Results for “functional”

End-to-end shotgun metagenomics workflow from FASTQ to taxonomic and functional profiles, orchestrating controls/host depletion, Kraken2+Bracken classification, MetaPhlAn marker profiling, and HUMAnN functional profiling. Covers the controls-first ordering, why Kraken2 read counts are not abundances and MetaPhlAn cell fractions do not equal Bracken read fractions, and the consistent-pipeline framing. Use when profiling shotgun metagenomic samples end to end, or chaining classification, abundance, and function. For resistome see metagenomics/amr-detection; for strains see metagenomics/strain-tracking; for assembly see genome-assembly/metagenome-assembly.

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Estimate SNP heritability and partition it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML, GCTA-GREML, graphREML, and Popcorn cross-population genetic correlation. Use when computing total h2_SNP from summary stats, partitioning heritability across functional categories, prioritizing trait-relevant tissues or cell types from ENCODE/Roadmap chromatin marks, reconciling LDSC vs LDAK enrichment estimates, computing local heritability with HESS, estimating genetic correlation between traits, or producing publication-grade enrichment with calibrated sensitivity to model assumptions.

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Uncorrelated Evaluator — 4軸ルーブリック専門エージェント（functionality-reviewer・code-reviewer・design-reviewer・originality-reviewer）と security-reviewer を5並列実行し、成果物を多面的に独立評価します。PASS / NEEDS WORK / BLOCKED 判定を返します。Self-leniency 防止のため、実装エージェントのコンテキストを引き継がない新規エージェントとして起動します。「レビューして」「評価して」「実装を確認して」などのリクエストで起動します。

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Design traceable functional test conditions across positive, negative, boundary, and error behavior with observable expectations.

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Estimate SNP heritability and partition it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML, GCTA-GREML, graphREML, and Popcorn cross-population genetic correlation. Use when computing total h2_SNP from summary stats, partitioning heritability across functional categories, prioritizing trait-relevant tissues or cell types from ENCODE/Roadmap chromatin marks, reconciling LDSC vs LDAK enrichment estimates, computing local heritability with HESS, estimating genetic correlation between traits, or producing publication-grade enrichment with calibrated sensitivity to model assumptions.

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Clarifies the purpose, preferences, and constraints of a new feature or project through conversation. When useful, it offers mockups or temporary prototypes, then captures an agreed description or written design before implementation begins.

• Clarifying the purpose of a new feature
• Organizing ideas for a talk or business
• Comparing screen or room layouts visually

Plan a consistent visual direction for music videos and short edits in angelcore, cloud-trance, and hyperpop styles. Define color, lighting, camera movement, and beat-synced cuts, then coordinate footage generation and editing through companion skills.

• Plan the visual direction of a music video
• Give AI-generated supporting footage a consistent look
• Design cuts that follow the song's beat

Research existing solutions before implementing a feature. Search project code, package registries, agent tools, and GitHub, then compare functionality, maintenance, licensing, and dependencies to decide whether to adopt, extend, combine, or build.

• Researching existing solutions before adding a feature
• Comparing packages before adding a dependency
• Finding tools for an external integration

Develop applications through separate planning, building, and evaluation agents. The workflow tests the running app, scores its design and functionality, and feeds specific issues back into repeated development cycles with configurable quality thresholds and iteration limits.

• Turning a brief idea into an application specification
• Refining frontend design through separate evaluation
• Testing and improving full-stack application features

Explore a web app in the browser to find functional, visual, and usability issues. The skill organizes screenshots, console errors, and reproduction steps into a Markdown bug report, with findings grouped by severity and category.

• Explore key user flows before release
• Check forms with valid, invalid, and empty input
• Document layout issues and JavaScript errors

Use a sample bundled skill to try the skills registry, the mechanism for making bundled skills available. Its invocation command provides a basic test case for checking the bundled skills feature.

• Trying a bundled skill command
• Checking bundled skills registry behavior
• Learning from a minimal skill sample

Review HTML pages, presentations, or prototypes across five design dimensions. Receive evidence-backed scores, a radar chart, and practical lists of what to keep, fix, or improve quickly, all packaged in a single self-contained HTML report.

• Reviewing a landing page before delivery
• Checking the readability and navigation of an HTML presentation
• Comparing two versions of a design

Create an FAQ page with expandable answers, live text search, and category filters. The skill organizes realistic questions for a product or service into a single HTML file with a contact section.

• Creating a help page for a SaaS product
• Organizing billing and account questions
• Building a searchable online store FAQ

Refactor claude-flow into an extension of agentic-flow@alpha to reduce duplicate implementations. Plan adapter layers, migrate agent and task management, and connect learning, shared memory, and tools while checking compatibility with existing functionality.

• Consolidate duplicate agent and task management code
• Design an adapter that preserves existing APIs
• Integrate learning, shared memory, and MCP tools

Find installable agent skills for a task you want help with. Search using relevant keywords, explain matching options with installation commands and detail links, and install a chosen skill through the provided script when requested.

• Finding skills for a specific task
• Exploring skills for a new area of work
• Checking what a skill does and how to install it

Refactor claude-flow into an extension of agentic-flow@alpha to reduce duplicate implementations. Plan adapter layers, migrate agent and task management, and connect learning, shared memory, and tools while checking compatibility with existing functionality.

• Consolidate duplicate agent and task management code
• Design an adapter that preserves existing APIs
• Integrate learning, shared memory, and MCP tools

Test local web applications with Python scripts using Playwright, a browser automation tool. Verify interface behavior, investigate problems, capture screenshots, and inspect browser logs, with a helper that manages one or more application servers.

• Verify buttons, links, and form behavior
• Investigate problems in dynamic web interfaces
• Capture screenshots of local applications

Review websites for content accidentally hidden by ad blockers. Identify problematic HTML class names and IDs, test affected pages with uBlock Origin, and suggest specific names that preserve the visibility and function of notices, banners, and consent controls.

• Investigating notices hidden by ad blockers
• Checking cookie consent controls for accidental hiding
• Reviewing HTML class names and IDs for blocking patterns

Retrieve and combine protein annotations, biological pathways, and chemical identifiers from services such as UniProt, KEGG, and UniChem using Python. Supports cross-database lookups and batch identifier conversion while preserving multiple matches and failed requests.

• Collect protein sequences and functional annotations
• Retrieve pathway information for genes
• Match compound identifiers across databases

Find agent skills for a specific task, compare candidates using their capabilities, sources, and installation history, and install a selected skill into Cherry after the user has expressed an intent to install it.

• Finding a skill for a specific task
• Comparing skill sources and installation history
• Installing a selected skill into Cherry

Use Python to analyze astronomical data, convert celestial coordinates, units, and times, and read or write FITS astronomy files. It also guides catalog matching and calculations of cosmic distances and ages using cosmological models.

• Converting celestial coordinates for an observing location
• Reading FITS images and inspecting their headers
• Matching objects across astronomical catalogs

Turn Airflow Improvement Proposals into practical guides checked against current code, or proposed user stories for design review before implementation. Organize use cases, distinguish verified examples from speculative code, and capture specific design questions.

• Create implementation-backed guides for an Airflow proposal
• Explore user stories before a feature is implemented
• Separate implemented features from proposed functionality

Build decentralized finance contracts from Solidity templates for staking and token swaps. Examples cover reward distribution, adding and removing pooled tokens, and swap calculations, with additional patterns for governance and flash loans.

• Build staking contracts that distribute rewards
• Implement token swaps using pooled assets
• Create governance token systems

Simplify Java methods and constructors by removing unused or redundant parameters. The skill adjusts definitions and internal calls, preserves existing functionality, and returns complete Java 17 code with comments explaining each removed parameter.

• Remove unused parameters from Java methods
• Simplify constructor parameter lists
• Review parameters whose values are available elsewhere