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.
49.399 de skill-uri din 2.375 de depozite · actualizat acum 28 de minute
49.399 de skill-uri
- statistical-analysisK-Dense-AI/scientific-agent-skillsGuided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.TestareFără avertismente★ 56 K↓ —
- blog-strategyAgriciDaniel/claude-blogBuild a blog-level strategy for a niche or business: audience segments, 3-5 content pillars with hub-and-spoke clusters, competitive gaps, measurement plan, and a 90-day roadmap. Use when the user says "blog strategy", "content strategy", "blog positioning", "content pillars", "what should I blog about". Not for a dated publishing schedule (blog-calendar), SERP-validated cluster maps (blog-cluster), or a brief or outline for one post (blog-brief, blog-outline). Makes no promise of rankings or AI citations.RedactareFără avertismente★ 2,6 K↓ —
- scientific-schematicsK-Dense-AI/scientific-agent-skillsGenerates scientific diagram drafts using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.7 Flash for quality review. Refines when the review requests improvement, with at most two generations. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.ȘtiințăFără avertismente★ 56 K↓ —
- get-available-resourcesK-Dense-AI/scientific-agent-skillsDetects host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.TestareFără avertismente★ 56 K↓ —
- latchbio-integrationK-Dense-AI/scientific-agent-skillsBuilds, registers, debugs, and operates bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic execution, and Latch MCP. Use when authoring or deploying Latch workflows, configuring resources or interfaces, moving data, integrating Registry, or launching and monitoring runs.DevOpsFără avertismente★ 56 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★ 56 K↓ —
- scholar-evaluationK-Dense-AI/scientific-agent-skillsProvides qualitative-first, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with optional local quality controls. Never use for ranking people or consequential decisions.ȘtiințăFără avertismente★ 56 K↓ —
- lab-hardware-cadK-Dense-AI/scientific-agent-skillsDesigns custom laboratory hardware as parametric build123d models and exports fabrication artifacts as STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research task needs a physical part that must mate with standardized labware, an optical table, a cage system, or a printer, CNC, or laser process.ȘtiințăFără avertismente★ 56 K↓ —
- employee-relationscbrock84/headcountHandles the difficult human situations — grievances, complaints, investigations, conflict, and separations conducted properly. Use this to respond to a complaint or grievance, structure an investigation, handle a conflict between colleagues, prepare for a difficult conversation, or work out what a manager can and cannot do in a given situation.FinanțeFără avertismente★ 2,6 K↓ —
- cobrapyK-Dense-AI/scientific-agent-skillsPerforms constraint-based metabolic modeling with COBRApy, including FBA, pFBA, FVA, gene knockouts, flux sampling, growth media, production envelopes, gap filling, and SBML model validation for systems biology and metabolic engineering.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- daskK-Dense-AI/scientific-agent-skillsScales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure require Dask.DateFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- blog-factcheckAgriciDaniel/claude-blogVerify statistics and claims in blog posts by fetching cited source URLs and checking if the claimed data actually appears on the page. Extracts all load-bearing claims (statistics, product or policy claims, ranking and comparative claims, named sources), validates cited URLs before fetching, and scores match confidence (exact match 1.0, paraphrase 0.7-0.9, not found 0.0). Flags uncited claims as UNVERIFIED and marks a claim verified only when this run fetched the source and found the passage. Checks that a source says what the post says it says; it cannot prove the source is true or verify first-hand experience. Use when the user says "fact check", "verify statistics", "check sources", "factcheck". Report only; not for rewriting posts (blog-rewrite).RedactareFără avertismente★ 2,6 K↓ —
- video-contentcbrock84/headcountPlans and scripts short-form and long-form video, and designs the packaging — titles, thumbnails, and openings — that determines whether it gets watched. Use this to script a video, plan a series, fix retention or click-through problems, design thumbnail and title concepts, or turn written content into video. For a YouTube channel specifically — idea selection, retention teardowns, and channel-level strategy — use `youtube-producer`.MediaFără avertismente★ 2,6 K↓ —
- scenario-seedreamscenario-labs/skillsUse when generating or editing images with Seedream models on Scenario via MCP: text-to-image, image-to-image editing with reference images, posters or packaging with exact in-image text (non-Latin scripts too), subject-preserving edits, sets of related images in one run, editing a transparent asset without losing its alpha, or splitting an image into transparent PNG layers with Layerize. Keywords: Seedream 5.0 Pro, Lite, Flash, 4.5, Layerize, ByteDance, txt2img, img2img, layer extraction.MediaFără avertismente★ 1,9 K↓ —
- depmapK-Dense-AI/scientific-agent-skillsRetrieves and analyzes Cancer Dependency Map (DepMap) release data, including CRISPR Chronos gene effects, cancer model annotations, omics biomarkers, and PRISM drug sensitivity. Supports cancer-selective dependency, co-essentiality, and candidate synthetic-lethality analyses with release-aware identifiers and statistical checks.AlteleFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- transformersK-Dense-AI/scientific-agent-skillsHugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with AutoModel, pipelines, tokenizers, generation configs, or TrainingArguments within Transformers.MediaFără avertismente★ 56 K↓ —
- sympyK-Dense-AI/scientific-agent-skillsPerforms exact symbolic mathematics with SymPy for algebra, calculus, equation solving, symbolic linear algebra, physics, and lambdify or LaTeX code generation. Use when a task needs symbolic results, explicit assumptions, or exact arithmetic; use NumPy or SciPy for purely numerical workloads.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- scenario-meshyscenario-labs/skillsUse when creating or refining 3D assets with Meshy models on Scenario via MCP: image-to-3D from one photo or 1-4 multi-view angles, text-to-3D, retexturing an existing GLB, remeshing to a target polycount, UV unwrapping, auto-rigging a humanoid character, or applying a library animation clip. Keywords: Meshy 7 and Meshy 6, Ultra mode, Smart Topology, PBR maps, texture prompt, triangle or quad topology, game-ready mesh, A-pose, T-pose, GLB pipeline.MediaFără avertismente★ 1,9 K↓ —
- franchise-agbKlotzkette/claude-fuer-deutsches-rechtFür Franchise AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: franchise-agb.AlteleFără avertismente★ 1,8 K↓ —
- skill-authoringcbrock84/headcountWrites and revises agent skills so they trigger at the right moments and give usable instruction when they do. Use this when creating a new skill, editing an existing one, diagnosing a skill that fires too often or never fires, or reviewing a set of skills for overlap. Also use before adding to a skill library, to check the capability is not already covered.RedactareFără avertismente★ 2,6 K↓ —
- gegen-gelb-gleichtKlotzkette/claude-fuer-deutsches-rechtFür Gegen: Dokumentenmatrix, Lückenliste und Nachforderung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- dsh-pre-push-checksNouqufei1993/skills-hub在交付或推送前验证改动时使用，核实项目必需检查、当前构建产物和真实用户行为，区分通过、失败、未运行与环境阻塞。AlteleFără avertismente★ 1,9 K↓ —
- ux-product-auditorcbrock84/headcountAudits a website, app, onboarding flow, or design for usability, conversion, and product problems, tying every finding to a business outcome and a severity. Use this to review an interface, diagnose low conversion or activation, find where users drop off, get structured product feedback, or decide which UX fixes to ship first. For raising visual quality rather than finding problems, use `interface-craft`.DesignFără avertismente★ 2,6 K↓ —
- hi-liteLeoYeAI/agent-master-skillsSearch, browse, and rediscover your Kindle highlightsAlteleFără avertismente★ 2,2 K↓ —
foundry-agentic-loop
github/awesome-copilot
DevOpsActualizat acum 15 ore
De la autor
Build agentic solutions on Microsoft Foundry, GitHub and Azure: hosted agents, toolbox tools and skills, Foundry IQ grounding and a React/FastAPI app. Three modes: rapid prototyping in an existing Foundry project; spec-driven development (SDD), where the foundry-agentic-loop-workflow runs Specify, Implement, Verify and Deploy to create the Foundry project and deploy with azd, or one phase runs alone; and Improve, which refines this skill and the workflow from past runs. Use for Agentic Loop requests and canvas actions, or end-to-end agent solutions from architecture to Azure deployment. Not for isolated Azure administration or unrelated UI edits.
Instalare
npx skills add github/awesome-copilot --skill foundry-agentic-loop -a claude-code
Se instalează în .claude/skills/foundry-agentic-loop/ · 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
Rulează scripturile incluseNu am văzut acces la rețeaLicență: MIT
Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 89
Securitate85
Proveniență95
Întreținere100
Licență100
Adopție71
Fișiere (55)
- SKILL.md
- assets/agents-md-rapid.md
- assets/agents-md-sdd.md
- assets/deployment-plan-template.md
- assets/devcontainer.json
- assets/loop-template.md
- assets/spec-template.md
- evals/evals.json
- evals/fixtures/improve-history/.agentic-loop/runs/wr_101.json
- evals/fixtures/improve-history/.agentic-loop/runs/wr_117.json
- evals/fixtures/improve-history/.agentic-loop/runs/wr_123.json
- evals/fixtures/improve-history/AGENTS.md
- încă 43