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Look up genes, sequences, protein structures, expression patterns, and disease associations across more than 20 bioinformatics resources using command-line tools or Python. Useful for interactive exploration, with results that can be saved for further analysis.

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• Looking up gene details and sequences
• Exploring protein structures and residue annotations
• Comparing tissue expression and disease associations

Plan protein characterization experiments with Adaptyv's cloud laboratory, estimate costs, submit sequences, track progress, and retrieve measured results. Supports binding, thermal stability, expression, fluorescence, and enzyme activity workflows through the API and Python SDK.

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• Plan binding screens for candidate protein sequences
• Estimate experiment costs before submission
• Track laboratory progress and retrieve results

Automate lab data tasks in Benchling using its Python SDK and REST API. Import and export sequences, inspect sample inventory, and work with electronic lab notebooks and workflow tasks while checking schemas, permissions, and operation results.

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• Importing DNA sequences from FASTA files
• Auditing sample inventory at a storage location
• Exporting sequences for a specific schema to CSV

Plan campaign messages around what customers already know about a problem, available solutions, and a product. Use audience research to assign an awareness stage, then choose suitable language, supporting evidence, and a sequence of messages.

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• Identify audience awareness before writing campaign copy
• Adapt proposal language to customer knowledge
• Plan a sequence from education to product comparison

Analyze a custom protocol in a CTF sandbox and reproduce an accepted exchange. Recover message boundaries, checksums, and session state, then build a small replay program that preserves the required message order.

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• Recover message boundaries in an unknown protocol
• Reconstruct handshake steps and session state
• Build a replay program for a captured exchange

Analyze WebSocket and SSE realtime connections in CTF sandboxes. Trace connection setup, authentication, subscriptions, and message sequences to explain changes in displayed or stored state and identify the smallest sequence that reproduces them.

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• Inspecting connection setup and authentication data
• Decoding realtime messages and subscription flow
• Tracing reconnect behavior and message order

Prepare datasets for language model training by formatting examples, checking conversation templates, and packing examples into training sequences. Document data sources, synthetic data ratios, and validation results in a dataset card before starting a run.

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• Convert raw examples into training-ready JSONL
• Check conversation templates and assistant-only training targets
• Review example boundaries after sequence packing

Build a shared incident timeline in Timesketch from endpoint, server, and cloud logs. Search events, add tags and investigator notes, reconstruct the attack sequence, and organize findings into a story for incident reporting.

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• Reconstructing the sequence of an incident
• Reviewing evidence with multiple analysts
• Combining Plaso output and other logs

Build and evaluate Mamba models for long sequences using state-space models, which summarize past inputs in an internal state. Covers setup, pretrained text generation, differences between Mamba-1 and Mamba-2, and speed comparisons with Transformers.

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• Generate text with pretrained Mamba models
• Compare Mamba-1 and Mamba-2 configurations
• Benchmark generation speed against Transformers

Integrate Flash Attention into transformer models to reduce processing time and GPU memory use for long sequences. Covers PyTorch integration, advanced attention options, and benchmarks that compare speed, memory use, and output accuracy.

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• Speeding up transformer training on long sequences
• Reducing GPU memory use during attention
• Adding Flash Attention to a PyTorch model

Build a PowerPoint presentation with Morph transitions, which smoothly transform shared shapes between slides. Plan how objects move, resize, rotate, appear, and exit across a slide sequence, then deliver a single .pptx file.

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• Shrinking and moving a cover title onto the next slide
• Creating a continuous background across a slide sequence
• Explaining changing values with animated rectangle bars

Document a technical decision in an architecture decision record, or ADR. Capture its context, alternatives, and consequences, assign a record number, and distinguish a proposed decision from an accepted one so dependent work reflects its actual status.

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• Recording the reasons behind a technical choice
• Documenting alternatives and consequences of a design decision
• Creating numbered records alongside existing architecture decisions

Build coordinated animation sequences with GSAP timelines. Set when each movement starts, overlap effects, name key moments, combine smaller sequences, and control playback, including pause, reverse, restart, and jumps to a specific point.

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• Animating several elements in a planned order
• Overlapping effects at precise times
• Organizing animation sections with labels

Implement Mamba, a model architecture that processes sequences through an internal state with computation scaling linearly with input length. Covers pretrained text generation, Mamba-1 and Mamba-2 configuration, speed comparisons with Transformers, and GPU memory troubleshooting.

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• Explore models for long sequences or streaming applications
• Generate text with pretrained Mamba models
• Compare Mamba-1 and Mamba-2 configurations

Optimize transformer attention, the calculation that relates tokens to one another, using Flash Attention. The skill guides PyTorch integration, GPU memory reduction, performance measurement, and output comparisons for training or inference with long sequences.

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• Reducing GPU memory use with long sequences
• Integrating Flash Attention into PyTorch models
• Comparing runtime and outputs before and after changes

Turn plain-language descriptions or Mermaid diagrams into interactive, standalone HTML diagrams of systems, workflows, API exchanges, data flows, and state changes. Validate layouts, explore relationships, switch themes, and export diagrams as images or video.

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• Explain system components and their relationships
• Visualize workflows and approval steps
• Map API calls and data pipelines

Look up existing predictions and protein information in the AlphaFold Protein Structure Database. Retrieve concise structure metadata, UniProt summaries, sequence summaries, and annotations, with an option to save the full response for later inspection.

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• Look up an existing protein structure prediction
• Check a UniProt summary
• Review sequence summaries and annotations

Turn descriptions or code analysis into Mermaid diagrams for workflows, system architecture, and database relationships. Check diagram syntax and export SVG, PNG, or text-based ASCII output, with themes and batch rendering options.

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• Visualizing system architecture
• Documenting API request sequences
• Drawing database relationships

Plan social selling on LinkedIn through profile improvements, relevant posts, personalized direct messages, and follow-ups. Build a clear path from audience engagement to sales conversations, with metrics to track which activities generate meetings.

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• Improving a LinkedIn profile for sales
• Drafting personalized direct message sequences
• Turning post engagement into sales meetings

Plan personalized sales emails to prospects you have not contacted before. This skill covers prospect selection, contact research, email drafts, follow-up sequences, inbox delivery, and reply handling, with guidance on tools and campaign improvements.

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• Drafting personalized sales emails for new prospects
• Planning a sequence of emails and follow-ups
• Investigating low reply rates or spam placement

Design amino acid sequences from a protein backbone using SolubleMPNN, a model trained on soluble protein structures. Generate candidates with a solubility bias for redesigning aggregation-prone proteins or preparing an E. coli expression screen.

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• Redesign protein candidates that aggregate
• Adapt membrane-adjacent folds for soluble expression
• Generate candidates for an E. coli expression screen

Predict patterns of gene expression and other genomic measurements from DNA sequences with Borzoi. Compare reference and altered sequences to estimate regulatory effects, generate predicted coverage tracks, and prioritize variants in regions that do not encode proteins.

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• Comparing predicted effects before and after a DNA variant
• Generating predicted coverage tracks for a genomic region
• Prioritizing variants in non-coding regions

Analyze biological data in Python, from DNA, RNA, and protein sequences to evolutionary trees and microbial communities. Read and convert files, compare diversity within and between samples, and test differences between groups.

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• Processing DNA, RNA, and protein sequences
• Building and comparing evolutionary trees
• Comparing microbial community diversity

Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.

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