Discover and install skills, docs, and rules to enhance your AI agent's capabilities.
| Name | Contains | Score |
|---|---|---|
Wraps LaunchDarkly server-side SDK testing patterns: TestData data source for hermetic tests (no network), file-based data source for fixture-driven tests, flag override patterns (TestData.update for per-test flag values), and assignment-integrity tests. Use when writing tests for code that uses LaunchDarkly flags; to decide which flag combinations those tests should cover in the first place, see feature-flag-test-matrix-reference. Contains: launchdarkly-testing Wraps LaunchDarkly server-side SDK testing patterns: TestData data source for hermetic tests (no network), file-based data source for fixture-driven tests, flag override patterns (TestData.update for per-test flag values), and assignment-integrity tests. Use when writing tests for code that uses LaunchDarkly flags; to decide which flag combinations those tests should cover in the first place, see feature-flag-test-matrix-reference. | Skills | |
Interprets the results of a valid online controlled experiment, one whose harness, SRM, and telemetry have already been confirmed. Covers the distinction between practical and statistical significance, reading confidence intervals instead of binary p-values, novelty and primacy week-over-week decay that causes post-ship reversion, interaction effects from concurrent experiments, Simpson's paradox in segmented results, and the ordered guardrail-check sequence required before a ship decision - with the deep methodology in references/: the peeking problem and its corrections (fixed-horizon, alpha-spending, always-valid mSPRT) in references/peeking.md, and guardrail-metric methodology (taxonomy, OEC relationship, pre-commitment, thresholds) in references/guardrails.md. Use when a data scientist or PM is ready to draw conclusions from an experiment, when designing a stop-early policy, or when declaring an experiment's guardrail set. Distinct from ab-test-validity-checklist (harness setup and SRM detection). Contains: experiment-results-interpreter Interprets the results of a valid online controlled experiment, one whose harness, SRM, and telemetry have already been confirmed. Covers the distinction between practical and statistical significance, reading confidence intervals instead of binary p-values, novelty and primacy week-over-week decay that causes post-ship reversion, interaction effects from concurrent experiments, Simpson's paradox in segmented results, and the ordered guardrail-check sequence required before a ship decision - with the deep methodology in references/: the peeking problem and its corrections (fixed-horizon, alpha-spending, always-valid mSPRT) in references/peeking.md, and guardrail-metric methodology (taxonomy, OEC relationship, pre-commitment, thresholds) in references/guardrails.md. Use when a data scientist or PM is ready to draw conclusions from an experiment, when designing a stop-early policy, or when declaring an experiment's guardrail set. Distinct from ab-test-validity-checklist (harness setup and SRM detection). | Skills | |
v1.2.18 Authors Playwright `_electron` tests for packaged Electron desktop apps - launches the app via `electron.launch({ args })`, returns an `ElectronApplication` handle, drives renderer windows as Playwright `Page` objects, and probes the main process via `electronApp.evaluate(({ app, BrowserWindow }) => …)`. Distinct from ordinary browser page automation: this wraps the `_electron` API for launching packaged Electron apps and probing main + renderer processes. Includes the legacy Spectron reference and Spectron-to-Playwright migration shopping list (references/spectron-migration.md). Use for end-to-end tests of Electron apps where main-process state, IPC, and renderer DOM must all be asserted from one suite, or when migrating a deprecated Spectron suite. Contains: electron-playwright Authors Playwright `_electron` tests for packaged Electron desktop apps - launches the app via `electron.launch({ args })`, returns an `ElectronApplication` handle, drives renderer windows as Playwright `Page` objects, and probes the main process via `electronApp.evaluate(({ app, BrowserWindow }) => …)`. Distinct from ordinary browser page automation: this wraps the `_electron` API for launching packaged Electron apps and probing main + renderer processes. Includes the legacy Spectron reference and Spectron-to-Playwright migration shopping list (references/spectron-migration.md). Use for end-to-end tests of Electron apps where main-process state, IPC, and renderer DOM must all be asserted from one suite, or when migrating a deprecated Spectron suite. | Skills | |
Build-an-X for PCI DSS v4.0 scope verification - cardholder data environment (CDE) boundary tests, segmentation tests (PCI Req 1), prohibited-data-storage assertions per Req 3 (no full track data, no CVV/CAV2/CVC2/CID, no PIN/PIN block post-authorization), key-management tests per Req 3.6, encryption-of-transmissions per Req 4; includes the scope catalog (SAQ A / A-EP / D levels, PAN-storage rules, hosted-fields / tokenization scope-reduction patterns) in references/pci-scope.md. Use when authoring PCI DSS scope-reduction + control tests for any system handling payment-card data, or when determining a payment integration's SAQ level. Contains: pci-dss-control-test-author Build-an-X for PCI DSS v4.0 scope verification - cardholder data environment (CDE) boundary tests, segmentation tests (PCI Req 1), prohibited-data-storage assertions per Req 3 (no full track data, no CVV/CAV2/CVC2/CID, no PIN/PIN block post-authorization), key-management tests per Req 3.6, encryption-of-transmissions per Req 4; includes the scope catalog (SAQ A / A-EP / D levels, PAN-storage rules, hosted-fields / tokenization scope-reduction patterns) in references/pci-scope.md. Use when authoring PCI DSS scope-reduction + control tests for any system handling payment-card data, or when determining a payment integration's SAQ level. | Skills | |
Scores existing tests and evidence against a named compliance framework's criteria list (GDPR, CCPA/CPRA, SOC 2 Trust Services Criteria, HIPAA Security Rule, PCI DSS, ISO/IEC 27001), marking every criterion met, partial, not met, or not applicable with a stated evidence requirement per state, and recording each scope exclusion with its criterion reference, reason, named approver, and re-review date. Includes an adversarial readiness-review mode with hard refusal rules (never "ready" with an unjustified gap), and the ISO/IEC 27001:2022 Annex A per-control test-pattern catalog in references/iso27001.md. Produces a readiness self-assessment only: not certification, not an audit opinion, not legal advice. Use when a framework version has been named and an evidence set already exists, and someone needs a per-criterion readiness score before an observation period opens, before a qualified assessor arrives, or in response to a regulator inquiry. Contains: compliance-coverage-scoring Scores existing tests and evidence against a named compliance framework's criteria list (GDPR, CCPA/CPRA, SOC 2 Trust Services Criteria, HIPAA Security Rule, PCI DSS, ISO/IEC 27001), marking every criterion met, partial, not met, or not applicable with a stated evidence requirement per state, and recording each scope exclusion with its criterion reference, reason, named approver, and re-review date. Includes an adversarial readiness-review mode with hard refusal rules (never "ready" with an unjustified gap), and the ISO/IEC 27001:2022 Annex A per-control test-pattern catalog in references/iso27001.md. Produces a readiness self-assessment only: not certification, not an audit opinion, not legal advice. Use when a framework version has been named and an evidence set already exists, and someone needs a per-criterion readiness score before an observation period opens, before a qualified assessor arrives, or in response to a regulator inquiry. | Skills | |
Configures GitHub Actions test workflows - `.github/workflows/test.yml` with matrix builds (OS × runtime, with per-OS quirks - path separators, line endings, shells - and per-language runtime matrices in references/os-matrix.md), JUnit XML artifact upload, retry/sharding, services (PostgreSQL, Redis), per-trigger filtering (pull_request, push, schedule, workflow_dispatch). Use when the project hosts on GitHub and the team wants idiomatic GitHub Actions patterns for test workflows, or needs continuous cross-platform OS / runtime coverage. Contains: github-actions-test-jobs Configures GitHub Actions test workflows - `.github/workflows/test.yml` with matrix builds (OS × runtime, with per-OS quirks - path separators, line endings, shells - and per-language runtime matrices in references/os-matrix.md), JUnit XML artifact upload, retry/sharding, services (PostgreSQL, Redis), per-trigger filtering (pull_request, push, schedule, workflow_dispatch). Use when the project hosts on GitHub and the team wants idiomatic GitHub Actions patterns for test workflows, or needs continuous cross-platform OS / runtime coverage. | Skills | |
v1.7.4 Configures Behave for Python BDD scenarios - `pip install behave`, authors `.feature` files in Gherkin, writes step implementations in `features/steps/*.py`, configures via `environment.py` for setup/teardown hooks, organizes via tags, runs via `behave`. Use for Python codebases that want Cucumber-family BDD without Cucumber-Ruby / Cucumber-JS. Contains: behave-testing Configures Behave for Python BDD scenarios - `pip install behave`, authors `.feature` files in Gherkin, writes step implementations in `features/steps/*.py`, configures via `environment.py` for setup/teardown hooks, organizes via tags, runs via `behave`. Use for Python codebases that want Cucumber-family BDD without Cucumber-Ruby / Cucumber-JS. | Skills | |
Generates tests from natural-language specs (acceptance criteria, user stories, requirements) using an LLM, with confidence scoring per test case (LLM self-assessment plus heuristics: assertion quality, naming, completeness), batching uncertain cases for human review, and integration with the team's existing test framework. Use when the user asks to generate unit tests from acceptance criteria, convert user stories to test cases, automate test creation from requirements, or augment a spec-driven test suite with AI-generated stubs that are then curated before merge. Contains: ai-test-generator Generates tests from natural-language specs (acceptance criteria, user stories, requirements) using an LLM, with confidence scoring per test case (LLM self-assessment plus heuristics: assertion quality, naming, completeness), batching uncertain cases for human review, and integration with the team's existing test framework. Use when the user asks to generate unit tests from acceptance criteria, convert user stories to test cases, automate test creation from requirements, or augment a spec-driven test suite with AI-generated stubs that are then curated before merge. | Skills | |
v1.3.11 Builds a CI gate that fails the build on **new** WCAG / a11y violations introduced by a PR while grandfathering pre-existing violations on a per-rule / per-page baseline. Aggregates verdicts from axe-core / pa11y / Lighthouse a11y / WAVE / IBM Equal Access scans. Use when a project has accumulated a11y debt and a strict \"zero violations\" gate would block every PR - the ratchet pattern lets the team ship while preventing regressions. Contains: a11y-violation-gate Builds a CI gate that fails the build on **new** WCAG / a11y violations introduced by a PR while grandfathering pre-existing violations on a per-rule / per-page baseline. Aggregates verdicts from axe-core / pa11y / Lighthouse a11y / WAVE / IBM Equal Access scans. Use when a project has accumulated a11y debt and a strict "zero violations" gate would block every PR - the ratchet pattern lets the team ship while preventing regressions. | Skills | |
Teaches web end-to-end testing from first principles: what browser-driven E2E covers and how it differs from unit and integration tests, a decision table for choosing between Playwright, Cypress, Selenium WebDriver, WebdriverIO, Puppeteer, TestCafe and the BrowserStack / Sauce Labs / LambdaTest cloud grids based on files already present in the repo, install and first-run commands for each, and the flakiness traps (fixed sleeps, CSS and XPath selectors, state shared between tests) that sink new suites. Use when a web application has no E2E coverage yet, when picking or replacing an E2E framework, or when a first browser test needs to go green end to end. Contains: web-e2e-overview Teaches web end-to-end testing from first principles: what browser-driven E2E covers and how it differs from unit and integration tests, a decision table for choosing between Playwright, Cypress, Selenium WebDriver, WebdriverIO, Puppeteer, TestCafe and the BrowserStack / Sauce Labs / LambdaTest cloud grids based on files already present in the repo, install and first-run commands for each, and the flakiness traps (fixed sleeps, CSS and XPath selectors, state shared between tests) that sink new suites. Use when a web application has no E2E coverage yet, when picking or replacing an E2E framework, or when a first browser test needs to go green end to end. | Skills | |
neo4j-contrib/neo4j-skills Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package. | Skills | |
yahsan2/static-admin Refactor HTML/TSX files to use existing UI components, DaisyUI classes, and semantic colors. Use when (1) refactoring React/TSX page components to use reusable UI components, (2) replacing raw HTML elements with component library equivalents, (3) converting primitive Tailwind colors to semantic DaisyUI colors, (4) extracting repeated styling patterns into components. | Skills | |
shockz09/uni-cli Twilio SMS messaging via uni CLI. Use when user wants to send SMS, check message status, or list sent messages. Requires TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN, and TWILIO_PHONE_NUMBER. | Skills | |
shockz09/uni-cli Trello boards, lists, and cards via uni CLI. Use when user wants to manage Trello tasks, create boards, move cards between lists. Requires TRELLO_API_KEY and TRELLO_TOKEN. | Skills | |
shockz09/uni-cli Productivity tools via uni CLI. Use when user wants to send Slack messages, search Notion, manage Linear issues, or handle Todoist tasks. Services: slack, notion, linear, todoist. | Skills | |
jpoutrin/product-forge Django development patterns and conventions (2025). Auto-loads when working with Django models, views, URLs, forms, templates, management commands, or project structure. Includes async support and type hints. | Skills | |
jpoutrin/product-forge Django API development for 2025. Covers Django Ninja (modern, async-first, type-safe) and Django REST Framework (mature, ecosystem-rich). Use when building REST APIs, choosing between frameworks, implementing authentication, permissions, filtering, pagination, or async endpoints. | Skills | |
jpoutrin/product-forge Git commit best practices with conventional commits format and atomic commit principles. Use when committing code to ensure clear, meaningful commit history with proper type prefixes and semantic versioning support. | Skills | |
dandye/ai-runbooks Hunt for lateral movement using PsExec, WMI, or similar techniques. Use when proactively searching for attackers moving through your network using admin tools. Searches for service installations, remote process execution, and suspicious network correlations. | Skills | |
dandye/ai-runbooks Hunt for credential access techniques like LSASS dumping or browser credential theft. Use when searching for evidence of credential harvesting. Takes MITRE technique IDs and searches for behavioral indicators in SIEM. | Skills |
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