264 skills · sorted by relevance
Find commercial sources for chemical compounds — PubChem/ChEMBL identity resolution then vendor catalog search across ZINC, Enamine, eMolecules, Mcule. Compares pricing, availability, and identifies purchasable analogs when an exact compound is not in stock. Use for chemical procurement, virtual library curation, and 'where can I buy X' questions for synthesis planning.
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Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.
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Standardizes molecular structures using ChEMBL chembl_structure_pipeline and RDKit rdMolStandardize covering sanitization, salt/solvent stripping, neutralization, tautomer canonicalization, stereochemistry standardization, mixture handling, and isotope normalization. Explicitly compares ChEMBL pipeline, canSARchem, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.
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Standardizes molecular structures using ChEMBL chembl_structure_pipeline and RDKit rdMolStandardize covering sanitization, salt/solvent stripping, neutralization, tautomer canonicalization, stereochemistry standardization, mixture handling, and isotope normalization. Explicitly compares ChEMBL pipeline, canSARchem, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.
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Build reusable, composable, and maintainable React/Vue/Angular components following established design patterns like compound components, render props, custom hooks, and HOCs. Use when creating component libraries, implementing component composition, building reusable UI elements, designing prop APIs, managing component state patterns, implementing controlled vs uncontrolled components, creating compound components, using render props or children as functions, building custom hooks, or establishing component architecture standards.
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Standardizes molecular structures using ChEMBL chembl_structure_pipeline and RDKit rdMolStandardize covering sanitization, salt/solvent stripping, neutralization, tautomer canonicalization, stereochemistry standardization, mixture handling, and isotope normalization. Explicitly compares ChEMBL pipeline, canSARchem, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.
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Answer questions using Paperclip wiki pages and original sources, with citations for each claim. Identify missing information clearly and, with user approval, save useful comparisons or explanations as linked wiki pages for future reference.
Refactor React components with too many true-or-false options into reusable parts. Provides guidance on component composition, shared state, and flexible interfaces, with examples of good and problematic implementations and specific guidance for React 19.
Clean and compare tandem mass spectra, measurements used to study molecular fragments, with matchms. Standardize metadata, filter peaks, search reference libraries, and export ranked candidate matches with similarity scores and matched-peak counts.
Retrieve facts from named scientific, regulatory, economic, and other databases through documented APIs. Get results with recorded filters, retrieval dates, and record counts so another person can repeat the lookup and assess its completeness.
Retrieve and combine protein annotations, biological pathways, and chemical identifiers from services such as UniProt, KEGG, and UniChem using Python. Supports cross-database lookups and batch identifier conversion while preserving multiple matches and failed requests.
Turn documents into a growing Markdown wiki and a knowledge graph, a map of entities and their relationships. Preserve source text, update linked pages as new material arrives, and answer questions with supporting evidence.
Build a lasting Markdown knowledge base for project decisions, architecture, and session discoveries. Search pages by keywords and tags, use results to answer with citations, and check for outdated content, broken links, and structural problems.
Audit a site's SEO, plan related topic groups and internal links, and create page briefs and article drafts with metadata and structured data. Save findings and deliverables locally so later sessions can continue from previous work.
Design autonomous AI agents that break goals into tasks, use tools, and review their own work. Covers reasoning and action loops, separate planning and execution, and reliability measures such as cost limits, validation, and logging.
Refactor React components into reusable pieces with clearer interfaces. Provides patterns for replacing excessive boolean settings, sharing state through providers, and designing component libraries, with additional guidance for React 19 APIs.
Model up to three overlapping business risks and trace how their effects spread across teams. Compare three severity levels, identify early warning signals, and define preventive actions with costs, owners, and deadlines to support strategic decisions.
Address existing feedback on a GitHub pull request, a proposed code change. Evaluate comments against the code, apply valid fixes, and verify replies and thread resolution, with options for local handoff or resuming saved work.
Refine a working feature through browser feedback from the user. Collect observations through typed comments or live speech and drawing, apply focused usability fixes, and save the changes in local commits.
Test the pages affected by a branch or pull request in a browser. The skill checks rendered pages and key interactions, then reports passes, failures, skipped checks with reasons, and steps to reproduce problems.
Retune a collection of skills for a new model using archived runs and controlled comparisons. Establish normal measurement variation, register success criteria before editing, and make targeted changes until measured behavior meets the criteria or a specific limitation is reported.
Explain how something works, why it took its current form, or what happened during a period of work. Use supporting evidence, distinguish documented reasons from inference, and adapt the answer or document to its readers.
Create, edit, and review agent skills against a shared authoring standard. Clarify goals, completion conditions, and responsibilities, remove unsupported instructions, and validate changes according to their risk, with a report explaining what changed and why.
Draft announcements for a shipped feature, explaining what users can now do and why it matters. Produce copy-ready text tailored to channels such as X, LinkedIn, email, release notes, blogs, or demo scripts.