DevOps & Infra

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Raman mineral mixture spectra analysis pipeline for unknown mixed-mineral spectra; preprocess noisy spectra once, iteratively match residual peaks against a reference spectral library, unmix components with NNLS, diagnose reliability, write reports, and optionally generate/evaluate synthetic benchmark cases with hidden ground truth.

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Call copy number variants with the GATK best-practices workflows — the somatic CNV pipeline (CollectReadCounts, DenoiseReadCounts with tangent normalization, ModelSegments, CallCopyRatioSegments) and the germline GATK-gCNV pipeline (DetermineGermlineContigPloidy, GermlineCNVCaller cohort/case mode, PostprocessGermlineCNVCalls). Covers panel-of-normals construction, AnnotateIntervals/FilterIntervals, allelic-count integration, and QS-based filtering. Use when integrating CNV calling into a GATK variant pipeline, calling rare germline CNVs from an exome cohort, deciding between the somatic and germline GATK workflows, or diagnosing why tangent normalization removed a real event or why gCNV output has low precision.

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Version Compatibility

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End-to-end Hi-C analysis workflow from FASTQ to compartments, TADs, and loops, with the decision of WHICH features the sequencing depth can support. Covers pairtools read-pair processing and library QC, cooler matrices, ICE balancing and distance-decay expected, A/B compartments, TAD boundaries, loop calling, and the routing of HiChIP/PLAC-seq/Capture Hi-C to protein-directed loop callers. Use when processing Hi-C data end to end, deciding a resolution for a given depth, or choosing between bulk-Hi-C and protein-directed loop calling.

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Orchestrates an end-to-end immune-repertoire pipeline from FASTQ to clonotypes, diversity, overlap, somatic hypermutation and lineages, routing on two forks. Use when deciding bulk vs single-cell (bulk amplicon/RNA-seq -> MiXCR analyze preset -> VDJtools/immunarch depth-normalized diversity and overlap -> figures; 10x paired VDJ -> MiXCR 10x preset or Cell Ranger -> scirpy gene-expression integration, chain QC, clonotype clusters); and TCR vs BCR (TCR -> exact CDR3-nt+V/J clonotypes, VDJtools diversity is fine; BCR -> somatic hypermutation makes exact clonotypes wrong -> Immcantation distToNearest/findThreshold clonal clustering, germline reconstruction, SHM, Dowser lineages); selecting the MiXCR 4.x preset by chemistry and activating its license; downsampling to equal depth before comparing diversity or overlap; and optionally annotating antigen specificity.

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End-to-end CLIP-seq pipeline from FASTQ to ENCODE-compliant binding sites, single-nucleotide crosslink maps, annotation, motifs, and (optionally) differential binding. Use when running the full Yeo lab eCLIP / iCLIP / iCLIP2 / iCLIP3 / irCLIP / PAR-CLIP analysis with SMInput control, protocol-specific UMI extraction, ENCODE STAR parameters, CLIPper or Skipper peak calling with stringent log2 FC and -log10 p thresholds, IDR rescue and self-consistency QC, and downstream motif registration with mCross or PEKA.

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End-to-end eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal (mandatory before DADA2 filterAndTrim), denoising with OBITools3 v3 (obi stats plural; DMS-based) or DADA2 ASVs (Callahan 2017), decontam combined method as screening-not-classifier (Davis 2018), tag-jumping (Schnell 2015) with a platform-dependent baseline (NovaSeq patterned flow cells ~10x MiSeq), Hill-number effective species counts with coverage-based rarefaction (Jost 2006; Chao & Jost 2012; doubling rule), beta-diversity decomposition with MANDATORY PERMANOVA + PERMDISP pair (Anderson & Walsh 2013), constrained ordination, and the read-counts-not-abundance critique (Lamb 2019). Use when processing eDNA samples for biodiversity assessment, deciding ASV vs OTU, configuring OBITools3 v3, interpreting decontam screening, or reporting community comparisons with the dispersion confound check.

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Download raw sequencing reads from NCBI SRA using sra-tools (prefetch, fasterq-dump, vdb-validate) or the ENA mirror. Use when pulling FASTQ for SRR/ERR/DRR accessions, deciding between SRA-direct, ENA mirror, or AWS/GCP cloud mirror (STRIDES), handling --include-technical for 10x and other single-cell records, validating with MD5/vdb-validate, navigating SRR/SRX/SRS/SRP/PRJNA hierarchy, or finding accessions via pysradb. Encodes SRA cloud-egress economics, the fasterq-dump uncompressed-scratch trap, and the --max-size default that silently truncates large prefetches.

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Orchestrates an end-to-end MeRIP-seq / m6A-seq analysis from raw FASTQ to differential m6A peak calls and metagene plots, chaining fastp adapter trimming, STAR splice-aware alignment (NO deduplication for non-UMI MeRIP), deepTools replicate-concordance + IP-enrichment QC, PreSeq saturation curves, exomePeak2 (transcript-aware, GC-bias-aware negative-binomial GLM) peak calling, optional MACS3 broad-peak cross-check, DRACH motif confirmation as a sanity check (NOT a per-peak filter), exomePeak2 differential calling via the four-BAM-vector interface (bam_ip + bam_input control; bam_treated_ip + bam_treated_input treatment), ChIPseeker annotation, and the canonical Guitar metagene with stop-codon enrichment as the biological QC anchor. Use when running a complete MeRIP analysis from raw reads, when chaining the constituent epitranscriptomics skills (merip-preprocessing -> m6a-peak-calling -> m6a-differential -> modification-visualization), or when wrapping the pipeline in Snakemake / Nextflow.

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Operates the QIIME2 framework as the glue for an amplicon analysis - the .qza/.qzv artifact model, semantic types (FeatureTable[Frequency], SampleData[PairedEndSequencesWithQuality], Phylogeny[Rooted], FeatureData[Taxonomy]), embedded provenance plus provenance replay, import (Casava/manifest/EMP/BIOM), export, the Metadata object, and the q2cli vs Artifact API interfaces. Covers why a .qza is data-plus-executable-history not a file, why export drops provenance, why a .qzv is terminal, why classifier .qza are version-pinned, and the 2026 distribution/rachis rename. Use when importing reads, choosing a manifest/Casava/EMP/BIOM path, reading or replaying provenance, exporting to BIOM/phyloseq, fixing semantic-type or Phred or sklearn-version errors, or orchestrating the pipeline. Denoising -> amplicon-processing; classifier/DB -> taxonomy-assignment; diversity metric/depth -> diversity-analysis; DA tool -> differential-abundance; PICRUSt2 -> functional-prediction; shotgun moshpit -> metagenomics.

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End-to-end Ribo-seq analysis from FASTQ through periodicity QC, P-site calibration, ORF detection, translation efficiency, and stalling. Use when orchestrating a full ribosome profiling pipeline and deciding harvest/dedup/alignment options and which downstream analyses the library can support.

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Calls germline SNPs and indels with Google DeepVariant, which reframes variant calling as CNN image classification over multi-channel pileup tensors. Covers platform-specific model selection (WGS, WES, PACBIO, ONT_R104, HYBRID_PACBIO_ILLUMINA), one-shot run_deepvariant vs the three-stage make_examples/call_variants/postprocess_variants pipeline, GPU acceleration of call_variants, DeepTrio for family/trio and de-novo calling, and joint genotyping of gVCFs with GLnexus (not GenotypeGVCFs). Use when deciding DeepVariant vs GATK vs DRAGEN, picking the right --model_type for a sequencing platform, avoiding post-hoc GATK hard filters or BQSR that degrade CNN calls, calling de-novo variants in a trio, merging a DeepVariant cohort, or weighing GIAB-trained benchmark accuracy before clinical deployment.

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End-to-end 16S/ITS amplicon workflow from demultiplexed FASTQ to a consensus differential-abundance result, orchestrating cutadapt primer removal, per-run DADA2 ASV inference (learnErrors/mergeSequenceTables/removeBimeraDenovo), region-matched taxonomy assignment, a SEPP/Greengenes2 tree, alpha/beta diversity at a declared sampling depth (phyloseq/vegan, adonis2 paired with betadisper), compositional DA as a consensus of >=2 tools (ALDEx2/ANCOM-BC2) on unrarefied counts, and optional PICRUSt2 functional prediction gated on NSTI. Covers the stage-ordering decisions (primers before truncation, per-run error model, rarefy for diversity not DA, predicted potential not activity) and defers each per-step choice to the six microbiome skills. Use when staging an amplicon study end to end or chaining ASV inference, taxonomy, diversity, and differential abundance. For shotgun reads see workflows/metagenomics-pipeline.

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standard operating procedure(SOP) agent team to processanalysis→procedure document→checklist→training materials→versionmanagementto Korean creation Full pipeline. 'SOP create it', 'standard operating procedurefrom writing', 'work procedurefrom', 'task ', 'operations procedure', 'procedure document writingplease do', 'checklist create it', 'work process document' etc. SOP writing before skill usage. existing process document procedure document·checklist·training materials writing degreeKRW. However, actual BPM whensystem building, workflow specialist development, ISO authentication company versus is outside this skill's scope.

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Full pipeline for building web scraping systems with agent team collaboration. Use this skill for requests like 'build a web scraper', 'develop a crawler', 'collect site data', 'web crawling system', 'build a scraper', 'data collection automation', 'site parsing', 'web data extraction', etc. Also supports target-analysis-only mode for specific site analysis. Note: real-time streaming data processing (Kafka/Flink), browser automation testing (Selenium testing), and website performance monitoring are outside the scope of this skill.

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Full pipeline for REST/GraphQL API design, documentation, mocking, and testing. An agent team collaborates to perform API architecture design, OpenAPI/GraphQL schema generation, developer documentation writing, and mock server and test design. Use this skill for any API design task including 'design an API', 'REST API', 'GraphQL API', 'API documentation', 'API schema', 'OpenAPI', 'Swagger', 'API testing', 'API mocking', 'endpoint design', etc. Also supports documentation and testing for existing APIs. Note: actual server implementation (Express, FastAPI, etc.), API Gateway deployment, and monitoring dashboard setup are outside the scope of this skill.

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Full pipeline where an agent team collaborates to generate data warehouse design, KPI definitions, visualizations, and automated reports for a BI dashboard. Use this skill for requests like 'build me a BI dashboard', 'dashboard design', 'define KPIs', 'executive reporting dashboard', 'data visualization design', 'report automation', 'data warehouse design', 'build a KPI tree', 'sales dashboard', 'performance metrics framework', and other BI dashboard construction tasks. Also supports visualization or report automation when existing data models or KPI lists are available. Note: direct manipulation of BI tools (Tableau/PowerBI/Looker), database instance creation, and real-time data pipeline operation are outside the scope of this skill.

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A grant/funding application full pipeline. An agent team collaborates to generate announcement analysis, business plan, budget, compliance verification, and submission checklist. Use this skill for requests like 'grant application', 'funding program business plan', 'government funding', 'grant proposal', 'write a business plan', 'budget preparation', 'funding program preparation', 'R&D project application', 'startup support program', 'small business support', and other grant/funding application needs. Also supports review of existing business plans. However, actual online system access and submission, supporting document issuance, and presentation coaching for reviewer panels are outside the scope of this skill.

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An internal audit report generation pipeline. An agent team collaborates to produce everything from audit scope design through checklists, findings, improvement recommendations, and tracking ledgers. Use this skill for 'create audit report', 'internal audit preparation', 'create audit checklist', 'organize audit findings', 'corrective action plan', 'audit tracking ledger', 'compliance audit', 'operational audit report', and similar internal audit topics. External financial audits, tax investigations, and litigation-related audits are out of scope.

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Full IP management pipeline for intellectual property portfolio management where an agent team collaborates to generate IP status analysis, patent/trademark/copyright mapping, renewal schedules, license strategies, and protection strategy reports. Use this skill for requests such as 'manage IP portfolio', 'patent portfolio analysis', 'trademark management', 'develop IP strategy', 'patent renewal schedule', 'license strategy', 'IP protection strategy', 'intellectual property status analysis', 'create a patent map', 'trade secret management', and other intellectual property management tasks. Also supports analysis of specific IP types (patents/trademarks/copyrights) or updating existing portfolios. However, actual patent application drafting (use patent-drafter skill), patent office electronic filing, legal opinion writing, and litigation representation are outside the scope of this skill.

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A full production pipeline where an agent team collaborates to create comics — from storyboarding through dialogue, image generation, and editing — covering 4-panel strips, short-form, and long-form (including webtoon). Use this skill for 'create a comic,' 'draw a 4-panel strip,' 'webtoon production,' 'comic storyboard,' 'comic strip,' 'comic scenario,' 'illustrated comic,' 'comic storyboard,' and all other comic creation tasks. Also supports image generation or editing specification when an existing scenario is provided. Note: actual image editing software (Photoshop, Clip Studio) operation, print production, and webtoon platform uploads are outside this skill's scope.

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Full pipeline for CI/CD pipeline design, build, monitoring, and optimization. An agent team collaborates to perform stage design, YAML configuration generation, security scan integration, and monitoring/alert design. Use this skill for any CI/CD task including 'create a CI/CD pipeline', 'GitHub Actions', 'GitLab CI', 'Jenkins pipeline', 'deployment automation', 'build pipeline', 'DevOps pipeline', 'auto deploy', 'CI setup', 'CD setup', etc. Also supports optimization and security hardening for existing pipelines. Note: actual infrastructure provisioning (AWS/GCP resource creation), server configuration, and cluster management are outside the scope of this skill.

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Full pipeline for automated code review. An agent team collaborates to systematically review 4 domains: style, security, performance, and architecture. Use this skill for any code review task including 'review this code', 'look at this code', 'code inspection', 'PR review', 'code quality analysis', 'security review', 'performance review', 'architecture review', 'code style check', etc. Also supports requests for specific domains only. Note: actual CI/CD integration, auto-fix, and Git commit/merge operations are outside the scope of this skill.

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A full Infrastructure as Code design and implementation pipeline. An agent team collaborates to perform Terraform/Pulumi-based infrastructure design, security policies, cost optimization, and drift detection. Use this skill for requests like 'design IaC', 'write Terraform code', 'create infrastructure code', 'Pulumi project design', 'cloud infrastructure design', 'infrastructure security design', 'infrastructure cost optimization', 'drift detection setup', and other IaC tasks. Also supports codifying existing infrastructure (import). Note: actual terraform apply execution, cloud console operations, and production deployment are outside the scope of this skill.

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data pipelineof count, transformation, -based, verification, monitoring inthisbefore teamthis to ·lower pipeline. 'data pipeline ', 'ETL pipeline ', 'data count automatic-ize', 'data lower pipeline', 'ELT ', ' pipeline', 'tree pipeline', 'Airflow DAG only', 'dbt model ', 'data verification ' etc. data pipeline · beforein this for. existing pipelineof verificationthis monitoringonly necessary inalso supported. , real-time tree (Flink/Spark Streaming) direct execution, infrastructure provisioning, database administrator(DBA) this of scope .

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A full ML pipeline where an agent team collaborates to perform data preparation, model design, training, evaluation, and deployment readiness. Use this skill for 'design an ML experiment', 'train a model', 'machine learning project', 'build a deep learning model', 'classification model', 'regression model', 'data preprocessing', 'model evaluation', 'hyperparameter tuning', 'MLOps setup', 'XGBoost model', 'PyTorch model', and other ML experiment tasks. Supports data-preprocessing-only or evaluation-only requests as well. Note: model serving infrastructure (SageMaker/Vertex AI) direct deployment, large-scale distributed training cluster management, and real-time inference service operation are outside this skill's scope.

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A full analysis pipeline where an agent team collaborates to perform exploratory data analysis (EDA), data cleaning, statistical analysis, visualization, and report writing. Use this skill for 'analyze this data', 'do EDA', 'exploratory analysis', 'statistical analysis', 'data visualization', 'write an analysis report', 'analyze CSV', 'extract data insights', 'data cleaning', 'outlier analysis', and other data analysis tasks. Note: real-time data streaming, ML model training/deployment, and BI dashboard server construction are outside this skill's scope.

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RFI/RFP response full pipeline. An agent team collaborates to generate requirements analysis, capability matching, technical proposal, pricing proposal, and differentiation strategy. Use this skill for requests like 'RFP response', 'write a proposal', 'RFP analysis', 'bid proposal', 'technical proposal', 'pricing proposal', 'public procurement bid', 'RFP response document', 'SI proposal', 'IT project bidding', and other RFP/RFI response needs. Also supports review of existing proposals. However, direct access to government procurement systems, real-time bid price retrieval, and electronic bidding participation are outside the scope of this skill.

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A full production pipeline where an agent team collaborates to generate podcast episode content — planning, research, scripting, show notes, and distribution strategy — all at once. Use this skill for requests like 'plan a podcast episode,' 'write an episode script,' 'podcast scriptwriting,' 'podcast show notes,' 'episode planning,' 'interview script,' 'podcast distribution,' 'audio content planning,' and other podcast production tasks. Also supports show note or distribution package creation when an existing script or research is provided. Note: actual audio recording/editing (Audacity, GarageBand), podcast hosting API integration, and RSS feed technical setup are outside this skill's scope.

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A full narrative pipeline where an agent team collaborates to design game story, quests, dialogue, and branching scenarios all at once. Use this skill for 'create a game scenario,' 'game story design,' 'quest design,' 'game dialogue writing,' 'branching scenarios,' 'world-building,' 'NPC dialogue,' 'game scenario branching,' 'interactive story,' and all other aspects of game narrative design. Also supports quest/dialogue/branch design when existing world-building or story is provided. Note: game programming, level design (terrain/maps), game balancing (numerical values), and UI/UX design are outside the scope of this skill.

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A full production pipeline where an agent team collaborates to design online courses all at once — curriculum, lesson plans, quizzes, and hands-on labs. Use this skill for 'create an online course,' 'design a curriculum,' 'write lesson plans,' 'course design,' 'syllabus,' 'learning course development,' 'curriculum development,' 'course design,' 'create lab assignments,' and all other course development tasks. Also supports lesson plan writing or quiz creation when an existing curriculum is provided. Note: actual LMS construction, video recording/editing, student management, and certificate issuance are outside this skill's scope.

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security auditof vulnerability , code security analysis, penetration test , improvement inthisbefore teamthis to countlower security audit pipeline. 'security audit', 'vulnerability ', 'security ', 'code security analysis', 'penetration test report', 'security vulnerability ', 'OWASP ', 'queue ', 'security improvement ', 'infrastructure security ' etc. security audit beforein this for. code analysisonly necessarylower improvement only necessary inalso supported. , actual network penetration execution, code analysis, SOC operations, real-time security monitoring this of scope .

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Text processing pipeline: an agent team collaborates to perform preprocessing, classification, entity/keyword extraction, sentiment analysis, summarization, structured data conversion, and report generation on bulk text. Use this skill for requests like 'analyze this text', 'text processing', 'classify documents', 'run sentiment analysis', 'extract keywords', 'named entity recognition', 'NER', 'text summarization', 'review analysis', 'survey text analysis', 'comment analysis', and other general text NLP tasks. Note: speech recognition (STT), machine translation, chatbot dialogue management, and LLM fine-tuning are outside the scope of this skill.

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Full migration pipeline where an agent team collaborates to perform source analysis, schema mapping, transformation script generation, validation query design, and rollback planning. Use this skill for requests like 'data migration', 'DB migration', 'data transfer', 'schema conversion', 'database migration plan', 'ETL scripts', 'data transition', 'DB migration validation', 'system cutover', etc. Note: real-time CDC streaming setup, cloud infrastructure provisioning, and application code migration are outside the scope of this skill.

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A foreign language learning full pipeline. An agent team collaborates to provide level testing, curriculum design, lesson generation, quizzes, and review management. Use this skill for requests like 'study English', 'learn Japanese', 'learn a foreign language', 'language learning', 'English grammar', 'conversation practice', 'level test', 'vocabulary memorization', 'self-study English', 'beginner Chinese', 'TOEIC preparation', 'English conversation', and other foreign language learning needs. Also supports learning specific skill areas only. However, real-time voice conversation (STT/TTS), native speaker matching, and taking official exams on behalf of the learner are outside the scope of this skill.

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A thesis writing support full pipeline. An agent team collaborates to perform topic selection, literature review, methodology design, writing, and proofreading. Use this skill for requests like 'help with my thesis', 'find a research topic', 'literature review', 'methodology design', 'write my thesis', 'proofread my thesis', 'dissertation', 'journal submission', 'research design', and other academic thesis writing needs. Existing manuscripts or reference lists can augment the relevant phase. However, actual data collection/analysis execution, statistical software operation, and journal submission system operation are outside the scope of this skill.