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.
47.966 de skill-uri din 2.309 depozite · actualizat acum 4 ore
46.854 de skill-uri
- metabase_ingestKaelio/ktxConvert Metabase questions, models, and metrics into ktx Semantic Layer source definitions. Covers result-metadata to KSL column type mapping, FK/PK detection, near-duplicate deduplication, pre-aggregation decomposition, join-graph connectivity, and how to react to priorProvenance from earlier ingest syncs. Load when the WorkUnit contains `cards/<id>.json` files under a Metabase bundle.InginerieFără avertismente★ 1,6 K↓ —
- slKaelio/ktxktx's semantic layer - a structured catalog of sources (tables/views), measures, joins, and segments expressed as YAML. Covers the schema and how to query it via `sl_query`. Use when the task involves querying pre-defined metrics (ARR, churn, retention, LTV, MAU) or reading SL source YAML to understand the catalog. Capture is handled by the `sl_capture` skill (memory-agent only).ProductivitateFără avertismente★ 1,6 K↓ —
- design-stylescbrock84/headcountApplies a deliberate visual direction to an interface — minimalist editorial, industrial utilitarian, or high-polish commercial — each with its own type scale, palette behavior, surface treatment, and motion. Use this when a product needs a point of view rather than defaults, when choosing between visual directions, when an interface reads as generic, or when restyling something without changing its structure.DesignFără avertismente★ 2,5 K↓ —
- jetpack-compose-performanceandroid/skillsDiagnose and optimize Android Jetpack Compose UI code. Use this skill when analyzing performance bottlenecks of existing code to minimize recomposition overhead and prevent dropped frames and UI lag.OficialDesignFără avertismente★ 10,1 K↓ —
- dbt_ingestKaelio/ktxMap dbt `schema.yml` / `properties.yml` models and sources into ktx semantic-layer overlays and column notes. Covers `sources:` vs `models:`, column `data_tests` (not_null, unique, accepted_values, relationships), and how bundle-time writes complement manifest backfill from git sync. Load when the WorkUnit's `skillNames` includes `dbt_ingest` or when raw files are dbt YAML under `models/` / `sources/`.DateFără avertismente★ 1,6 K↓ —
- ktx-analyticsKaelio/ktxUse when answering a question that needs data from a ktx-connected database - investigating, analyzing, "how many", "show me", "what's the breakdown of", finding records by value, exploring tables, comparing periods, explaining metrics, or any data-analysis request. Triggers even when the user does not say "analytics"; if the answer requires querying a configured ktx connection, this skill applies.DateFără avertismente★ 1,6 K↓ —
- hivemind-memoryactiveloopai/hivemindGlobal team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.ProductivitateFără avertismente★ 1,6 K↓ —
- hivemindactiveloopai/hivemindGlobal team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.ProductivitateFără avertismente★ 1,6 K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).PlanificareFără avertismente★ 1,6 K↓ —
- hivemind-goalsactiveloopai/hivemindCreate, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.InginerieFără avertismente★ 1,6 K↓ —
- dsh-client-ui-uxNouqufei1993/skills-hub设计、实现或审查客户端 UI、响应式布局、交互状态、焦点或失败反馈时使用,结合真实运行界面验证用户体验。DesignFără avertismente★ 1,8 K↓ —
- agent-orchestrationcodeaholicguy/ai-devkitAI DevKit · Supervise multi-agent workflows over repeated passes: poll progress, unblock waiting agents, coordinate dependencies, relay outputs, resolve conflicts, and verify completion. Use only for ongoing multi-agent coordination, not one-off list/detail/send/start/kill actions.AlteleFără avertismente★ 1,7 K↓ —
- dev-implementationcodeaholicguy/ai-devkitAI DevKit · Implementation phase guidance for executing feature plans and checking implementation against design. Use when the user wants to implement planned tasks, update implementation docs, verify code matches design, or run dev-lifecycle phases 5 and 7.DesignFără avertismente★ 1,7 K↓ —
- 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★ 55,4 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★ 55,4 K↓ —Apare și în 1 alt depozit
- simulation-studypedrohcgs/claude-code-my-workflowScaffold and run a reproducible Monte Carlo simulation study in R — a declared assumption regime, a parameterized DGP, an estimator grid, a seeded replication loop, and a summary of bias, RMSE, empirical SE, coverage, size/power with Monte Carlo standard errors. Use when the user says "run a Monte Carlo simulation", "simulation study", "check the bias/coverage of an estimator", "compare estimators in simulation", "size and power simulation", "Monte Carlo experiment", or wants to demonstrate an estimator's finite-sample properties. Produces a numbered R script in `scripts/R/` and saves per-replication raw results + a summary table to `output/`.ProductivitateFără avertismente★ 1,7 K↓ —
- teach-from-paperpedrohcgs/claude-code-my-workflowTurn a research paper into teaching materials — a lecture outline, the 3-5 results worth presenting (with intuition), a slide skeleton ready for `/create-lecture`, discussion questions, and a problem-set brief. Reads the paper end-to-end and pitches to a stated audience level. Use when user says "turn this paper into a lecture", "teach from this paper", "build slides from this PDF", "make teaching materials from X", "I'm presenting this paper to my class".ȘtiințăFără avertismente★ 1,7 K↓ —
- 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★ 55,4 K↓ —Apare și în 1 alt depozit
- design-systemcbrock84/headcountBuilds and maintains the design system a product is assembled from — tokens for color, type, spacing and elevation, component contracts, and the rules that keep them coherent as the product grows. Use this when starting a new interface, when screens have drifted apart visually, when the same component exists three times in slightly different forms, or when a token or component needs adding without breaking what exists.DesignFără avertismente★ 2,5 K↓ —
- r-package-checkpedrohcgs/claude-code-my-workflowRun the full R package release gate — regenerate docs, run the test suite, run R CMD check --as-cran, and triage every ERROR / WARNING / NOTE against CRAN policy before a release or submission. Use when the user says "check my R package", "R CMD check", "is this package CRAN-ready", "run devtools::check", "prepare for CRAN submission", or points at a directory containing a DESCRIPTION file. Produces a check report + CRAN-submission checklist in `quality_reports/`.TestareFără avertismente★ 1,7 K↓ —
- pysamK-Dense-AI/scientific-agent-skillsProvides Python/HTSlib workflows for genomic files. Used when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.ȘtiințăFără avertismente★ 55,4 K↓ —Apare și în 1 alt depozit
- compress-sessionpedrohcgs/claude-code-my-workflowDistill the current conversation into a structured note (decisions made, open questions, file pointers with line numbers, next 1–3 actions) and save to `quality_reports/session_logs/` before auto-compression. Differs from `/checkpoint` (explicit stop-point snapshot) and from auto-compaction (which truncates rather than distills). Use when context is approaching auto-compact threshold, when a long pipeline has accumulated many decisions, or when the user says "compress", "distil this session", "before we hit auto-compact", "structured handoff before context resets".ProductivitateFără avertismente★ 1,7 K↓ —
- pytdcK-Dense-AI/scientific-agent-skillsProvides Therapeutics Data Commons workflows through PyTDC for registry discovery, dataset access, task-aware splits, evaluator metrics, benchmark groups, and bounded molecular-oracle scoring. Use when working with TDC therapeutic ML datasets or benchmarks.ProductivitateFără avertismente★ 55,4 K↓ —Apare și în 1 alt depozit
- typeuibergside/typeuiUse TypeUI with OpenClaw to access project design skills, brand kits, UI prompts, and layout variations through the TypeUI MCP server when creating or refining user interfaces.DesignFără avertismente★ 2,2 K↓ —
voice-of-customer
cbrock84/headcount
De la autor
Builds the loop from what customers say to what gets changed — collecting feedback, distinguishing signal from noise, routing it to owners, and closing the loop back to the customer. Use this to set up a feedback program, design or interpret CSAT/NPS, decide what customer feedback deserves action, get product to act on recurring issues, or diagnose why feedback is collected but nothing changes.
Instalare
npx skills add cbrock84/headcount --skill voice-of-customer -a claude-code
Se instalează în .claude/skills/voice-of-customer/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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