| --- |
| license: apache-2.0 |
| language: |
| - en |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| tags: |
| - agents |
| - web-agents |
| - benchmark |
| - google-workspace |
| - tool-use |
| pretty_name: KNOWS Benchmark |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test.jsonl |
| --- |
| |
| # KNOWS Benchmark |
|
|
| KNOWS evaluates web agents on the work people actually do in Google Workspace: writing documents, |
| building spreadsheets, and composing slide decks that require web research, multi-step tool use, and |
| faithful grounding in retrieved sources. |
|
|
| This dataset contains the **task definitions** — the prompt an agent receives, plus the structured |
| evaluation rubric used to grade the artifact it produces. |
|
|
| | | | |
| |---|---| |
| | Tasks | **110** (22 templates × 5 instances) | |
| | Domains | 20 | |
| | Mean prompt length | 204 words | |
| | Evaluation steps per task | ~25 | |
|
|
| | Artifact | Templates | Tasks | |
| |---|---|---| |
| | Google Docs | 5 | 25 | |
| | Google Sheets | 9 | 45 | |
| | Google Slides | 8 | 40 | |
|
|
| - **Code and evaluators:** https://github.com/alexgill321/KNOWS-benchmark |
| - **Project page:** https://alexgill321.github.io/KNOWS-benchmark |
|
|
| ## This dataset does not score anything |
|
|
| Each task is graded by a task-specific Python evaluator that inspects the *finished artifact* |
| through the Google Workspace APIs and its rendered form — combining deterministic comparisons, |
| tolerance-based matching, geometric layout tests, document-structure inspection, browsing-trace |
| verification, and LLM/VLM judgements. Those evaluators live in the GitHub repository, not here. |
|
|
| To actually run and score the benchmark, follow |
| [RUNNING_STANDALONE.md](https://github.com/alexgill321/KNOWS-benchmark/blob/main/RUNNING_STANDALONE.md), |
| or use the reference harnesses: |
| [BrowserGym-Knows](https://github.com/farhanishmam/BrowserGym-Knows) and |
| [AgentLab-Knows](https://github.com/farhanishmam/AgentLab-Knows). |
|
|
| Use this dataset when you want the prompts and rubric as data — for analysis, task selection, or |
| driving your own harness. |
|
|
| ## Fields |
|
|
| | field | description | |
| |---|---| |
| | `task_id` | Registered harness id, e.g. `knows.docs_1_formal_letter.1`. For nine families this differs from `family` (`sheets_6_investmenttracker` registers as `knows.sheets_6_stock_tracker`) — use `task_id` to launch a task, `family` to find it on disk | |
| | `short_id` | Short internal id (e.g. `11a`); `null` where none was assigned | |
| | `family` | Task template, e.g. `docs_11_personal_recipe_ocr` | |
| | `instance`, `instance_num` | Which of the five instances | |
| | `artifact` | `Docs`, `Sheets`, or `Slides` | |
| | `group`, `domain` | Use-case grouping and domain label | |
| | `prompt` | The agent-facing instruction, verbatim from `task.md` (which itself carries `{{...}}` placeholders where a task writes to Drive — see below) | |
| | `checkpoints` | Rubric: `[{n, title, description, steps[]}]`, each step carrying `name`, `description`, `text`, `category`, `llm_vlm_primary` | |
| | `n_steps` | Number of evaluation steps | |
| | `total_points` | Points available for the task | |
| | `requires_browsing_history` | Whether the evaluator checks the agent's visited URLs | |
| | `source_assets` | Hosted, view-only Drive files the prompt references — usable as-is | |
| | `evaluator_url`, `checkpoints_url` | Links to the evaluator and rubric on GitHub | |
|
|
| Step `category` labels come from the benchmark's step-type taxonomy (`structural_check`, |
| `information_retrieval`, `formatting_check`, `content_check`, `spatial_check`, `web_visit_check`, |
| `visual_check`), with `llm_vlm_primary` marking steps decided primarily by a model judge. |
|
|
| ## External assets |
|
|
| Six task families reference Google Drive files from their prompts, in two kinds. |
|
|
| **Files the task reads.** Listed in `source_assets` (30 across the benchmark) and left in the prompt |
| verbatim. These are hosted copies shared *anyone-with-link, view only*, so they work as-is and a |
| benchmark run cannot modify them. |
|
|
| **Locations the task writes into.** Ten tasks — all of `sheets_10_paper_sorting` and |
| `slides_17_removeimagesaddplaceholders` — ask the agent to upload files into a Drive folder, or to |
| edit a scratch copy of a deck. A write destination cannot be shared between users, so the benchmark |
| does not ship one: the prompt carries a `{{TOKEN}}` you replace with a location in your own Drive. |
|
|
| | placeholder | what to supply | |
| |---|---| |
| | `{{OUTPUT_FOLDER_URL}}` | A folder the agent may write into. For `sheets_10` it must contain `pdfs/` and `figures/` subfolders — the prompt names those by name | |
| | `{{IMAGES_FOLDER_URL}}` | A folder for the images extracted from the deck | |
| | `{{WORKING_COPY_URL}}` | An editable copy of the source presentation (`slides_17` instance 1 only) | |
|
|
| The code repository provisions all of them for you, for both families at once: |
|
|
| ```bash |
| python src/browsergym/knows/eval/tasks/provision_run_targets.py --all |
| ``` |
|
|
| It creates a fresh folder tree per run and writes the URLs to `run_targets.json`, which the |
| harness and the evaluators both read — so the folder the agent uploaded to is the one that gets |
| graded. On your own harness, substitute with a plain string replace on `prompt`. Tasks whose |
| prompt contains no `{{` need no setup at all. See |
| [ASSETS.md](https://github.com/alexgill321/KNOWS-benchmark/blob/main/ASSETS.md) for the full layout. |
|
|
| ## Maintenance and versioning |
|
|
| Tasks are curated to be time-agnostic and independent of any single website, but some reference live |
| pages that can change. External sources the evaluators depend on are verified periodically; if a |
| change significantly alters a task's difficulty or solvability, the task is updated or replaced with |
| one of similar scope. Every change ships as a new tagged release on GitHub, and prior versions stay |
| available, so results remain reproducible. **Please report the benchmark version alongside your |
| results.** Issues can be reported via the |
| [templates](https://github.com/alexgill321/KNOWS-benchmark/issues/new/choose). |
|
|
| This dataset corresponds to benchmark **[v1.1.0](https://github.com/alexgill321/KNOWS-benchmark/releases/tag/v1.1.0)**. |
|
|
| ## Licence |
|
|
| Apache-2.0, matching the code repository. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{gill2026knows, |
| title = {The Hard Part Comes After Search: Benchmarking Web Agents on |
| Synthesizing, Organizing, and Displaying Knowledge}, |
| author = {Gill, Alexander and Ishmam, Md Farhan and Nguyen, Xuyen and |
| Bhat, Neha and DeYoung, Parker Henry and |
| Hashemi Chaleshtori, Fateme and Stringham, Nathan and |
| Marino, Kenneth and Marasovi\'{c}, Ana}, |
| booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2026}, |
| year = {2026}, |
| url = {https://arxiv.org/abs/2609.30604}, |
| eprint = {2609.30604}, |
| archivePrefix = {arXiv} |
| } |
| ``` |
|
|
| Please also state which benchmark version you ran (above). |
|
|
