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.
46.100 de skill-uri din 2.198 de depozite · actualizat acum 19 ore
45.010 skill-uri
- telegramsickn33/agentic-awesome-skillsIntegracao completa com Telegram Bot API. Setup com BotFather, mensagens, webhooks, inline keyboards, grupos, canais. Boilerplates Node.js e Python.InginerieFără avertismente★ 48,7 K↓ —
- find-hypertable-candidatestimescale/pg-aiguideUse this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.DateFără avertismente★ 1,9 K↓ —
- assessment-designcbrock84/headcountBuilds questions and assessments that measure what they claim — matching item type to the thing being assessed, writing distractors that diagnose, and telling a question that measures learning from one that measures reading speed or test-taking. Use this to write or review assessment items, design a unit check or diagnostic, work out why scores do not match classroom performance, or decide how much evidence a claim about mastery actually needs.DesignFără avertismente★ 2,5 K↓ —
- blog-taxonomyAgriciDaniel/claude-blogSuggest tags and categories for a blog post from its content, audit a site's tag and category health, and, only after the user approves a shown plan, sync tags and categories to WordPress, Shopify, Ghost, Strapi, or Sanity. suggest and audit are read-only; sync is dry-run by default and never deletes, merges, or edits post content. Use when the user says "tag suggestions", "taxonomy audit", "sync tags", "WordPress tags", "Shopify tags". Not for keyword research (blog-brief) or schema markup (blog-schema).RedactareFără avertismente★ 2,6 K↓ —
- matchmsK-Dense-AI/scientific-agent-skillsProcesses, cleans, compares, and searches tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.PlanificareFără avertismente★ 55,2 K↓ —Apare și în 1 alt depozit
- gutachten-uebungKlotzkette/claude-fuer-deutsches-rechtFür Gutachtenstil-Übung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- pathway-enrichmentK-Dense-AI/scientific-agent-skillsPerforms pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results. Used when the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".TestareFără avertismente★ 55,2 K↓ —
- access-and-identitycbrock84/headcountDesigns and audits who can reach what — authentication, authorization models, privileged access, service credentials, and joiner-mover-leaver process. Use this to design a permissions model, run an access review, reduce standing privilege, handle offboarding, set up SSO or MFA, manage service and machine credentials, or diagnose why permissions have sprawled.DesignFără avertismente★ 2,5 K↓ —
- strategic-alliancescbrock84/headcountStructures partnerships that change what the business can do — technology integrations, channel and reseller arrangements, joint ventures, and OEM relationships. Use this to evaluate or structure a strategic partnership, decide between partnering and building, negotiate commercial terms of an alliance, or diagnose a partnership that is signed but not producing. For audience-borrowing partnerships, use `marketing:partnership-marketing`.MarketingFără avertismente★ 2,5 K↓ —
- ehs-and-workplace-safetycbrock84/headcountRuns environment, health and safety on an operating site — hazard controls in order of effectiveness, incident recording and reporting obligations, and safety measurement that does not reward silence. Use this to build or audit a safety program, decide what controls a hazard actually needs, work out whether an injury is recordable or reportable, investigate an incident, or fix safety metrics that have stopped producing reports.FinanțeFără avertismente★ 2,5 K↓ —
- astropysickn33/agentic-awesome-skillsAstropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.DateFără avertismente★ 48,7 K↓ —
- impeccableActualizatpbakaus/impeccableUse when the user wants to design, redesign, shape, critique, audit, polish, simplify, harden, animate, or otherwise improve a frontend interface: websites, landing pages, dashboards, product UI, components, forms, settings, onboarding, empty states, and native iOS or Android screens. Handles UX review, hierarchy, layout, typography, color, motion, UX copy, accessibility, responsive behavior, edge cases, and capturing or documenting design systems (DESIGN.md, tokens). Also for making bland UI bolder, loud UI quieter, or ambitious visual effects. Not for backend-only or non-UI tasks.DesignFără avertismente★ 94,4 K↓ —
- anpassenKlotzkette/claude-fuer-deutsches-rechtFür Customize – Praxisprofil anpassen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- ncats-araxK-Dense-AI/scientific-agent-skillsQueries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings, publications, and knowledge-source provenance. Do not use for inference, ranking, open-ended pathfinding, clinical guidance, or sensitive queries.ȘtiințăFără avertismente★ 55,2 K↓ —
- loresickn33/agentic-awesome-skillsMarkdown project memory for AI agents. Use for decisions, architecture, conventions, monorepo scopes, `.lore/`, or `lore` commands; not native `/init`/`/compact` or generic init/compress/audit/query.PlanificareFără avertismente★ 48,7 K↓ —
- ai-search-optimizationcbrock84/headcountOptimizes for AI assistants and AI-generated answers — being retrievable, being cited, and being represented accurately when a model answers on your behalf. Use this when traffic is shifting from links to AI answers, when a brand is misrepresented or absent in AI responses, when planning content for retrieval rather than ranking, or when deciding how AI search changes an existing SEO program.MarketingFără avertismente★ 2,5 K↓ —
- anlagen-bauenKlotzkette/claude-fuer-deutsches-rechtFür Fahrgastrechte — Anlagen bauen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- bona-fidesKlotzkette/claude-fuer-deutsches-rechtFür Bona Fides: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 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★ 55,2 K↓ —
- wear-compose-m3Actualizatandroid/skillsGuidance for Wear OS Compose Material3 (Wear Compose Material 3 / Wear Compose Material3) watch and wearable apps. Covers creating, updating, and migrating projects (Material 2.5 and Horologist migration) using androidx.wear.compose.material3, androidx.wear.compose.foundation, and androidx.wear.compose.navigation3, including AppScaffold, ScreenScaffold, TransformingLazyColumn, ambient mode, and previews.OficialAlteleFără avertismente★ 10 K↓ —
- pgvector-semantic-searchtimescale/pg-aiguideUse this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.DateFără avertismente★ 1,9 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★ 55,2 K↓ —
- schema-explorationtimescale/pg-aiguideExplore an existing PostgreSQL database before answering questions about its data or writing SQL. Use this skill whenever a user asks for a query or a data-backed answer against an unfamiliar schema (counts, missing or failed records, recent changes), asks where a business concept lives, or asks how tables, joins, views, routines, triggers, RLS, or extensions work. Find the relevant objects with read-only pg_catalog queries, then request approval before inspecting data-derived statistics or rows. Not a schema-design or migration guide.DateFără avertismente★ 1,9 K↓ —
- android-profilerandroid/skillsRecords and analyzes Android performance data and diagnoses performance bottlenecks across user apps, system apps, and system services, even if the user does not explicitly mention profiling or traces. Use when: recording system traces, CPU call stacks, Vulkan GPU/DRM memory, or Java/native heap profiles; analyzing Perfetto traces for UI jank, frame drops, ANRs, or app startup latency issues; investigating CPU bottlenecks, IPC/Binder storms, or thread scheduling stalls; diagnosing battery drain, modem power rails, and kernel wake locks; debugging memory pressure, Low Memory Kills (LMK), OOMs, leaks, and allocation churn; performing A/B baseline trace comparisons to find regressions; executing ad hoc PerfettoSQL queries on Android traces.OficialDesignFără avertismente★ 10 K↓ —
liteparse
K-Dense-AI/scientific-agent-skills
DocumenteActualizat acum 4 zile
De la autor
Local document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities are spatial text boxes, Markdown, page raster output, and local parsing with optional custom HTTP OCR.
Instalare
npx skills add K-Dense-AI/scientific-agent-skills --skill liteparse -a claude-code
Se instalează în .claude/skills/liteparse/ · 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 incluseFolosește rețeauaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 89
Securitate85
Proveniență95
Întreținere100
Licență100
Adopție73
Fișiere (7)
- SKILL.md
- references/api_reference.md
- references/choosing_a_parser.md
- references/cli_reference.md
- references/ocr_and_formats.md
- references/output_formats.md
- scripts/batch_parse_dir.py