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.
42.683 de skill-uri din 2.004 depozite · actualizat acum 8 minute
41.993 de skill-uri
- app-observabilitygrafana/skillsGet RED metrics + service maps + frontend RUM + AI/LLM monitoring out of Grafana Cloud — Application Observability (`traces_spanmetrics_*` from OTel traces, p50/p95/p99 latency, exemplar-to-trace, traces-to-logs / profiles), Frontend Observability with the Faro Web SDK (Core Web Vitals, session replay, `pushError`, React + router integration, `TracingInstrumentation` for browser → backend trace correlation), and AI Observability via OpenLIT (token / cost / latency, GPU, hallucination + toxicity evals). Use when standing up APM for a service, wiring an Alloy OTLP receiver + forwarding to Cloud, instrumenting a React frontend for RUM, debugging why service-map edges are missing, monitoring LLM cost drift, or correlating a frontend error to its backend trace — even when the user says "set up APM", "show service map", "monitor browser perf", "session replay", "RUM SDK", or "watch our OpenAI bill" without naming App / Frontend / AI Observability.OficialDevOpsFără avertismente★ 290↓ —
- mcp-builderanthropics/skillsGuide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).OficialInginerieFără avertismente★ 183,4 K↓ —Apare și în 10 alte depozite
- replica-buildJakeschincariol/replica-skillRebuilds an app screen by screen from the recon map: app shell first, then the core flow as a vertical slice, then every screen with all its states, ticking off the feature matrix as it goes. Writes every line fresh, never the original's code, assets or copy. Use when the user says "build the clone", "build screen S07", "start building", "rebuild this screen", "implement the booking page", or after /replica-design.DesignFără avertismente★ 5,1 K↓ —
- excel-threshold-analysis-and-stylingOpenSenseNova/SenseNova-Skills根据 Excel 数据量级自动判断处理策略,执行数值列清洗、条件过滤,并使用 openpyxl 对符合条件的单元格进行样式标记与导出。DocumenteFără avertismente★ 5,9 K↓ —
- create-blazor-projectdotnet/skillsCreate a new ASP.NET Core web application or web site using Blazor. USE FOR: creating a new Blazor web app, scaffolding a new web project, starting a new web site, choosing render modes (Static SSR, Interactive Server, Interactive WebAssembly, Auto), running dotnet new blazor with the right options, setting up initial project structure. DO NOT USE FOR: adding features to existing projects, changing how an existing app renders, or component authoring (use author-component).MediaFără avertismente★ 5,7 K↓ —
- pdf-analysisOpenSenseNova/SenseNova-SkillsPDF 文档解析。自动区分文字型 PDF 与扫描型 PDF,覆盖:文本/表格提取、多页全量扫描、嵌入图表 caption、单位感知数值计算。DocumenteFără avertismente★ 5,9 K↓ —
- sn-da-large-file-analysisOpenSenseNova/SenseNova-Skills万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取(iter_rows 支持 10 万行以上)、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**:①数据行数 ≥ 10k(由 sn-da-excel-workflow 的行数评估步骤触发);②用户出现触发词:大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing;③直接使用 pd.read_excel() 导致超时或内存溢出;④用户明确要求对大规模数据集进行高性能处理。仅不用于:小于 10k 行的常规 Excel 分析(使用 sn-da-excel-workflow 即可)。DocumenteFără avertismente★ 5,9 K↓ —
- sn-updateOpenSenseNova/SenseNova-SkillsUpdate SenseNova Skills (the sn-* bundle) inside an OpenClaw or hermes-agent install. ALWAYS use this skill when the user says any of: "update SenseNova skills", "update SN skills", "更新 sensenova skills", "更新 sn skills", "刷新 sn-*", "升级 sn-* skills", or names a specific sn-* skill to update (e.g. "更新 sn-ppt-standard", "refresh sn-image-base"). Default scope is the whole sn-* bundle; if the user names specific skills, update ONLY those.MediaFără avertismente★ 5,9 K↓ —
- mongodb-atlas-stream-processingmongodb/agent-skillsManages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.OficialInginerieFără avertismente★ 190↓ —Apare și în 3 alte depozite
- hunt-ntlm-infoelementalsouls/Claude-BugHunterHunt NTLM/Negotiate information disclosure on internet-reachable IIS/SharePoint/Exchange. Anonymous NTLM Type-2 challenge capture leaks NetBIOS domain, internal DNS forest, computer name, AD timestamp via AV_PAIRS structure. Default Windows-installer hostnames (WIN-XXXXXXXXXXX pattern) signal lazy provisioning. Use when target advertises `WWW-Authenticate: NTLM` or `Negotiate` headers anonymously.MarketingFără avertismente★ 5,3 K↓ —
- mirrord-upmetalbear-co/mirrordHelps users run multiple concurrent mirrord sessions from a single mirrord-up.yaml (compose-style multi-service local debugging). Use when the user mentions mirrord up, mirrord-up.yaml, mirrord up init, debugging several related microservices together, or managing multiple mirrord sessions' lifecycle in one command.InginerieFără avertismente★ 5,4 K↓ —
- hunt-dispatchelementalsouls/Claude-BugHunterSkill-set loader for /hunt orchestrator. Fingerprints the target, picks the right platform attack skills, and loads the Red Team or WAPT skill set. Use when /hunt has just received a mode answer (redteam or wapt + blackbox|greybox) and needs to load the appropriate skills and print the taxonomy. Not for direct user invocation.AlteleFără avertismente★ 5,3 K↓ —
- fetch-and-send-datadotnet/skillsCall APIs, load data into components, and handle the async lifecycle in Blazor. USE FOR fetching data from a backend, submitting data to an API, displaying loading/error states, registering HttpClient, building service abstractions for Auto/WebAssembly render modes. DO NOT USE for form validation (see collect-user-input), prerendering persistence (see support-prerendering), or project scaffolding (see create-blazor-project).MediaFără avertismente★ 5,7 K↓ —
- skill-authoringgrafana/skillsAuthor, audit, and improve Grafana SKILL.md files against Anthropic's published Agent Skills guidance and the four-dimension rubric the grafana/skills CI gate uses (conciseness, actionability, workflow clarity, progressive disclosure). Applies the canonical SKILL.md structure (YAML frontmatter + body + references/ + scripts/ + assets/), the "pushy description" trigger pattern, the three-level progressive-disclosure model, and the validate-fix-rerun feedback loop. Use when creating a new skill in this repo, when reviewing a skill PR, when a skill's Tessl review score is below 75 (the merge gate), when a skill's description isn't getting picked up by agents, when restructuring a long SKILL.md into a bundle, or when the user asks how to write, improve, optimize, audit, or fix a skill - even if they don't say "skill" explicitly (e.g. "this isn't triggering", "Tessl scored this 72", "split this doc").OficialRedactareFără avertismente★ 290↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for retool.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- mirrord-quickstartmetalbear-co/mirrordGuide users from zero to their first working mirrord session — check system requirements, install mirrord via CLI, VS Code, or IntelliJ, run a first session against a Kubernetes target, and verify the connection. Use when a user is new to mirrord, wants to install it, needs help running their first session, or wants to debug or test a local process against their Kubernetes cluster.TestareFără avertismente★ 5,4 K↓ —
- mirrord-chaosmetalbear-co/mirrordHelp users chaos test their app with mirrord: inject artificial latency or connection errors into a mirrord session's outgoing traffic via per-session chaos rules managed with the `mirrord chaos` CLI. Use when a user wants to add latency or delay to outgoing connections or a dependency (e.g. a slow database), simulate connection failures (reset, timed out, refused), test app behavior under degraded network conditions, or wire chaos rules into CI test runs. Always use this skill instead of the deprecated _experimental_.latency mirrord config option.TestareFără avertismente★ 5,4 K↓ —
- time-series-and-categorical-analysisOpenSenseNova/SenseNova-Skills对时间序列或分类数据进行多维度趋势分析、百分比清洗、绩效分级建模与预测,并生成高分辨率的可视化综合报告,适用于业务指标监控与预测场景。AlteleFără avertismente★ 5,9 K↓ —
- keyword-researchRyze-AI-Adgent/open-seo-mcp-skillsKeyword research from a seed topic — ideas, real Google volume/CPC, intent, difficulty, clustered into a plan. Use when asked to "find keywords", "keyword research for X", "what should I rank for", or "build a keyword plan".ȘtiințăFără avertismente★ 7 K↓ —
- mirrord-operatormetalbear-co/mirrordHelp users install and configure the mirrord Operator for team/enterprise environments. Use when users ask about operator setup, Helm installation, cloud API key or license configuration, air-gapped/offline licensing, enabling features (queue splitting, DB branching, preview environments, multi-cluster), internal registries, OpenShift/GKE Autopilot, RBAC, or multi-user mirrord deployments. Also use when an AI agent hits a Team or Enterprise feature on a cluster with no license and needs to offer the user a trial (agent-started trial; the trial is Enterprise tier).DevOpsFără avertismente★ 5,4 K↓ —
- marginaleffectsbrycewang-stanford/Auto-Empirical-Research-SkillsManual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.TestareFără avertismente★ 4,8 K↓ —
- oncall-irmgrafana/skillsRoute alerts, run on-call rotations, and drive incidents in Grafana IRM / OnCall — integrations (Alertmanager / Grafana Alerting / generic webhook / PagerDuty), Jinja2 routing + grouping templates, escalation chains (wait → notify schedule → notify team → webhook → auto-resolve), schedules (web + iCal + Terraform `grafana_oncall_schedule`), Slack chatops with Acknowledge/Resolve/Silence, and the P1-P4 incident lifecycle. Use when wiring Alertmanager to OnCall, deciding which team gets paged, building rotations from a Google Calendar / iCal, hooking up Slack notifications, or declaring an incident from an alert — even when the user says "page the platform team on critical alerts", "send Prometheus alerts to Slack", "set up our on-call rota", "escalation policy", or "auto-resolve when the alert clears" without naming OnCall / IRM. Heads up — OnCall OSS is in maintenance mode (archived March 2026); Grafana Cloud users should use IRM.OficialDevOpsFără avertismente★ 290↓ —
- pivot-table-cross-analysisOpenSenseNova/SenseNova-Skills利用交叉表与热力图对分类数据进行多维度占比分析,适用于奖项分布、绩效评估或市场占有率等结构化数据的清洗与可视化。AlteleFără avertismente★ 5,9 K↓ —
- statistical-distribution-and-outlier-analysisOpenSenseNova/SenseNova-Skills执行数值型数据的分布分析与异常值检测,支持通过正则表达式从文本中提取误差项并生成高分辨率的箱线图与直方图报告。AlteleFără avertismente★ 5,9 K↓ —
hunt-idor
elementalsouls/Claude-BugHunter
De la autor
Hunting skill for idor vulnerabilities. Built from 26 public bug bounty reports. Use when hunting idor on any target.
Instalare
npx skills add elementalsouls/Claude-BugHunter --skill hunt-idor -a claude-code
Se instalează în .claude/skills/hunt-idor/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (MIT) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
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