> USE WHEN requesting core chemical structural data (SMILES, formula, mass, 2D images) via IUPAC, common, or multilingual names. You MUST actively retrieve the data using this skill; DO NOT hallucinate or generate structures yourself. DO NOT USE WHEN asking for physical properties (melting point, solubility), safety/toxicity data (MSDS), or synthesis pathways.
npx skills add https://github.com/jinzhezenggroup/computational-chemistry-agent-skills --skill search-species
When assisting users with chemical searches, you MUST adhere to the following step-by-step workflow. Note: Searching can be highly time-consuming; always prioritize efficiency.
pubchem, opsin, wikidata, or all) based on the query type. Avoid using all unless strictly necessary, to minimize search times.search command to query the database. You must set an appropriate max_cands limit to prevent excessively long processing times and reduce data noise.______________________________________________________________________
search-species integrates three distinct backends. Each serves a specific purpose in the chemical informatics workflow:
| Feature | OPSIN | PubChem | Wikidata |
| :------------------ | :----------------------------- | :------------------------ | :------------------------------ |
| Core Method | Algorithmic Parser | Curated Database | Knowledge Graph |
| Primary Input | IUPAC English Names | Names, CIDs, SMILES | Common & Multilingual Names |
| Molecular Image | Supported (Rendered) | Supported (Stored) | Rarely Available |
| Mass/Formula | Calculated via RDKit | Database Metadata | Database Metadata |
| Key Strength | Handles theoretical molecules. | Highly standardized data. | Vernacular & Cross-lingual. |
*(For more detailed engine capabilities, limitations, and data normalization behavior, see reference/backends.md)*
Typical search syntax:
uvx search-species <engine> "<query>" [max_cands] -o <output_dir>
> Output: Prints the retrieved species data summary and the file path where each candidate's JSON is saved (e.g., SpeciesCandidate(...) written -> ./cache/xyz.json).
Typical render syntax:
uvx --from search-species render-species <candidate_files...> -o <output_dir>
> Output: Prints the file path of the successfully generated image card (e.g., Successfully rendered -> ./gallery/xyz.png).
PubChem (Standard database lookups):
uvx search-species pubchem "benzene" 5 -o ./results
OPSIN (Theoretical molecules & strict IUPAC):
uvx search-species opsin "2-acetyloxybenzoic acid"
Wikidata (Multilingual & common/trade names):
uvx search-species wikidata "Аспирин"
uvx search-species wikidata "TNT"
When using this toolkit for users, ensure you cross-check these points with the Core Workflow:
pubchem fails on a systematic name, fallback to opsin.<query> in quotes.reference/backends.mdCreate beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
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Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Take jinzhezenggroup/search-species from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference uvx.
Without those the skill loads but fails at the first command.