dask
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
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.
cosmic-database
Access COSMIC cancer mutation database. Query somatic mutations, Cancer Gene Census, mutational signatures, gene fusions, for cancer research and precision oncology. Requires authentication.
academic-paper-composer
Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.
cobrapy
Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.
clinvar-database
Query NCBI ClinVar for variant clinical significance. Search by gene/position, interpret pathogenicity classifications, access via E-utilities API or FTP, annotate VCFs, for genomic medicine.
neuropixels-analysis
Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.
neurokit2
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
clinpgx-database
Access ClinPGx pharmacogenomics data (successor to PharmGKB). Query gene-drug interactions, CPIC guidelines, allele functions, for precision medicine and genotype-guided dosing decisions.
clinicaltrials-database
Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.
clinical-reports
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.
clinical-decision-support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
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.
cirq
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
chembl-database
Query ChEMBL bioactive molecules and drug discovery data. Search compounds by structure/properties, retrieve bioactivity data (IC50, Ki), find inhibitors, perform SAR studies, for medicinal chemistry.
markitdown
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
brenda-database
Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.
bioservices
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
matlab
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
matchms
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.
nextjs-app-router
PostHog integration for Next.js App Router applications
list-templates
List available AI agent instruction templates from the repository. Use to discover what templates can be loaded.
load-template
Load an AI agent instruction template into the current project. Use when you need structured instructions for a specific role like technical planning.
add-remote-skill
This skill should be used when the user wants to add one or more skills from GitHub repositories to the kilo-marketplace. It handles parsing GitHub URLs, cloning skill directories, and updating SKILL.md frontmatter with source metadata.
running-dbt-commands
Formats and executes dbt CLI commands, selects the correct dbt executable, and structures command parameters. Use when running models, tests, builds, compiles, or show queries via dbt CLI. Use when unsure which dbt executable to use or how to format command parameters.
fetching-dbt-docs
Retrieves and searches dbt documentation pages in LLM-friendly markdown format. Use when fetching dbt documentation, looking up dbt features, or answering questions about dbt Cloud, dbt Core, or the dbt Semantic Layer.
configuring-dbt-mcp-server
Generates MCP server configuration JSON, resolves authentication setup, and validates server connectivity for dbt. Use when setting up, configuring, or troubleshooting the dbt MCP server for compatible MCP clients.
building-dbt-semantic-layer
Use when creating or modifying dbt Semantic Layer components — semantic models, metrics, dimensions, entities, measures, or time spines. Covers MetricFlow configuration, metric types (simple, derived, cumulative, ratio, conversion), and validation for both latest and legacy YAML specs.
answering-natural-language-questions-with-dbt
Writes and executes SQL queries against the data warehouse using dbt's Semantic Layer or ad-hoc SQL to answer business questions. Use when a user asks about analytics, metrics, KPIs, or data (e.g., "What were total sales last quarter?", "Show me top customers by revenue"). NOT for validating, testing, or building dbt models during development.
adding-dbt-unit-test
Creates unit test YAML definitions that mock upstream model inputs and validate expected outputs. Use when adding unit tests for a dbt model or practicing test-driven development (TDD) in dbt.
migrating-dbt-project-across-platforms
Use when migrating a dbt project from one data platform or data warehouse to another (e.g., Snowflake to Databricks, Databricks to Snowflake) using dbt Fusion's real-time compilation to identify and fix SQL dialect differences.
migrating-dbt-core-to-fusion
Classifies dbt-core to Fusion migration errors into actionable categories (auto-fixable, guided fixes, needs input, blocked). Use when a user needs help triaging migration errors to understand what they can fix vs what requires Fusion engine updates.
using-dbt-for-analytics-engineering
Builds and modifies dbt models, writes SQL transformations using ref() and source(), creates tests, and validates results with dbt show. Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing tests, or evaluating impact of changes.
troubleshooting-dbt-job-errors
Diagnoses dbt Cloud/platform job failures by analyzing run logs, querying the Admin API, reviewing git history, and investigating data issues. Use when a dbt Cloud/platform job fails and you need to diagnose the root cause, especially when error messages are unclear or when intermittent failures occur. Do not use for local dbt development errors.
discover-package-skills
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onboardjs-react
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birdmate
APM project for birdmate
datadog-operations
Comprehensive Datadog operations: query APM/logs/metrics/RUM/database, create monitors/dashboards/synthetics, manage incidents, trigger workflows, analyze costs and LLM usage. 73% platform coverage including service catalog, uptime monitoring, and frontend performance. Use for debugging, automation, incident response, and cost optimization.
create-pr
GitHub Pull Request を作成するときに使う。ユーザーが PR を作りたい、PR本文やタイトルのドラフトを差分から作りたい、既存の PR テンプレートに沿って内容を埋めたいと言ったときに適用する。実行時に新規ブランチや add/commit が必要な場合もこのスキル内で行う。カレントが main または release/* または epic/* のときは、新規ブランチを作る必要があるか必ずユーザーに聞く。それ以外は普段は質問せず、必要ならブランチ作成・コミット・プッシュしてから PR を作成する。ベースブランチは origin のリモートブランチから候補を推定してユーザー確認を取る。
create-commit
Gitの変更をステージしてコミットする。「コミットして」「コミットしたい」「変更をコミット」といったリクエストで使用。差分を分析し、whatとwhyを含む適切なコミットメッセージを自動生成する。
create-branch
現在の変更内容を確認し、適切なブランチ名を提案してブランチを作成するときに使う。ユーザーが「ブランチ作って」「作業用ブランチ切りたい」「変更に合わせてブランチ名を決めて」と言ったとき、または新規作業を始める前にブランチを作りたいときに適用する。git status / diff を確認し、プレフィックス規則（feat/fix/release/epic）に従ってブランチ名を提案し、ユーザー確認後に git checkout -b で作成する。
coderabbit-review
Use CodeRabbit CLI to receive external code review feedback and address identified issues. Invoke this skill when the user requests CodeRabbit review, or proactively after implementing significant code changes to get feedback and improve code quality.
anthropic-skill-creator
Create and iteratively improve Cursor Agent Skills using the Anthropic skill-creator workflow. Use when the user wants to create a skill from scratch, refine an existing skill with test prompts and feedback, or follow a structured draft→test→review→improve loop for skills.
karpathy-guidelines
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
web-verify
Analyze code changes, derive test scenarios, and verify them on a live deployment via browser automation. Use when user wants to verify changes work in the browser, test a deployment, or says /web-verify.
wrap
Pre-commit session analysis. Triages trivial vs substantive changes, checks commit scope, and for substantive sessions proposes docs/permissions/automations updates. Use when user is finishing work, about to commit, or says /wrap.
feature-dev
Develop features end-to-end from planning to PR. Use when user asks to implement feature, build functionality, or says /feature-dev.
voice-realtime
Real-time voice AI knowledge including STT and TTS providers, LiveKit Agents plugins, and voice pipeline patterns. Use when working with speech-to-text, text-to-speech, voice agents, LiveKit, or any voice-related infrastructure.
sleep-domain
Sleep science and Asleep sleep tracking knowledge. Use when working with sleep data, hypnograms, sleep stages, sleep insights, sleep metrics, or any sleepstar/agent-a/backend sleep-related code.
self-enhance
Framework for improving Claude configuration (skills, agents, commands). Use when analyzing work patterns, proposing new skills, identifying knowledge gaps, reviewing Claude setup, or when user asks to improve how Claude helps them.
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