Researchers

Design and orchestrate multi-agent AI systems — define agent roles, communication protocols, tool use patterns, and failure recovery strategies.

AWS Bedrock AgentCore skill for deploying, managing, and scaling agent infrastructure across Gateway, Runtime, Memory, Identity, and related services.

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.

This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".

Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.

Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.

Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.

Deep competitor analysis with feature matrices, SWOT frameworks, and positioning maps — understand where you stand and where to move next.

A Composio skill for turning research inputs into a stronger writing brief or content draft foundation.

Answer data questions -- from quick lookups to full analyses. Use when looking up a single metric, investigating what's driving a trend or drop, comparing segments over time, or preparing a formal data report for stakeholders.

Build an interactive HTML dashboard with charts, filters, and tables. Use when creating an executive overview with KPI cards, turning query results into a shareable self-contained report, building a team monitoring snapshot, or needing multiple charts with filters in one browser-openable file.

Create publication-quality visualizations with Python. Use when turning query results or a DataFrame into a chart, selecting the right chart type for a trend or comparison, generating a plot for a report or presentation, or needing an interactive chart with hover and zoom.

Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts.

Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.

Profile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.

Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.

Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results.

QA an analysis before sharing -- methodology, accuracy, and bias checks. Use when reviewing an analysis before a stakeholder presentation, spot-checking calculations and aggregation logic, verifying a SQL query's results look right, or assessing whether conclusions are actually supported by the data.

Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc.

Run a WCAG 2.1 AA accessibility audit on a design or page. Trigger with "audit accessibility", "check a11y", "is this accessible?", or when reviewing a design for color contrast, keyboard navigation, touch target size, or screen reader behavior before handoff.

Get structured design feedback on usability, hierarchy, and consistency. Trigger with "review this design", "critique this mockup", "what do you think of this screen?", or when sharing a Figma link or screenshot for feedback at any stage from exploration to final polish.

Generate developer handoff specs from a design. Use when a design is ready for engineering and needs a spec sheet covering layout, design tokens, component props, interaction states, responsive breakpoints, edge cases, and animation details.

Audit, document, or extend your design system. Use when checking for naming inconsistencies or hardcoded values across components, writing documentation for a component's variants, states, and accessibility notes, or designing a new pattern that fits the existing system.

Synthesize user research into themes, insights, and recommendations. Use when you have interview transcripts, survey results, usability test notes, support tickets, or NPS responses that need to be distilled into patterns, user segments, and prioritized next steps.

Plan, conduct, and synthesize user research. Trigger with "user research plan", "interview guide", "usability test", "survey design", "research questions", or when the user needs help with any aspect of understanding their users through research.

Write or review UX copy — microcopy, error messages, empty states, CTAs. Trigger with "write copy for", "what should this button say?", "review this error message", or when naming a CTA, wording a confirmation dialog, filling an empty state, or writing onboarding text.

Anthropic's coauthoring skill for shaping shared documents, refining drafts, and collaborating on long-form writing.

Anthropic's document-processing skill for creating, editing, and analyzing Microsoft Word files.

Generate a daily or weekly digest of activity across all connected sources. Use when catching up after time away, starting the day and wanting a summary of mentions and action items, or reviewing a week's decisions and document updates grouped by project.

Combines search results from multiple sources into coherent, deduplicated answers with source attribution. Handles confidence scoring based on freshness and authority, and summarizes large result sets effectively.

Search across all connected sources in one query. Trigger with "find that doc about...", "what did we decide on...", "where was the conversation about...", or when looking for a decision, document, or discussion that could live in chat, email, cloud storage, or a project tracker.

Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.

Manages connected MCP sources for enterprise search. Detects available sources, guides users to connect new ones, handles source priority ordering, and manages rate limiting awareness.

Track and organize upcoming catalysts, earnings dates, and market-moving events for equity research coverage.

Analyze quarterly earnings results against estimates, dissect key drivers, and summarize implications for your thesis.

Generate a structured earnings preview note with consensus estimates, key watchpoints, and scenario analysis ahead of results.

Generate and screen new investment ideas using structured frameworks for identifying mispriced securities.

Build a comprehensive initiating coverage note with investment thesis, valuation, risk factors, and price target.

Update financial models with new data, revise estimates, and document changes to key assumptions and price targets.

Produce a structured morning research note summarizing overnight developments, market moves, and key items to watch.

Write a comprehensive sector overview covering industry dynamics, competitive landscape, valuation, and key themes.

Track and monitor investment thesis milestones, update conviction scores, and flag when thesis assumptions are being tested.

Design testable product hypotheses with correct sample sizing, success metrics, and guardrail metrics to run valid product experiments.

A Composio community skill for organizing files, spotting duplication, and improving folder structure.

Build an integrated income statement, balance sheet, and cash flow model with proper linkages and driver-based forecasting.

Audit financial spreadsheets for formula errors, broken links, hardcoded values, and structural inconsistencies.

Clean and standardize raw financial data — fix formatting, remove duplicates, normalize units, and prepare for analysis.

Map the competitive landscape for a company or sector, identifying key players, positioning, and market share dynamics.

Build a comparable company analysis with standardized financial metrics, trading multiples, and peer group benchmarking.

Build a discounted cash flow model with scenario analysis, sensitivity tables, and WACC derivation.

Refresh and update an existing financial presentation deck with new data, revised charts, and updated commentary.

Review investment banking presentation decks for accuracy, consistency, formatting standards, and completeness.

Build a leveraged buyout model with debt schedule, returns analysis, and sensitivity tables for private equity transactions.

Create structured PowerPoint templates for financial presentations with consistent formatting, master slides, and data placeholders.

Create new financial analysis SKILL.md files by extracting workflows from existing processes and formatting them as reusable skills.

DCF valuation, budgeting, forecasting, and SaaS metrics analysis — financial modeling and analysis from a professional analyst perspective.

Build a structured buyer list for M&A processes, categorizing strategic and financial buyers by fit, capacity, and likelihood.

Build a Confidential Information Memorandum with structured sections covering business overview, financials, and investment highlights.

Track live M&A and financing deal processes, manage timelines, counterparty lists, and milestone documentation.

Compile and format comprehensive financial data packs with historical financials, KPIs, and management-ready exhibits.

Build an M&A merger model with accretion/dilution analysis, synergy modeling, and pro forma financial projections.

Create investment banking pitch decks with credentials, situation analysis, strategic alternatives, and process recommendations.

Draft M&A process letters with bid instructions, data room access details, NDA requirements, and timeline guidance.

Generate concise one-page company strip profiles with financial summary, valuation, and key investment metrics.

Write an anonymous M&A teaser document highlighting investment highlights and financial profile without disclosing company identity.

A Composio community skill for pulling LangSmith traces into Claude workflows for debugging and inspection.

A Composio skill for gathering and organizing prospect or company research into a usable outreach brief.

Analyze bond futures basis relationships, cheapest-to-deliver dynamics, and carry trade opportunities in fixed income futures markets.

Identify relative value opportunities across the yield curve, sectors, and credit quality tiers in fixed income markets.

Conduct equity research analysis using LSEG data infrastructure, covering valuation, fundamentals, and consensus tracking.

Analyze fixed income portfolios for duration, credit exposure, yield, and risk-adjusted performance using LSEG data.

Identify and analyze foreign exchange carry trade opportunities, modeling interest rate differentials, volatility, and risk-adjusted returns.

Monitor macro rates environment across global markets, tracking central bank policy, yield curves, and inflation expectations.

Analyze options volatility surfaces, term structure, and skew across asset classes to identify mispricings and trading opportunities.

Develop interest rate swap curve strategies, analyzing spread relationships, basis dynamics, and relative value across tenors.

A Composio skill for extracting the real takeaways, decisions, and insights from meeting content.

Anthropic's official PDF skill for reading, extracting, and working with PDF-based documents.

Screen incoming deal opportunities against investment criteria, producing structured assessments of fit, size, and return potential.

Build and maintain deal sourcing pipelines, identify target companies, and track relationship development with intermediaries.

Prepare structured question sets and talking points for management meetings and expert calls during due diligence.

Generate comprehensive due diligence checklists covering financial, legal, operational, and commercial workstreams for PE transactions.

Write investment committee memos with thesis, diligence findings, financial analysis, risk factors, and return expectations.

Assess portfolio company readiness for AI adoption across data infrastructure, use cases, and implementation capability.

Monitor portfolio company performance against plan, tracking KPIs, budget variance, and value creation initiatives.

Analyze and model investment returns including IRR, MOIC, DPI, and TVPI across different exit scenarios and timelines.

Analyze unit economics for portfolio companies, modeling CAC, LTV, payback periods, and contribution margins.

Build structured value creation plans with strategic initiatives, operational KPIs, and milestone tracking for portfolio companies.

Define KPIs, build product dashboards, set up funnel analysis, and translate data into product decisions — metrics that actually drive the product forward.

Create a competitive analysis brief for one or more competitors or a feature area. Use when informing product strategy or feature prioritization, building sales battle cards, prepping board or investor materials, or deciding where to differentiate vs. achieve parity.

Review and analyze product metrics with trend analysis and actionable insights. Use when running a weekly, monthly, or quarterly metrics review, investigating a sudden spike or drop, comparing performance against targets, or turning raw numbers into a scorecard with recommended actions.

Update, create, or reprioritize your product roadmap. Use when adding a new initiative and deciding what moves to make room, shifting priorities after new information comes in, moving timelines due to a dependency slip, or building a Now/Next/Later view from scratch.

Plan a sprint — scope work, estimate capacity, set goals, and draft a sprint plan. Use when kicking off a new sprint, sizing a backlog against team availability (accounting for PTO and meetings), deciding what's P0 vs. stretch, or handling carryover from the last sprint.

Generate a stakeholder update tailored to audience and cadence. Use when writing a weekly or monthly status for leadership, announcing a launch, escalating a risk or blocker, or translating the same progress into exec-brief, engineering-detail, or customer-facing versions.

Synthesize user research from interviews, surveys, and feedback into structured insights. Use when you have a pile of interview notes, survey responses, or support tickets to make sense of, need to extract themes and rank findings by frequency and impact, or want to turn raw feedback into roadmap recommendations.

Write a feature spec or PRD from a problem statement or feature idea. Use when turning a vague idea or user request into a structured document, scoping a feature with goals and non-goals, defining success metrics and acceptance criteria, or breaking a big ask into a phased spec.

Design and build Retrieval-Augmented Generation systems — chunking strategies, embedding selection, vector store setup, and query pipeline optimization.

Object detection, image segmentation, visual AI model implementation, and computer vision pipeline design from a senior engineer perspective.

ETL/ELT pipeline design, data warehouse architecture, dbt transformations, and data infrastructure at scale from a senior data engineer.

Data analysis, statistical modeling, ML experiment design, and insights generation — a senior data scientist perspective on your data problems.

Machine learning model implementation, training pipelines, evaluation frameworks, and MLOps — production ML engineering from an expert perspective.

LLM prompt design, chain-of-thought optimization, few-shot example selection, and systematic prompt testing — get the most out of any AI model.

Anthropic's official meta-skill for designing and packaging new skills more systematically.

Generate earnings preview analysis using S&P Global data, covering consensus estimates, historical beats, and sentiment indicators.

Compile and analyze funding round data from S&P Global, tracking venture capital activity, deal sizes, and sector trends.

Generate concise company tear sheets using S&P Global data with key financials, ownership, credit ratings, and market data.

A Composio community skill for downloading videos for offline use, editing, or analysis workflows.

Anthropic's spreadsheet skill for working with Excel files, formulas, data transformations, and chart-friendly workflows.