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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 18 ore
48.168 de skill-uri
- validate-bibpedrohcgs/claude-code-my-workflowValidate bibliography entries against citations in all lecture files. Structural checks (missing/unused entries, malformed fields) by default; `--semantic` adds citation-drift detection, DOI verification, and style-consistency checks.AlteleFără avertismente★ 1,7 K↓ —
- relionK-Dense-AI/scientific-agent-skillsValidates and executes RELION single-particle cryo-EM refinement and half-map postprocessing. Supports STAR optics/acquisition checks, particle-stack consistency, gold-standard half sets, soft-mask validation, diagnostic Fourier shell correlation, and restart guidance.AlteleFără avertismente★ 55,5 K↓ —Apare și în 1 alt depozit
- gtarsK-Dense-AI/scientific-agent-skillsSupports Gtars for local genomic interval models and set algebra, overlaps and counts, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and the CLI.ȘtiințăFără avertismente★ 55,5 K↓ —Apare și în 1 alt depozit
- labarchive-integrationK-Dense-AI/scientific-agent-skillsIntegrates with the official LabArchives ELN REST-like API and Inventory API v1. Supports regional endpoint selection, signed-request construction, user authorization and UID flows, local LA container validation, and verified LabArchives integration workflows.InginerieFără avertismente★ 55,5 K↓ —
- bulk-rnaseqK-Dense-AI/scientific-agent-skillsPrepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq and standalone quantification, biological replication, strandedness, reference provenance, validated count assembly and a PyDESeq2 handoff. Use for FASTQ-to-counts analysis, nf-core/rnaseq configuration, STAR/Salmon quantification, or building a counts matrix for DESeq2. For single-cell data use scanpy; for statistical fitting alone use pydeseq2.ȘtiințăFără avertismente★ 55,5 K↓ —
- knowledge-baseinkeep/open-knowledgeHow to work in a Knowledge Base project (the `knowledge-base` starter pack). Read when the project has the three-layer source-grounded layout — `external-sources/` → `research/` → `articles/` — or when asked how this project is organized. Carries the layer model, per-folder rules, status flows, and log discipline so this guidance does NOT live inside template bodies or log.md. The three procedures live elsewhere: ingest in the platform `open-knowledge` skill, research and consolidate as their own sibling skills in this pack. Complements the platform `open-knowledge` skill; does not replace it.ȘtiințăFără avertismente★ 4,7 K↓ —
- analytical-method-validationK-Dense-AI/scientific-agent-skillsPlans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.TestareFără avertismente★ 55,5 K↓ —
- scientific-brainstormingK-Dense-AI/scientific-agent-skillsFacilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.ȘtiințăFără avertismente★ 55,5 K↓ —
- what-if-oracleK-Dense-AI/scientific-agent-skillsSupports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.TestareFără avertismente★ 55,5 K↓ —
- stata-replicationpedrohcgs/claude-code-my-workflowEnd-to-end Stata replication pipeline — scaffolds numbered `.do` files in `scripts/stata/`, executes them via the `stata-mcp` MCP server, captures logs and outputs to `output/`, and produces publication-ready tables (esttab) and figures (graph export). Mirrors `/data-analysis` for R-first projects. Use when user says "stata replication", "set up Stata pipeline", "scaffold the .do files", "run Stata analysis", "AEA replication package in Stata", or when a project's analysis language is Stata not R.DateFără avertismente★ 1,7 K↓ —
- pathogen-variant-surveillanceK-Dense-AI/scientific-agent-skillsQueries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.ȘtiințăFără avertismente★ 55,5 K↓ —
- generate-imageK-Dense-AI/scientific-agent-skillsGenerates or edits images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams, use the scientific-schematics skill instead.MediaFără avertismente★ 55,5 K↓ —
- syllabuspedrohcgs/claude-code-my-workflowBuild or restructure a course syllabus from a topic list or reading list — course description + prerequisites, week-by-week schedule (topic → readings → deliverables), measurable learning objectives, an assessment scheme + rubric, standard policies (late work, AI use, academic integrity, accessibility), and a per-week work-list to hand to `/create-lecture`. Use when user says "build a syllabus", "structure my course", "turn this reading list into a schedule", "draft a course outline", "make a syllabus for Econ 7xx", or "map weeks to lectures". Economics-aware (PhD metrics/micro/macro sequences, undergrad); generic enough for any field.AlteleFără avertismente★ 1,7 K↓ —
- change-requestKlotzkette/claude-fuer-deutsches-rechtFür Change Reqüst: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- huashu-video-outlinealchaincyf/huashu-skills快速生成2-3个视频大纲方案,含标题、封面建议和结构设计。当用户提到"视频大纲"、"视频结构"、"脚本大纲"、"视频选题"时使用。MediaFără avertismente★ 2,1 K↓ —
- statusKlotzkette/claude-fuer-deutsches-rechtFür Fallstatus: Zielgruppengerechte Fallzusammenfassung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- output-waehlenKlotzkette/claude-fuer-deutsches-rechtFür Output wählen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Technik-Governance.AlteleFără avertismente★ 1,8 K↓ —
- deepchemK-Dense-AI/scientific-agent-skillsBuilds molecular property prediction and MoleculeNet workflows with DeepChem, including SMILES featurization, scaffold or grouped holdouts, masked labels, graph models and explicit pretrained encoder transfer. Used for ADMET, toxicity, solubility and chemistry ML when DeepChem data/model contracts and scientific validation are needed.ȘtiințăFără avertismente★ 55,5 K↓ —Apare și în 1 alt depozit
- gke-ai-troubleshooting-tpu-dynamic-slices-monitoringgoogle/skillsMonitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use for generic GKE cluster node pool creation or standard non-TPU workload management (use gke-basics or gke-cluster-creation instead).OficialAlteleFără avertismente★ 21,7 K↓ —
- einstieg-routingKlotzkette/claude-fuer-deutsches-rechtFür Einstieg und Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Jurastudium.AlteleFără avertismente★ 1,8 K↓ —
- cirqsickn33/agentic-awesome-skillsCirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.AlteleFără avertismente★ 48,9 K↓ —
- power-analysispedrohcgs/claude-code-my-workflowCompute statistical power, required sample size, and minimum detectable effect (MDE) for a study design, then write a registry-ready power section. Handles two-arm RCTs (with clustering / ICC and unequal allocation), multiple-arm corrections, and a simulation-based power option for non-standard designs (DiD/event-study, IV, panel). Use when user says "power analysis", "power calculation", "MDE", "minimum detectable effect", "how big a sample do I need", "is my study powered", "power for an RCT", or when /preregister needs a power section for an experiment. Produces a power/MDE table, power curves, and a methods paragraph to paste into a preregistration.DesignFără avertismente★ 1,7 K↓ —
- assuredworkloads-frameworks-navigatorgoogle/skillsActs as a Data Boundary Compliance Analyst that maps user compliance queries against Data Boundary Frameworks and cloud controls, validates matched resources, and recommends appropriate Frameworks or cloud controls. Use when mapping direct natural language workload requirements to Assured Workloads / Data Boundary Frameworks and cloud controls, browsing built-in Data Boundary frameworks, or identifying major requirement gaps. Don't use for non-Data-Boundary Compliance Manager posture assessments or direct Terraform deployment execution without framework selection.OficialDevOpsFără avertismente★ 21,7 K↓ —
- cloud-monitoring-chart-generationgoogle/skillsGenerates Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos on Google Cloud from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.OficialDesignFără avertismente★ 21,7 K↓ —
ml-kit-genai-prompt-api
android/skills
De la autor
Analyzes Android codebases to implement ML Kit GenAI Prompt API. Use this skill to send natural language requests on-device to Gemini Nano, use structured output with Prompt API, implement prefix caching, optimize the current prompt, or apply best practices."
Instalare
npx skills add android/skills --skill ml-kit-genai-prompt-api -a claude-code
Se instalează în .claude/skills/ml-kit-genai-prompt-api/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (Personalizată sau neclară) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
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De ce 89
Fișiere (7)
- SKILL.md
- references/get-started.md
- references/prefix-caching.md
- references/prompt-design.md
- references/prompt-optimization.md
- references/structured-output.md
- references/system-instructions.md