assembled evidence rather than presented as a verbatim sentence. Introduction and location reviews performed by Claude Code are recorded as AI reviews, not human reviews.

Dates describe different events: fetch and re-check times belong to the processing history; an OAI datestamp signals a metadata-record update, not a confirmed change to the paper's text. The arXiv version and HTML hash identify the source when known. Link observations have their own check dates, and each published database records its build time. Unknown dates stay unknown.

How the data is stored

The builder writes directly to a local SQLite database, with normalized tables linked by paper and benchmark IDs:

Tables	Stored relationships
editions, observations, observation_authors	Conference and year, paper IDs, authors and coverage; one observation per paper and conference edition
benchmarks, benchmark_aliases, claims	Benchmark identity, aliases and reviewed introduction evidence; resource records and paper links are retained as structured metadata
uses, use_roles, use_surfaces, evidence	Which paper uses which benchmark, evaluation versus training, observed spellings and supporting passages
observation_labels	Subject labels with their source, method and version, preserving conference tracks separately from research fields
unattributed, unattributed_candidates	Mentions that cannot be assigned confidently, with candidate benchmark IDs and reasons

Raw HTML archives and intermediate extraction files stay in the build environment. A separate working database tracks processing stages, source versions, retries and review queues. The downloadable research database contains the catalog, observations, counts and evidence; it does not contain the processing queue, private conversations or the complete HTML archive. External benchmarks' actual questions, labels and images are separate downloads.

Both interfaces query this database through the same BenchmarkStore and six MCP tools: coverage, usage, trends, introductions, adoption and evidence. Usage counts paper–edition observations; adoption counts unique papers and separates other authors, introducing authors and unknown relationships.

Each installed database is an immutable data revision with a manifest, content hash and file checksums. New data installs alongside existing revisions; saved conversations keep the revision used for their first answer, so follow-up questions and answer checks remain on the same data. No database server is required. Database design · Counting and evidence rules

Use the tools inside Claude Code or Codex

After installation, these shortcuts download missing data and open the official client with Bench2Agent's MCP tools:

bench2agent claude
# Or:
bench2agent codex

Ask the client to use Bench2Agent. In this route the client writes the answer; Bench2Agent's final-answer checks run in the bench2agent conversation interface. MCP setup and scripted queries.

Data coverage

The 2026-10-21 data release (revision 1e1fa171722da693, used in the screenshot) contains 61 editions of 11 conferences, 88,172 analyzed paper-edition observations and 9,334 benchmark/dataset entries, including 8,770 entries with reviewed introduction claims and 315 benchmarks with individually reviewed resource links (336 links): an AI review against the introducing paper's own release line and the text at the link. It also adds 70 unique links printed in 65 papers, attached to 74 benchmark entries; these paper links remain separate from verified resource links. Paper and benchmark coverage is the same as in the 2026-10-19 release.

Venue	Included editions
AAAI	2020 · 2021 · 2022 · 2023 · 2024 · 2025 · 2026
ACL	2020 · 2021 · 2022 · 2023 · 2024 · 2025 · 2026
CORL	2020 · 2021 · 2022 · 2023 · 2024 · 2025
CVPR	2021 · 2022 · 2023 · 2024 · 2025 · 2026
ECCV	2024 · 2026
EMNLP	2020 · 2021 · 2022 · 2023 · 2024 · 2025
ICCV	2021 · 2023 · 2025
ICLR	2020 · 2021 · 2022 · 2023 · 2024 · 2025 · 2026
ICML	2020 · 2021 · 2022 · 2023 · 2024 · 2025 · 2026
NAACL	2021 · 2022 · 2024 · 2025
NEURIPS	2020 · 2021 · 2022 · 2023 · 2024 · 2025

Counts come from explicitly stated evaluation or training use in parsed arXiv HTML, with the analyzed editions and denominator reported for each query. Missing or unparsed papers remain unknown. Field filters match labels that name a research field, each with its origin (the primary area the authors declared at submission, the topic an AAAI track states, or a derived topic); proceedings volume ids are kept but are not fields, and many editions carry no field labels at all, so a field filter excludes those papers. New introduction claims in the expanded editions are not yet reviewed, so introduction discovery is less complete than usage coverage. “New” means a reviewed claim in this corpus, not the first public release worldwide.

The 2026-10-21 bundle (data format v2) installs with Bench2Agent 0.5.0 or later (0.5.0 serves it without the paper links or percentages); the 2026-10-13 bundle (format v1) still installs from its explicit URL through a one-time conversion. Data rules · Database design

Updates

Version 0.6.0 is distributed on PyPI and GitHub. Code and research data update separately:

1. Update the code with your installation method (rerun its install command).
2. Run bench2agent data install to download and activate the new data. Installed data is never replaced automatically.
3. Start a new conversation (/new) to use it. Saved conversations keep the revision they started on.
4. If you use the tools inside Claude Code or Codex, restart that client so its Bench2Agent server reads the new revision.

Version 0.4.0 cannot install the new bundle and keeps working with the 2026-10-13 data. Migration and data management.

The 0.6.0 local browser workspace implements bench2agent --web with the same conversation service as the terminal. It runs a loopback API and bundled browser assets on your computer; a paid backend or hosted login is not required. The two interfaces share saved conversations and data revisions. Browser mode needs no server extra. Browser guide.

The existing optional web/HTTP MCP modules are development prototypes. The earlier hosted visitor prototype is deferred; hosted sign-in, strong visitor isolation and public operation remain unvalidated; they are separate from the local terminal, browser and stdio MCP interfaces. Account connections.

Code is licensed under Apache-2.0.