Topic: mcp
13,395 skills in this topic.
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networkx
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
beita6969/ScienceClaw 571
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arxiv-search
Search arXiv for preprints in physics, math, CS, quantitative biology, quantitative finance, statistics, electrical engineering, economics. Use when: (1) finding preprints by topic, (2) searching by author, (3) browsing arXiv categories, (4) getting paper metadata/abstracts. NOT for: published journal articles (use crossref-search), biomedical (use pubmed-search).
beita6969/ScienceClaw 571
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lobster
beita6969/ScienceClaw 571
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latex-writing
Write and format LaTeX documents for academic journals. Use when: user asks to write LaTeX code, format papers for specific journals (Nature/Science/IEEE/ACM), create equations, tables, or BibTeX entries. NOT for: non-LaTeX writing (use paper-writing), data analysis, or literature search.
beita6969/ScienceClaw 571
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lit-synthesizer
Search PubMed and bioRxiv, summarise papers with LLM, build citation graphs, and generate literature review sections.
beita6969/ScienceClaw 571
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energy-systems
Analyzes energy systems including renewable energy resource assessment, power grid modeling, battery storage optimization, energy efficiency evaluation, and techno-economic analysis of energy technologies; trigger when users discuss solar, wind, grid integration, energy storage, or power system design.
beita6969/ScienceClaw 571
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prose
OpenProse VM skill pack. Activate on any `prose` command, .prose files, or OpenProse mentions; orchestrates multi-agent workflows.
beita6969/ScienceClaw 571
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wikidata-knowledge
Query Wikidata for structured knowledge using SPARQL and entity search. Use when: (1) finding structured facts about entities (people, places, organizations), (2) querying relationships between entities, (3) cross-referencing external identifiers (Wikipedia, VIAF, GND, ORCID), (4) building knowledge graphs from linked data. NOT for: full-text article content (use Wikipedia API), scientific literature (use semantic-scholar), geospatial data (use OpenStreetMap).
beita6969/ScienceClaw 571
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feishu-doc
Feishu document read/write operations. Activate when user mentions Feishu docs, cloud docs, or docx links.
beita6969/ScienceClaw 571
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math-computation
Mathematical computation including symbolic math, numerical methods, linear algebra, calculus, differential equations, optimization, and mathematical modeling. Uses Python with SymPy, NumPy, SciPy. Use when user asks to solve equations, compute integrals/derivatives, do matrix operations, solve ODEs/PDEs, optimize functions, or build mathematical models. Triggers on "solve equation", "integral", "derivative", "matrix", "eigenvalue", "differential equation", "optimization", "linear algebra", "symbolic math", "proof".
beita6969/ScienceClaw 571
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himalaya
CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).
beita6969/ScienceClaw 571
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data-extractor
Extract numerical data from scientific figure images using Claude vision + OpenCV calibration. Supports 26+ plot types including bar charts, scatter plots, forest plots, Kaplan-Meier curves, box plots, and more.
beita6969/ScienceClaw 571
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test-driven-development
Use when implementing any feature or bugfix, before writing implementation code
beita6969/ScienceClaw 571
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pubmed-database
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
beita6969/ScienceClaw 571
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post-processing
Extract, analyze, and visualize simulation output data. Use for field extraction, time series analysis, line profiles, statistical summaries, derived quantity computation, result comparison to references, and automated report generation from simulation results.
beita6969/ScienceClaw 571
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statsmodels
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.
beita6969/ScienceClaw 571
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citation-management
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
beita6969/ScienceClaw 571
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quantum-computing
Designs and analyzes quantum computing solutions including quantum circuit construction, algorithm implementation, error correction, and quantum advantage assessment; trigger when users discuss qubits, quantum gates, quantum algorithms, or quantum hardware.
beita6969/ScienceClaw 571
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data-stats-analysis
Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
beita6969/ScienceClaw 571
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diffs
Use the diffs tool to produce real, shareable diffs (viewer URL, file artifact, or both) instead of manual edit summaries.
beita6969/ScienceClaw 571
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research-lookup
Look up current research information using the Parallel Chat API (primary) or Perplexity sonar-pro-search (academic paper searches). Automatically routes queries to the best backend. Use for finding papers, gathering research data, and verifying scientific information.
beita6969/ScienceClaw 571
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computational-pathology-agent
COPYRIGHT NOTICE
beita6969/ScienceClaw 571
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statistical-testing
Advanced statistical testing including hypothesis testing, Bayesian analysis, survival analysis, time series, multivariate methods, and meta-analysis. Use when user needs specific statistical tests beyond basic EDA, power analysis, Bayesian inference, survival curves, time series forecasting, or meta-analysis. Triggers on "hypothesis test", "Bayesian", "survival analysis", "time series", "meta-analysis", "bootstrap", "permutation test", "mixed model", "structural equation".
beita6969/ScienceClaw 571
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bear-notes
Create, search, and manage Bear notes via grizzly CLI.
beita6969/ScienceClaw 571