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.
49.395 de skill-uri din 2.375 de depozite · actualizat acum 35 de minute
49.395 de skill-uri
- employment-compliancecbrock84/headcountCovers the employment rules that carry real penalties — exempt and non-exempt classification, overtime and hours, employee versus contractor status, work authorization and recordkeeping, accommodation requests, and the notices and retention obligations that go with them. Use this to classify a role, review a contractor arrangement, respond to an accommodation request, work out what records to keep and for how long, or sanity-check a practice you inherited.JuridicFără avertismente★ 2,6 K↓ —
- seedance-storyboard-grid-to-videoLearnPrompt/awesome-seedanceTwo stages: first a single-page sheet of numbered panels from an image model, then that sheet fed to Seedance as the reference. The sheet owns order, framing and timing, and the video prompt only has to connect the panels. Use when the user wants a Seedance 2.5 / 2.0 video prompt for this kind of clip (Storyboard grid to video; 中文触发词: 分镜网格转视频, 分镜图, 九宫格, 故事板), or asks how published cases of this type were prompted. Read references/cases.md before drafting.MediaFără avertismente★ 2,4 K↓ —
- slide-excellencepedrohcgs/claude-code-my-workflowMulti-agent comprehensive slide review (visual + pedagogy + proofreading, plus TikZ / parity / substance conditionally). Use when user says "full review", "excellence pass", "comprehensive check", "review everything", "pre-release review", "slide excellence", or before teaching / shipping a deck. Fanout wrapper — for a single lens, use `/visual-audit`, `/pedagogy-review`, or `/proofread` directly.DocumenteFără avertismente★ 1,7 K↓ —
- session-compactcodeaholicguy/ai-devkitAI DevKit · Compact a historical AI coding session with Jev when context is long, work is handed off or resumed, or durable continuation facts and memory candidates need extraction.InginerieFără avertismente★ 1,7 K↓ —
- youtube-transcribe-skillfeiskyer/claude-code-settingsExtract subtitles/transcripts from YouTube videos. Triggers: "youtube transcript", "extract subtitles", "video captions", "视频字幕", "字幕提取", "YouTube转文字", "提取字幕".MediaFără avertismente★ 1,7 K↓ —
- networkxK-Dense-AI/scientific-agent-skillsCreates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 1 alt depozit
- pydeseq2K-Dense-AI/scientific-agent-skillsPerforms bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage, and result visualization. Use for PyDESeq2 or Python DESeq2 workflows with biological replicates.TestareFără avertismente★ 56 K↓ —Apare și în 1 alt depozit
- seabornK-Dense-AI/scientific-agent-skillsCreates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory plots; plotly covers interactive figures and scientific-visualization covers publication styling.DateFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- convert-excel-to-mdgithub/awesome-copilotConverts Excel (.xlsx) workbooks into Markdown so their contents can be accurately analyzed, summarized, searched, or extracted from. Use this skill whenever the user shares, references, or asks about a .xlsx file — even if they don't say "convert" or "markdown" explicitly. This includes requests to "read", "summarize", "review", "extract data from", "compare", "chart", or "analyze" a spreadsheet, workbook, budget, data export, or tracker. Always run the bundled conversion script to produce Markdown first; do not attempt to parse .xlsx content directly or write ad-hoc extraction code. Also use this skill for batch requests involving a whole folder of Excel workbooks. IMPORTANT: When the user references a folder or set of documents containing multiple file types (.pdf, .docx, .xlsx), invoke ALL three sibling skills — convert-pdf-to-md, convert-word-to-md, and convert-excel-to-md — so no file type is silently skipped.DocumenteFără avertismente★ 40,8 K↓ —
- autoskillK-Dense-AI/scientific-agent-skillsAnalyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review. Requires a reachable Screenpipe HTTP API, normally on localhost:3030. Detection and embedding inference run locally; the selected LLM receives redacted app/title cluster summaries and matched skill descriptions. Use only when the user explicitly asks to analyze their recent work and propose skills.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 1 alt depozit
- 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
- diagram-designcathrynlavery/diagram-designCreate branded architecture, architecture delta, IT current-state, flowchart, sequence, state machine, ER/data model, timeline, swimlane, quadrant, radar/spider, polar chart (polar/radial lollipop), loop/flywheel, nested, tree, org chart, layer stack, exploded axonometric, axonometric plan, Venn, pyramid/funnel, treemap and marimekko, heatmap, bar and dumbbell, waterfall, line (slopegraph, ridgeline, streamgraph, bump), Gantt and scatter charts (bubble, beeswarm, box plot), high-level, process, medallion, data flow, DP integration, DP security matrix, Sankey, fishbone, Wardley map, kanban, user journey, service blueprint, deployment, dependency graph, UML class, story map, or database schema diagrams as HTML/SVG/PNG, with .drawio, Mermaid, and .excalidraw import, plus lifecycle phase maps, block decomposition trees, and onboarding guidance.DesignFără avertismente★ 64,6 K↓ —
- research-lookupK-Dense-AI/scientific-agent-skillsCompiles current scholarly evidence for a scientific manuscript or research brief when the user explicitly asks to gather literature, references, background evidence, competing findings, or a manuscript research packet. Uses Parallel Search by default, Parallel Extract for source retrieval, Parallel Research for explicitly deep/exhaustive work, optional explicit Parallel Chat, and optional Perplexity only when requested or allowed as a failure fallback.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↓ —
- 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↓ —
- agent-skill-stackgithub/awesome-copilotFind, evaluate, and assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use when a user wants Skills for a multi-step workflow, asks which Skills fit a project, needs an installed-Skill audit or conflict check, has low Skill recall, wants indirect helpers such as humanizers or compliance checks, or wants a project-specific Skill Stack with controlled installation. Search local Skills, registries, GitHub, and OpenCLI; compare adoption, verified fit, safety, and overlap. Do not use for locating one known or common Skill; use the generic find-skills workflow.JuridicFără avertismente★ 40,8 K↓ —
- 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↓ —
- 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★ 56 K↓ —
- relsa-severity-assessmentK-Dense-AI/scientific-agent-skillsSupports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.ȘtiințăFără avertismente★ 56 K↓ —
- 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↓ —
- 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↓ —
- keyword-stuffingcisco-ai-defense/skill-scannerInflate skill discovery through repeated activation keywordsAlteleFără avertismente★ 2,7 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↓ —
- 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★ 56 K↓ —
hivemind
activeloopai/hivemind
ProductivitateActualizat 24 oct. 2026
De la autor
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
Instalare
npx skills add activeloopai/hivemind --skill hivemind -a claude-code
Se instalează în .claude/skills/hivemind/ · 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: APACHE-2.0
Verificări de siguranță pe SKILL.md
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De ce 89
Securitate100
Proveniență79
Întreținere100
Licență100
Adopție52
Fișiere (1)
- SKILL.md