| --- |
| license: apache-2.0 |
| library_name: sklearn |
| pipeline_tag: text-classification |
| tags: |
| - ai-systems |
| - capabilities |
| - reasoning |
| - planning |
| - memory |
| - agents |
| - world-models |
| - verification |
| - reliability |
| --- |
| |
| # Capability Classifier |
|
|
| **Capability Classifier** is a lightweight reference model that maps short AI task descriptions to practical capability categories. |
|
|
| It is published under the **ai-systems** handle as a transparent demonstration model for AI-system analysis. |
|
|
| ## Capability Labels |
|
|
| - `adaptation` |
| - `agents` |
| - `coding` |
| - `memory` |
| - `multimodal` |
| - `planning` |
| - `reasoning` |
| - `reliability` |
| - `science` |
| - `tool-use` |
| - `verification` |
| - `world-modeling` |
|
|
| ## Examples |
|
|
| Input: |
|
|
| ```text |
| Break a complex objective into subtasks and replan after failure. |
| ``` |
|
|
| Expected category: |
|
|
| ```text |
| planning |
| ``` |
|
|
| Input: |
|
|
| ```text |
| Predict how the environment will change before acting. |
| ``` |
|
|
| Expected category: |
|
|
| ```text |
| world-modeling |
| ``` |
|
|
| Input: |
|
|
| ```text |
| Run tests before accepting generated code. |
| ``` |
|
|
| Expected category: |
|
|
| ```text |
| verification |
| ``` |
|
|
| ## Usage |
|
|
| ```python |
| from joblib import load |
| |
| classifier = load("capability-classifier.joblib") |
| |
| text = "Use a browser and API to complete the task" |
| prediction = classifier.predict([text])[0] |
| |
| print(prediction) |
| ``` |
|
|
| ## Model Architecture |
|
|
| The reference model uses: |
|
|
| - TF-IDF text features |
| - unigram and bigram features |
| - logistic regression classification |
|
|
| The model is intentionally small so the classification approach remains easy to inspect and reproduce. |
|
|
| ## Training Data |
|
|
| The model was trained on a small curated set of short AI-task descriptions covering capability areas such as: |
|
|
| - reasoning |
| - coding |
| - planning |
| - memory |
| - tool use |
| - agents |
| - multimodal understanding |
| - world modeling |
| - verification |
| - reliability |
| - adaptation |
| - science |
|
|
| ## Intended Use |
|
|
| Suitable for: |
|
|
| - capability explorers |
| - educational tools |
| - lightweight taxonomy experiments |
| - AI-system documentation |
| - prototyping |
| - simple routing demos |
|
|
| ## Limitations |
|
|
| This is a **reference model**, not a benchmark and not a production-grade classifier. |
|
|
| It was trained on a small curated dataset. Predictions outside the covered task descriptions may be unreliable. |
|
|
| The model should not be used for medical, legal, financial, safety-critical, or other high-impact decisions. |
|
|
| ## Related Dataset |
|
|
| `ai-systems/ai-system-patterns` |
|
|
| ## Related Model |
|
|
| `ai-systems/system-router` |
|
|
| ## License |
|
|
| Apache-2.0 |
|
|
