skills/skill-collections/alfworld/alfworld-tool-user/SKILL.md
Use when the agent needs to apply a tool to a target object in ALFWorld to accomplish an interaction such as cleaning, heating, cooling, or examining. This skill handles locating both the tool and target object, then executing the correct environment action (e.g., `clean`, `heat`, `cool`, `use`) to progress the task.
npx skillsauth add zjunlp/Skills alfworld-tool-userInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Trigger this skill when:
knife 1, potato 2)sinkbasin 1, microwave 1)clean, heat, cool, use, examine)take {object} from {receptacle}Apply the tool to the object using the correct action syntax:
| Interaction | Action Command | Example |
|-------------|---------------|---------|
| Clean | clean {obj} with {tool} | clean knife 1 with sinkbasin 1 |
| Heat | heat {obj} with {tool} | heat potato 2 with microwave 1 |
| Cool | cool {obj} with {tool} | cool apple 1 with fridge 1 |
| Examine | examine {obj} | examine book 3 |
| Use | use {tool} | use desklamp 1 |
knife 1 becomes clean)sinkbasin for cleaning, not bathtub).take first.Task: "Clean the knife and put it in the drawer."
> go to countertop 1
On the countertop 1, you see a knife 1, a saltshaker 2.
> take knife 1 from countertop 1
You pick up the knife 1 from the countertop 1.
> go to sinkbasin 1
On the sinkbasin 1, you see nothing.
> clean knife 1 with sinkbasin 1
You clean the knife 1 using the sinkbasin 1.
Result: knife 1 is now clean and ready for the next step (storing).
development
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
development
Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.
tools
Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.
development
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.