AGENT SKILLS · ÉQUIPEMENT DE MISSION
Des Agent Skills utiles classés selon leur usage réel
Comparez les Skills vérifiés par fonction, contenu, installations et fiabilité de la source avant de les ajouter.
- PÉRIMÈTRE
- VÉRIFIÉ
- Skills
- 17 520
- dépôts
- 2843
- dernière synchronisation
- 20 oct. 2026
phurynstartup-canvas
Generate a Startup Canvas combining Product Strategy (9 sections) and Business Model (costs + revenue) for a new product. An alternative to BMC and Lean Canvas that separates strategy from business model. Use when launching a new product or evaluating a startup concept.
- installations
- 2
- GitHub Stars
- 26,6 k
- Mis à jour
- 14 sept.
phurynsummarize-interview
Summarize a customer interview transcript into a structured template with JTBD, satisfaction signals, and action items. Use when processing interview recordings or transcripts, synthesizing discovery interviews, or creating interview summaries.
- installations
- 2
- GitHub Stars
- 26,6 k
- Mis à jour
- 14 sept.
phurynsummarize-meeting
Summarize a meeting transcript into structured notes with date, participants, topic, key decisions, summary points, and action items. Use when processing meeting recordings, creating meeting notes, writing meeting minutes, or recapping discussions.
- installations
- 2
- GitHub Stars
- 26,6 k
- Mis à jour
- 14 sept.
phuryntest-scenarios
Create comprehensive test scenarios from user stories with test objectives, starting conditions, user roles, step-by-step actions, and expected outcomes. Use when writing QA test cases, creating test plans, defining acceptance tests, or preparing for feature validation.
- installations
- 2
- GitHub Stars
- 26,6 k
- Mis à jour
- 14 sept.
phurynuser-stories
Create user stories following the 3 C's (Card, Conversation, Confirmation) and INVEST criteria with descriptions, design links, and acceptance criteria. Use when writing user stories, breaking down features into backlog items, or defining acceptance criteria.
- installations
- 2
- GitHub Stars
- 26,6 k
- Mis à jour
- 14 sept.
phurynvalue-proposition
Design a detailed value proposition using a 6-part JTBD template — Who, Why, What before, How, What after, Alternatives. Use when creating a value proposition, analyzing customer value delivery, or articulating why customers should choose your product.
- installations
- 2
- GitHub Stars
- 26,6 k
- Mis à jour
- 14 sept.
bergsideglassmorphism
Frosted glass effect with translucent layers, subtle blur, and luminous borders for depth and modern elegance.
- installations
- 2
- GitHub Stars
- 2,9 k
- Mis à jour
- 28 juin
spartan-ngspartan
- Manages spartan/ui, the Angular UI library - adding, composing, fixing, debugging, and styling UI with the Brain (headless primitives) and Helm (styled) layers. Provides project context, component APIs, and usage examples. Applies when working with spartan/ui, @spartan-ng/brain, @spartan-ng/helm, the @spartan-ng/cli generators, or any Angular project with a components.json file. Also triggers for "spartan init", "add a spartan component", or "set up spartan/ui".
- installations
- 2
- GitHub Stars
- 2,9 k
- Mis à jour
- 22 sept.
yonatangrossagent-orchestration
Agent orchestration patterns for agentic loops, multi-agent coordination, alternative frameworks, and multi-scenario workflows. Use when building autonomous agent loops, coordinating multiple agents, evaluating CrewAI/AutoGen/Swarm, or orchestrating complex multi-step scenarios.
- installations
- 2
- GitHub Stars
- 284
- Mis à jour
- 25 sept.
yonatangrossdomain-driven-design
DDD tactical patterns for complex business modeling including entities, value objects, aggregates, domain services, repositories, specifications, and bounded contexts. Python dataclass implementations with TypeScript alternatives. Use when building rich domain models, enforcing invariants, or separating domain logic from infrastructure.
- installations
- 2
- GitHub Stars
- 284
- Mis à jour
- 25 sept.
yonatangrosszustand-patterns
Reference for Zustand 5.x state management including slices, middleware, Immer, useShallow, persistence, selectors, and devtools integration. Documents 7 core patterns with TypeScript examples and anti-patterns. Use when building React state management with Zustand instead of Redux.
- installations
- 2
- GitHub Stars
- 284
- Mis à jour
- 25 sept.
mohitmishra786cross-gcc
Cross-compilation with GCC skill for embedded and multi-architecture targets. Use when setting up cross-gcc toolchains, configuring sysroots, building for ARM/AArch64/RISC-V/MIPS from an x86-64 host, troubleshooting wrong-architecture errors, or running cross-compiled binaries under QEMU. Activates on queries about cross-compilation triplets, sysroot, pkg-config for cross builds, embedded toolchains, or Yocto/Buildroot integration.
- installations
- 2
- GitHub Stars
- 231
- Mis à jour
- 27 juin
mohitmishra786device-drivers
Linux device driver skill for kernel driver development. Use when writing platform/i2c/spi drivers, char device lifecycle, IRQ handling, DMA engine API, regmap, power management, or udev rules. Activates on queries about platformdriver, requestirq, dmaalloccoherent, regmap, pmruntime, or char devices.
- installations
- 2
- GitHub Stars
- 231
- Mis à jour
- 27 juin
mohitmishra786device-tree
Device tree skill for Linux hardware description. Use when writing DTS/DTSI, bindings, overlays, phandles, or debugging OF platform probe failures. Activates on queries about device tree, DTS syntax, phandle, devicetree bindings, DT overlay, or OF graph.
- installations
- 2
- GitHub Stars
- 231
- Mis à jour
- 27 juin
mohitmishra786kernel-debugging-advanced
Advanced kernel debugging skill for ftrace, trace-cmd, perf, kprobes, kgdb, and crash analysis. Use when tracing kernel functions, profiling syscalls in kernel, dynamic instrumentation, or analyzing vmcore. Activates on queries about ftrace, trace-cmd, kprobe, kgdb, kernel crash dump, or dyndbg.
- installations
- 2
- GitHub Stars
- 231
- Mis à jour
- 27 juin
mohitmishra786linux-kernel-architecture
Linux kernel architecture skill for subsystem overview. Use when navigating kernel source, understanding boot flow, initcalls, or major subsystems (VFS, scheduler, MM). Activates on queries about kernel architecture, boot process, initcall levels, subsystem layout, or where code lives in linux.git.
- installations
- 2
- GitHub Stars
- 231
- Mis à jour
- 27 juin
mohitmishra786platform-device-model
Platform device model skill for Linux driver binding. Use when implementing platformdriver probe/remove, sysfs attributes, device properties, or deferred probe. Activates on queries about platformdevice, platformdriver, driver model, sysfs, probe remove, or Linux device bus.
- installations
- 2
- GitHub Stars
- 231
- Mis à jour
- 27 juin
mohitmishra786qemu-for-kernel-development
QEMU kernel development skill for driver and kernel testing. Use when booting custom kernels in QEMU, Buildroot/Yocto rootfs, virtio devices, or NFS root for driver iteration. Activates on queries about QEMU kernel dev, Buildroot QEMU, virtio block, kernel module test QEMU, or -append root=
- installations
- 2
- GitHub Stars
- 231
- Mis à jour
- 27 juin
smixshumanizer-ru
Редактор русского текста - убирает признаки AI-генерации, канцелярит и воду, сохраняя факты и добавляя голос. 38 паттернов AI-слопа с жёсткими запретами (негативные параллелизмы, длинное тире, математические знаки, техножаргон), детерминированным линтером и детектом артефактов копипаста из чат-ботов. Use when пользователь просит "отредактируй", "убери воду", "сделай живым", "humanize", "очисти от AI", "перепиши человечнее", говорит что текст "звучит как нейросеть", готовит AI-черновик к публикац
- installations
- 2
- GitHub Stars
- 175
- Mis à jour
- 23 sept.
scenario-labsscenario-orbit-views
Use when a single image of a character, creature, prop, vehicle, or building must be seen from new camera angles through the Scenario MCP server: turnarounds, a 360 orbit, views from behind, above, below, or straight down, consistent multi-angle renders on the same grounded background or on transparency, or novel views that go through a 3D intermediary instead of guessing.
- installations
- 2
- GitHub Stars
- 122
- Mis à jour
- 25 sept.
decathlonadd-cucumber-tests
Generates Tzatziki-based Cucumber BDD tests (.feature files) from a functional specification. Use this skill whenever a user wants to write Cucumber tests, add BDD scenarios, create feature files, generate tests, or test application behaviors with Gherkin — especially in Java/Spring projects using Tzatziki step definitions for HTTP, JPA, Kafka, MongoDB, OpenSearch, logging, or MCP. Also use when the user mentions writing integration tests, acceptance tests, or end-to-end tests in a project that
- installations
- 2
- GitHub Stars
- 87
- Mis à jour
- 21 sept.
tencentcloudbaseai-model-nodejs
Use this skill for Node.js backend AI via @cloudbase/node-sdk (=3.16.0) — cloud functions, CloudRun, Express/Koa/NestJS, serverless APIs, scheduled jobs, LLM proxies, agent orchestration. The only SDK supporting image generation (ai.createImageModel + generateImage). Text via ai.createModel with groups cloudbase, hunyuan-exp, or custom-; model ids (e.g. deepseek-v4-flash, glm-5, kimi-k2.6) go in the model field of generateText/streamText. MUST run two-step preflight before code — see body. NOT f
- installations
- 2
- GitHub Stars
- 77
- Mis à jour
- 24 sept.
tencentcloudbaseai-model-web
Use this skill when a browser/Web app (React, Vue, Next, Nuxt, static sites, SPAs, dashboards, AI chat UI, 页面, 前端, 网页) needs AI models via @cloudbase/js-sdk. Default routing for Web/frontend AI — call directly from the browser, do NOT propose a Node.js proxy. Covers generateText and streamText; models via ai.createModel with groups cloudbase, hunyuan-exp, or custom-, model id in the model field. MUST run two-step preflight before code — see body. NOT for Node.js backend (use ai-model-nodejs), Mi
- installations
- 2
- GitHub Stars
- 77
- Mis à jour
- 24 sept.
tencentcloudbaseai-model-wechat
Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI (小程序, wx.cloud apps). Covers generateText and streamText with callbacks (onText, onEvent, onFinish); streamText needs a data wrapper, generateText returns the raw response. Models via wx.cloud.extend.AI.createModel with groups hunyuan-exp (小程序成长计划), cloudbase (main managed), or custom-; model id goes in the data wrapper model field. MUST run two-step preflight before code — see body. NOT for browser/Web (use ai-model-web), Node.js
- installations
- 2
- GitHub Stars
- 77
- Mis à jour
- 24 sept.