| --- |
| license: apache-2.0 |
| task_categories: |
| - image-text-to-text |
| - visual-question-answering |
| - document-question-answering |
| language: |
| - en |
| pretty_name: Multimodal Knowledge Agent (MKA) Showcase Examples |
| --- |
| |
| # Multimodal Knowledge Agent (MKA) — 10 Showcase Examples |
|
|
| **Multimodal Knowledge Agent (MKA)** is a benchmark from Google DeepMind for evaluating autonomous AI agents on complex, multi-step, real-world visual knowledge work across professional domains. |
|
|
| Unlike text-extractable benchmarks where attachments can be solved via plain-text extraction or OCR alone, every MKA task contains a multi-file workspace with load-bearing visual artifacts—such as architectural CAD blueprints, electrical and RF schematics, geospatial rasters, seasonal dependency graphs, biochemical gel and spectrophotometric plates, and multi-axis charts—that require native multimodal perception, cross-document synthesis, tool orchestration (code execution, file inspection), and standalone deliverable generation (`.xlsx`, `.pptx`, `.docx`, `.json`, or structured technical reports). |
|
|
| --- |
|
|
| ## 10 Showcase Tasks (10 Unique Domains & Verticals) |
|
|
| | # | Vertical | Domain | Role | Task ID | |
| | :-: | :--- | :--- | :--- | :--- | |
| | **1** | **Logistics & Mapping** | Surveying & GIS | GIS Analyst | `task_4308eaef4d504328988c1cb5dfd7db77` | |
| | **2** | **Construction** | Architecture | Architect | `task_a46a6c3cebd54b82b9ad5e66d1e14e48` | |
| | **3** | **Engineering** | Electrical & RF Engineering | RF IC Design Engineer | `task_143a5623f26c404baaeb63ccd891e196` | |
| | **4** | **Engineering** | Mechanical & Control Systems | Mechanical Engineering Instructor | `task_dd94dc222db74864a13fcb7c6c2844a2` | |
| | **5** | **Science** | Applied Sciences (Biochemistry) | Biochemist | `task_47d262f6d58c4e5293a22623f0d711e5` | |
| | **6** | **Business** | Workforce Planning & HR Analytics | Workforce Planning Analyst | `task_fea07f327cfd4f4c91af0bf78da197d4` | |
| | **7** | **Finance** | M&A / Management Consulting | Investment Analyst | `task_c9ab91021dc14eab926dfea0a208108a` | |
| | **8** | **Education** | History & Cartography | Historian | `task_9e3bdd2bdccd4164bcc792c914f59925` | |
| | **9** | **Law & Government** | Public Policy | Policy Analyst | `task_5a0212833c224c85b79960604679eb84` | |
| | **10** | **Software & Data** | Data Science | Data Scientist | `task_e49e96e764424db08531c39fb685ed70` | |
|
|
| --- |
|
|
| ## Repository Structure |
|
|
| ```text |
| tasks/ |
| └── task_<id>/ |
| ├── metadata.json # Task ID, prompt, domain, role, input file list, task goal, and economic rationale |
| ├── rubrics.json # Fine-grained grading criteria and criterion weights |
| └── input/ # All source input files provided to the agent in the workspace |
| ``` |
|
|
| Each `metadata.json` contains: |
| - `TaskID`: Unique task identifier (`task_<32-hex>`) |
| - `Prompt`: Full verbatim instruction prompt given to the agent |
| - `All Task Files`: Relative path to the task input workspace (`tasks/task_<id>/input/`) |
| - `Rubric Criteria`: Relative path to the task rubric file (`tasks/task_<id>/rubrics.json`) |
| - `Input_files`: Comma-separated list of input filenames inside `input/` |
| - `Vertical`: Top-level industry vertical |
| - `Domain`: Professional domain |
| - `Role`: Target professional role |
| - `Task Goal`: Summary of the deliverable goal |
| - `Economic Rationale`: Real-world professional time and value context |
|
|
| --- |
|
|
| ## License |
|
|
| Licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). |
|
|
