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.
48.622 de skill-uri din 2.355 de depozite · actualizat acum 4 ore
48.622 de skill-uri
- claude-reflectBayramAnnakov/claude-reflectSelf-learning system that captures corrections during sessions and reminds users to run /reflect to update CLAUDE.md. Use when discussing learnings, corrections, or when the user mentions remembering something for future sessions.AlteleFără avertismente★ 1,9 K↓ —
- unit-economicscbrock84/headcountEstablishes whether the business makes money on each customer or unit — contribution margin, acquisition cost, payback period, lifetime value, and the cohort behavior underneath. Use this to assess whether growth is profitable, evaluate a channel or segment, support a pricing decision, judge how fast the business can afford to grow, or diagnose why revenue growth is not producing profit.MarketingFără avertismente★ 2,6 K↓ —
- change-and-adoptioncbrock84/headcountGets people to actually use what was delivered — stakeholder analysis, communication, training, resistance, and measuring adoption. Use this to plan a rollout, recover an implementation nobody is using, handle resistance to a change, sequence communications, or work out why a technically successful project changed nothing.PlanificareFără avertismente★ 2,6 K↓ —
- eyeballgithub/awesome-copilotDocument analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.AlteleFără avertismente★ 40,7 K↓ —
- blog-styleAgriciDaniel/claude-blogLearn author writing style from 5 to 10 existing blog posts and generate a voice profile for /blog style learn, VOICE.md, blog-persona, and blog-write when users ask to infer tone, analyze author voice, learn style, or build a writing baseline.RedactareFără avertismente★ 2,6 K↓ —
- 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★ 40,7 K↓ —
- activationcbrock84/headcountGets new users from signup to first real value — signup flow, onboarding, time-to-value, and the early experience that determines whether someone becomes a user or a lapsed account. Use this to design or fix signup and onboarding, diagnose why signups do not convert to active use, reduce time-to-value, or decide what a new user must accomplish first.DesignFără avertismente★ 2,6 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★ 55,6 K↓ —Apare și în 1 alt depozit
- sigma_ingestKaelio/ktxExtract durable ktx wiki knowledge from staged Sigma data model specs and workbook summaries. Load for WorkUnits with unitKey sigma-data-models or sigma-workbooks.PlanificareFără avertismente★ 1,6 K↓ —
- wiki_captureKaelio/ktxktx's knowledge base - wiki pages for durable, reusable business knowledge. Covers capture workflow for user preferences, metric definitions, organizational conventions, and cross-references between wiki pages and semantic-layer sources. Loaded by the post-turn memory-agent only. The research agent reads wiki via `wiki_read`/`wiki_search` but does not write it.ȘtiințăFără avertismente★ 1,6 K↓ —
- looker_ingestKaelio/ktxExtract durable ktx knowledge and semantic-layer contribution proposals from staged Looker runtime dashboard, Look, and explore JSON. Load for WorkUnits whose raw files are under explores/, dashboards/, or looks/.AlteleFără avertismente★ 1,6 K↓ —
- sl_captureKaelio/ktxHow to capture new reusable patterns into ktx's semantic layer - when a measure, segment, or join belongs in the catalog and how to write it generically so it stays small and useful over time. Loaded by the post-turn memory-agent only. The research agent does not write to the SL.ȘtiințăFără avertismente★ 1,6 K↓ —
- ingest_triageKaelio/ktxClassify and resolve conflicts detected during bundle ingest (structural duplicates, definitional contradictions, near-duplicate clusters, re-ingest changes, evictions).AlteleFără avertismente★ 1,6 K↓ —
- 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↓ —
- lookml_ingestKaelio/ktxMap a LookML view/model/explore into ktx semantic layer sources. Covers the LookML to ktx primitive table, provenance tagging, and three worked examples (overlay, standalone from derived_table, standalone with sql_always_where). Load when the turn contains `.lkml` content.AlteleFără 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↓ —
- deal-negotiationcbrock84/headcountNegotiates a commercial deal without giving away the terms that matter — preparing your walk-away and theirs, trading concessions rather than conceding them, recognizing the tactics that create false urgency, protecting price by moving other variables, and closing on terms someone can actually deliver. Use this to prepare for a negotiation, respond to a demand mid-deal, work out why discounts keep landing at quarter end, or review terms before they are signed.FinanțeFără avertismente★ 2,6 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↓ —
- ransomware-requestcisco-ai-defense/skill-scannerIssue an explicit imperative request for a prohibited cyber-harm capabilityAlteleFără avertismente★ 2,7 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↓ —
- seabornsickn33/agentic-awesome-skillsSeaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.InginerieFără avertismente★ 49 K↓ —
- networkxsickn33/agentic-awesome-skillsNetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.InginerieFără avertismente★ 49 K↓ —
- bumblebeesickn33/agentic-awesome-skillsRun Bumblebee supply-chain inventory and exposure scans on macOS/Linux to detect compromised packages, extensions, and MCP host configs.AlteleFără avertismente★ 49 K↓ —
- setup-timescaledb-hypertablestimescale/pg-aiguideUse this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. **Trigger when user asks to:** - Create or design SQL schemas/tables AND Timescale/TimescaleDB/TigerData/Tiger Cloud is available - Set up hypertables, compression, retention policies, or continuous aggregates - Configure partition columns, segment_by, order_by, or chunk intervals - Optimize time-series database performance or storage - Create tables for sensors, metrics, telemetry, events, or transaction logs **Keywords:** CREATE TABLE, hypertable, Timescale, TimescaleDB, time-series, IoT, metrics, sensor data, compression policy, continuous aggregates, columnstore, retention policy, chunk interval, segment_by, order_by Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes.DateFără avertismente★ 1,9 K↓ —
ml-kit-genai-prompt-api
android/skills
OficialInginerieActualizat acum 3 zile
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
Doar instrucțiuniNu am văzut acces la rețeaLicență: Personalizată sau neclară
Verificări de siguranță pe SKILL.md
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De ce 89
Securitate100
Proveniență100
Întreținere100
Licență45
Adopție63
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