single-cell-rna-qc
Assesses and filters single-cell RNA-seq data in .h5ad or .h5 files using scverse best practices. Uses MAD-based filtering and comprehensive visualizations to identify low-quality cells and evaluate data quality.
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Find your next superpower If you are an agent, refer to our llms.txt for full access.Assesses and filters single-cell RNA-seq data in .h5ad or .h5 files using scverse best practices. Uses MAD-based filtering and comprehensive visualizations to identify low-quality cells and evaluate data quality.
Researches a company's product and ideal customer profile, discovers target companies, and evaluates their fit. Uses a planning, research, and synthesis process to produce scored reports and CSV output with adjustable research depth.
Apply Team Topologies to team boundaries, reorganizations, and internal platform design. Covers four team types, three interaction modes, the inverse Conway maneuver, and fracture planes.
Provides a framework for competitor research, peer comparisons, market maps, and strategic synthesis. Supports competitive landscape decks, market positioning assessments, strategic reviews, and investment memo presentations.
Creates advertising visuals and copy for Meta, Google Display, and LinkedIn. Includes a hero image and crops optimized for each platform.
Drafts or revises a personal -mode skill using create-skill and unslop. Can draw fresh evidence from recent transcripts to help agents follow the user's working preferences.
Coordinates conversion, material and physics assignment, SimReady conformance, validation, and optional packaging. Deploys or verifies Content Agents services when property assignment is enabled and routes individual stages through nested references.
Creates blog schema markup using Article or BlogPosting, Person, Organization, BreadcrumbList, ImageObject, and optional FAQPage types. Validates against Google requirements and flags deprecated types.
Queries and investigates detected DAVIS problems, correlating them with other telemetry. Assesses root causes, affected users and services, blast radius, problem history, and recurring trends.
Provides four narrative patterns for design work: protagonist-arc, choreography, situation/complication/resolution, and what-is/what-could-be. Applies them to journeys, briefs, blueprints, and presentations while preserving evidence and avoiding manufactured tension or manipulative persuasion.
Searches, filters, parses, and correlates log data. Calculates error rates and entry counts, identifies frequent error messages, and analyzes patterns and trends over time.
Takes a branch through multi-axis subagent review, finding verification, fixes, and ci:check. Creates checkpoint commits and updates the pull request for the maintainer's final review.
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