3 535 testing skills from 425 authors. They run test suites, check accessibility and catch what broke. Half of them fit into 1 800 tokens or less — that is what one costs your context window when the agent loads it. 404 ship runnable scripts rather than instructions alone. 2 of them cannot work without an MCP server, most often rube. We also found 403 copies of these same skills sitting in other people's repositories — counted once here, not 403 times.
3 535 unique 425 authors 2 151 updated this month 319 from vendors
>- Converts end-to-end (e2e) test targets or paths to `bazel run` commands for `heir-opt`. Use when you need to convert an e2e test target (where flags are defined in the BUILD file) to a shell command whose flags can be modified for further analysis and debugging.
>- Converts MLIR lit test files to `bazel run` commands. Use when you need to convert a failing MLIR lit test target (containing RUN lines) to a shell command whose flags can be modified for further analysis and debugging.
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
Debug computerd in real-FUSE mode end-to-end without workerd, vitest-pool-workers, or wrangler in the loop. Boot the linux-x64 binary in a privileged docker container, drive its capnweb /ws endpoint from Node, simulate DO-side sync from a SQLiteTestStorage, and isolate FUSE-related deadlocks. Load when a real-FUSE bug reproduces locally but unit tests pass, when the harness vitest tests hang against a real container, or when you need to attribute a wedge to FUSE vs sync vs exec.
> Post-migration quality review. Checks Java test files produced by migrate-groovy-to-java against the shared quality rules. Use after migration, or on any branch with recently migrated .java test files. Produces structured FINDING blocks grouped by severity, then offers to auto-fix BLOCKERs and WARNINGs.
依据真实 OpenAPI、路由实现和现有测试生成并验证 API 测试。用于用户要求测试接口、补集成测试、验证 API 契约、生成回归用例或排查接口兼容性时；区分“生成测试”和“执行请求”的授权，不猜测状态码、响应结构或 SLA，不在未确认环境中发送写请求。
分析真实项目并生成或修订安全、可验证的 GitHub Actions workflow；当用户要求创建 CI、测试矩阵、构建、Release、部署、缓存、Secrets、OIDC、PR 自动化或排查 workflow 配置时使用
依据真实代码契约生成并验证单元测试或集成测试。用于用户要求为函数、类、接口或缺陷补测试、提高覆盖率、生成回归用例或完善测试策略时；先读取现有测试与调用方，不猜测空值、异常或超时行为，不自动安装框架或访问生产依赖。
Strix JWT 与 OIDC 安全测试手册,覆盖令牌伪造、算法混淆与声明篡改;触发名:strix-authentication-jwt
给中文用户和新手用的 Strix Lite 统一入口：先判断该用哪一个 strix-* 工具或漏洞测试 skill，再给最小化起手步骤；适合在 Web 安全测试、工具链使用、漏洞验证时不知道先用哪个 Strix skill 的场景;触发名:strix-beginner-hub
Strix 功能级授权缺陷测试手册,覆盖操作级权限失效、管理功能越权与 API 操作绕过;触发名:strix-broken-function-level-authorization
Strix 业务逻辑漏洞测试手册,覆盖流程绕过、状态操控与领域约束破坏;触发名:strix-business-logic
Strix CSRF 测试手册,覆盖 token 绕过、SameSite、CORS 误配与状态变更滥用;触发名:strix-csrf
Strix ffuf 模糊测试命令手册,覆盖匹配器、过滤器与自动化友好参数;触发名:strix-ffuf
Strix IDOR/BOLA 测试手册,覆盖对象级授权失效与跨账户数据访问;触发名:strix-idor
Strix 信息泄露测试手册,覆盖报错、调试端点、元数据泄露与源码暴露;触发名:strix-information-disclosure
Strix 文件上传安全测试手册,覆盖扩展名绕过、Content-Type 操控与路径穿越;触发名:strix-insecure-file-uploads
Strix 开放重定向测试手册,覆盖钓鱼跳转、OAuth 令牌窃取与白名单绕过;触发名:strix-open-redirect
Strix 路径穿越与文件包含测试手册,覆盖本地/远程文件访问与代码执行链;触发名:strix-path-traversal-lfi-rfi
Strix 快速安全评估模式,面向高影响漏洞的限时测试;触发名:strix-quick
Strix RCE 测试手册,覆盖命令注入、反序列化、模板注入与代码求值;触发名:strix-rce
Strix SQL 注入测试手册,覆盖 union、blind、error-based 与 ORM 绕过技巧;触发名:strix-sql-injection
Strix SSRF 测试手册,覆盖云元数据访问、内网服务发现与协议走私;触发名:strix-ssrf
Strix XSS 测试手册,覆盖反射型、存储型、DOM 型向量与 CSP 绕过;触发名:strix-xss
>- Assesses the production viability of findings, filtering out debug-only features and assertion traps. Use when findings have been validated and you need to confirm they are triggerable in production release builds (with assertions disabled). Don't use for writing reproduction scripts or patches.
Write high-quality JUnit 5 tests with AssertJ assertions. Use when user says "add tests", "write tests", "improve test coverage", or when reviewing/creating test classes for Java code.
Design A/B and multivariate tests. Use when: sample size calculation, testing hypothesis, CRO experimentation.
Design structured ad creative tests with A/B test plans, multivariate creative strategies, sample size calculations, and iteration cadences. Use when planning creative testing for ads, optimizing creative performance, or building a testing playbook across advertising platforms.
Run synthetic focus groups. Use when: testing messaging, pricing, or positioning before live research spend.
Test message variants on synthetic audiences. Use when: predicting response rates, sentiment, or objections before live tests.
A/B test content variations. Use when: comparing quality scores across prompt approaches, headline styles, or content versions.
Generate quality trends report. Use when: reviewing eval scores over time, content type performance, or regression alerts.
Simulate revenue impact via Monte Carlo. Use when: testing channel mix changes, budget shifts, or new channel launches.
Compare budget scenarios side-by-side. Use when: testing 2-4 allocation variants with projected outcomes.
> Pull and interpret production experiment query-performance data from the staff-only slowest experiment queries, precompute read/build health, and preaggregation cache footprint. and response field semantics (exception codes, exposure paths, precompute skip reasons, job states). Use when investigating slow or failing experiment queries, precompute regressions, 307/159/241 errors, preaggregation table growth, or when asked how experiment query performance or the precompute rollout is doing in production.
> Guides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo. Stabilizing is not the only valid outcome — the skill also gates whether the test should exist, so deleting a test that catches nothing real, or re-leveling one that flakes because of the level it runs at, are first-class endings.
> When and how to add scenarios, chaos events, and invariants to the personhog e2e test harness (rust/personhog-test-harness). Use after fixing a bug or regression in the personhog leader path (leader, router, writer, replica, coordination protocol) so the fix gets a permanent regression scenario; when adding a new failure mode to test (crashes, drains, zombies, lag, failover); or when a new correctness property needs asserting during runs. Trigger handoff bug, eviction, writer lag, acked write.
> Internal PostHog developer frontend/browser QA skill. Use only when a PostHog developer explicitly asks to run frontend QA, browser-test a PR, verify a UI flow against the local PostHog stack, use qa-frontend, or QA current frontend changes with browser/runtime evidence. Do not use for generic code review, PR review, "check my changes", CI debugging, or security audit; use qa-team, debugging-ci-failures, or security-audit instead. Runs in PR mode or local mode, plans adaptive browser and visual checks, drives browser MCP/tooling such as Playwright MCP or Chrome DevTools MCP, captures evidence, and applies only approved/narrow fixes.
Use when writing a Storybook story for a component gated on a feature flag — boolean flags or multivariate/experiment-arm variants. Covers the `featureFlags` story parameter and why imperatively setting flags renders the flag-off branch in visual-regression snapshots while passing in jest.
> Teaches how to write and run evals on the `products/posthog_ai/eval_harness/` harness — sandboxed agent suites that execute the real coding agent in a Docker or Modal sandbox against a seeded Hedgebox project, and one-shot suites that score a single in-process model invocation per case. Use when adding or changing eval suites, cases, scorers, seeders, or synthesizers under `products/posthog_ai/evals/` or `products/*/evals/`, when touching the harness under `products/posthog_ai/eval_harness/`, or when running or debugging those evals (`hogli evals`). Covers suite kinds and discovery, case anatomy, the seeder/synthesizer split, the one-branch scorer patterns, and how to read results. Not for `ee/hogai/eval/ci/` pytest evals, and not for the LLM Analytics product's evaluation features.
> Gates whether a new test should exist and forces it to be efficient, protecting CI from low-value test bloat. Use before adding or substantially changing any pytest, Jest, or Playwright test — whenever an agent or engineer is about to write tests for a new feature, bugfix, or PR. Front-loads the value bar (every test must catch a realistic regression no existing test already catches; test behavior through the public interface, not implementation details; collapse near-duplicates into parameterized cases) and the efficiency bar (deterministic, isolated, fast; pick the cheapest test level; Django TestCase over TransactionTestCase; no sleeps, no real network). Includes a "don't write it" decision tree. For fixing an existing flaky test use `/fixing-flaky-tests`; after this gate says a Playwright test is warranted, use `/playwright-test` for mechanics.
Expert knowledge for Azure App Testing development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure Load Testing with VNets/private endpoints, JMeter/Locust, Playwright Workspaces, CI/CD, or quotas, and other Azure App Testing related development tasks. Not for Azure Test Plans (use azure-test-plans), Azure DevOps (use azure-devops), Azure Pipelines (use azure-pipelines), Azure App Service (use azure-app-service).
Expert knowledge for Azure Test Plans development including limits & quotas, security, and integrations & coding patterns. Use when tuning test retention, configuring access for manual testers, or automating suites via tcm.exe CLI, and other Azure Test Plans related development tasks. Not for Azure DevOps (use azure-devops), Azure Boards (use azure-boards), Azure Pipelines (use azure-pipelines), Azure App Testing (use azure-app-testing).
Integration and E2E test design principles, ROI calculation, test skeleton specification, and review criteria. Use when designing integration tests, E2E tests, or reviewing test quality.
Implements React/TypeScript unit, integration, and browser E2E tests with the repository's configured runner, mocks, setup, and browser harness. Use when creating or completing frontend tests and generated test skeletons.
Language-agnostic testing principles including TDD, test quality, coverage standards, and test design patterns. Use when writing tests, designing test strategies, or reviewing test quality.
Add integration/E2E tests to existing codebase using Design Docs
Verifies the work plan is implementable end-to-end and resolves verification-lane / fixture / E2E-environment gaps before the build phase begins. Use when "implement-ready/verification readiness/lane setup/E2E environment missing" is mentioned, or before any build phase begins on a work plan whose readiness has not been preflight-checked.