Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
45.604 skill-uri din 2.205 depozite · actualizat acum 19 ore
45.604 skill-uri
- google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skillsDiscovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).OficialDateFără avertismente★ 21,6 K↓ —
- zarr-pythonK-Dense-AI/scientific-agent-skillsStores and queries chunked N-D scientific arrays with Zarr-Python 3, including codecs, sharding, S3/GCS storage, and NumPy/Dask/Xarray integration. Use for array layout, bounded I/O, format migration, or scientific metadata preservation.InginerieFără avertismente★ 54,5 K↓ —
- meeting-minutesgithub/awesome-copilotGenerate concise, actionable meeting minutes for internal meetings. Includes metadata, attendees, agenda, decisions, action items (owner + due date), and follow-up steps.AlteleFără avertismente★ 40,4 K↓ —
- modellixsickn33/agentic-awesome-skillsIntegrate the Modellix API/CLI for async AI image, video, and speech generation or transcription (model run --wait, task download).MediaFără avertismente★ 48,5 K↓ —Apare și în 1 alt depozit
- google-cloud-solution-agentic-ai-borderless-data-lakehousegoogle/skillsDiscovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).OficialDevOpsFără avertismente★ 21,6 K↓ —
- paperzillaK-Dense-AI/scientific-agent-skillsReads projects, searches project feeds, and retrieves recommendations and canonical papers in Paperzilla through the pz CLI. Supports recent recommendations, paper details, markdown-based summaries, recommendation feedback, JSON export, and Atom feed URLs.ȘtiințăFără avertismente★ 54,5 K↓ —
- bigquery-troubleshootinggoogle/skillsProvides diagnostic workflows and step-by-step root-cause analysis procedures for actively broken, failing, or slow BigQuery jobs, execution graph and query plan stage bottlenecks, system performance issues, or unexpectedly expensive workloads. Use when interpreting symptoms, isolating bottlenecks, diagnosing cost spikes (on-demand query spend, capacity slot autoscaling, storage growth), execution graph stages or substep variables, identifying root causes, and determining remediation steps. Don't use for writing or optimizing SQL, proactive capacity planning, or storage layout design (use bigquery-optimization), or when the user already knows which telemetry they want and just needs the query (use bigquery-observability).OficialDateFără avertismente★ 21,6 K↓ —
- spanner-basicsgoogle/skillsAssists in provisioning instances and databases, designing performant schemas, and querying data in Cloud Spanner on Google Cloud. Use when designing primary keys, writing SQL queries or client library code, or diagnosing performance issues.OficialDateFără avertismente★ 21,6 K↓ —
- google-cloud-waf-securitygoogle/skillsGenerates security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate workloads, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.OficialSecuritateFără avertismente★ 21,6 K↓ —
- remotionsickn33/agentic-awesome-skillsGenerate walkthrough videos from Stitch projects using Remotion with smooth transitions, zooming, and text overlaysAlteleFără avertismente★ 48,5 K↓ —
- polars-bioK-Dense-AI/scientific-agent-skillsPerforms genomic interval overlap, nearest, merge, coverage, complement and subtraction on Polars DataFrames, and reads or writes BED, VCF, BCF, BAM, CRAM, GFF, GTF, FASTA and FASTQ data. Use for coordinate-aware genomic joins, read-depth analysis, lazy bioinformatics I/O, SQL queries or migration from bioframe.DateFără avertismente★ 54,5 K↓ —
- pytest-coveragegithub/awesome-copilotRun pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.TestareFără avertismente★ 40,4 K↓ —
- google-cloud-solution-hybrid-search-alloydbgoogle/skillsDiscovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.OficialDevOpsFără avertismente★ 21,6 K↓ —
- dailysickn33/agentic-awesome-skillsDocumentation and capabilities reference for DailyAlteleFără avertismente★ 48,5 K↓ —
- agentic-evalgithub/awesome-copilotPatterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response qualityTestareFără avertismente★ 40,4 K↓ —
- supabasesickn33/agentic-awesome-skillsUse when doing ANY task involving Supabase.ProductivitateFără avertismente★ 48,5 K↓ —
- terraform-module-librarywshobson/agentsBuild reusable Terraform modules for AWS, Azure, GCP, and OCI infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.DevOpsFără avertismente★ 41,7 K↓ —
- ui-scoresickn33/agentic-awesome-skillsScore a UI file's design quality 0-100 against StyleSeed's design language — per-category breakdown, the worst offenders, and a prioritized fix list. A quantified version of /ss-review.DesignFără avertismente★ 48,5 K↓ —
- nx-workspace-patternswshobson/agentsConfigure and optimize Nx monorepo workspaces. Use when setting up Nx, configuring project boundaries, optimizing build caching, or implementing affected commands.AlteleFără avertismente★ 41,7 K↓ —
- wiki-yylosickn33/agentic-awesome-skillsUse YYLO Ledger wiki Records as durable project knowledge. Search before creating, classify information correctly, and make revision-safe Markdown updates without editing Ledger storage directly.RedactareFără avertismente★ 48,5 K↓ —
- gws-modelarmor-sanitize-responsegoogleworkspace/cliGoogle Model Armor: Sanitize a model response through a Model Armor template.AlteleFără avertismente★ 31,9 K↓ —
- analyze-feature-requestsphuryn/pm-skillsAnalyze and prioritize a list of feature requests by theme, strategic alignment, impact, effort, and risk. Use when reviewing customer feature requests, triaging a backlog, or making prioritization decisions.AlteleFără avertismente★ 27,4 K↓ —
- prioritize-assumptionsphuryn/pm-skillsPrioritize assumptions using an Impact × Risk matrix and suggest experiments for each. Use when triaging a list of assumptions, deciding what to test first, or applying the assumption prioritization canvas.TestareFără avertismente★ 27,4 K↓ —
- recipe-create-vacation-respondergoogleworkspace/cliEnable a Gmail out-of-office auto-reply with a custom message and date range.AlteleFără avertismente★ 31,9 K↓ —
java-debugging
github/awesome-copilot
InginerieActualizat alaltăieri
De la autor
Debug Java applications systematically: JDWP remote debugging, jdb, VS Code and IntelliJ attach, debugging Maven/Gradle tests, Spring Boot and Quarkus dev mode, containers, breakpoints/logpoints, and reading stack traces. Use when the user needs to find the cause of a Java bug, exception, wrong behavior, or failing test, or asks how to attach a debugger.
Instalare
npx skills add github/awesome-copilot --skill java-debugging -a claude-code
Se instalează în .claude/skills/java-debugging/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: MIT
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 95
Securitate100
Proveniență95
Întreținere100
Licență100
Adopție71
Fișiere (2)
- SKILL.md
- references/stack-traces.md