Generate compelling social media summaries from SRT subtitle files, optimized for different platform characteristics to maximize engagement and reach.

Validates internet access, compares the locally installed pm-skills version against the latest public release, and updates local files with conflict-aware overwrite-or-skip options. Produces an update report listing changed files, skipped files, and new capabilities. Use when you want to bring a local pm-skills installation up to date.

Generates an evidence-calibrated product or marketing persona using the canonical v2.5 output contract. Use when shaping artifact perspective, stress-testing decisions, or framing product and GTM strategy.

Generates professional presentations from a JSON deck specification using 18 slide types with dark/light variants, content-to-layout decision logic, and calibrated character limits. Ships with a default professional theme and supports custom themes via utility-slideshow-themer.

basecamp

Spatial depth design with isometric views, vanishing points, and layered elements that guide attention through 3D-like realism.

Generate SITF-compliant attack flow JSON from red team or pentest reports. Accepts report files, URLs, or pasted findings. Use when documenting offensive security engagements.

Use this skill when the task is implementation-ready and requires code changes now.

Use this skill when external documentation, standards, or library comparisons are needed.

Use when asked to audit a module, check its health, or assess whether it should be refactored. Runs structural query, risk check, and test generation automatically.

Schema reference for comment enrichment. The enrichment workflow is printed by `wednesday-skills map` in the `[ENRICH]` block — follow those instructions.

> **Deprecated:** Gap filling is now part of `brownfield-fix`. When editing a file with coverage gaps, `brownfield-fix` automatically triggers gap resolution. Use `brownfield-fix` instead.

Operate the optional `grace` CLI against a GRACE project. Use when you want to lint GRACE artifacts, explain/remediate lint issues, check autonomy readiness, inspect project or module health, inspect verification entries, resolve modules from names or file paths, inspect shared/public module context, or inspect file-local/private markup through `grace lint`, `grace status`, `grace module`, `grace verification`, and `grace file show`.

Complete GRACE methodology reference. Use when explaining GRACE to users, onboarding new projects, or when you need to understand the GRACE framework - its principles, semantic markup, knowledge graphs, contracts, testing, and unique tag conventions.

Debug an issue using GRACE semantic navigation. Use when encountering bugs, errors, or unexpected behavior - navigate through the graph, verification plan, and semantic blocks to analyze the mismatch and apply a targeted fix.

Design and enforce testing, traces, and log-driven verification for a GRACE project. Use when modules need stronger automated tests, execution-trace checks, or a maintained verification-plan.xml that autonomous and multi-agent workflows can trust.

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Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.

Set up the Python backtesting environment. Detects OS, creates virtual environment, installs dependencies (openalgo, ta-lib, vectorbt, plotly), and creates the backtesting folder structure.

Generate or edit images via backend Skywork Image API. Use for any image creation, poster design, logo design, visual asset generation, or image modification request. Supports text-to-image and image-to-image editing with aspect ratio and resolution control.

Specify algorithms for Model-Based Design: system specs, architecture specs, implementation plans, test plans. Use when creating specifications for controllers, signal processing, diagnostics, estimators, or other algorithms authored in Simulink, Stateflow, System Composer, or MATLAB Function blocks.

Install and configure the Simulink Agentic Toolkit — detect platform, download and install the MCP server binary, register with your AI coding agent, and verify the environment. Supports Claude Code, Cursor, Codex, GitHub Copilot, Amp, and Gemini CLI.

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Diagnose MATLAB errors and unexpected behavior. Breakpoints, workspace inspection, try-catch diagnostics, and common error patterns. Use when debugging functions, tracing errors, inspecting variables, or diagnosing runtime failures.

Generate and run MATLAB unit tests using matlab.unittest and matlab.uitest. Parameterized tests, fixtures, mocking, coverage analysis, CI/CD with buildtool, app testing with gestures. Use when creating tests, writing test classes, running test suites, checking coverage, testing apps, or validating MATLAB code.

Install and configure the MATLAB Agentic Toolkit — detect MATLAB, install the MCP server, register with your AI coding agent, and verify the environment. Supports Claude Code, Cursor, Codex, GitHub Copilot, Amp, and Gemini CLI.

Automate web browsers for AI agents using agent-browser CLI with deterministic element selection.

Star all repositories from a GitHub user automatically. Use when: (1) Supporting open source creators, (2) Bulk discovery of useful projects, or (3) Automating GitHub engagement.

Translate text using free LibreTranslate API. Use when: (1) Translating content between languages, (2) Creating multilingual documentation, (3) Processing international data, or (4) Building translation workflows.

Rewrite AI-sounding text into natural, human writing by removing common LLM patterns while preserving meaning and tone.

Aggregate and deduplicate recent news from multiple sources into concise topic summaries.

Comprehensive WCAG compliance and accessibility testing covering ARIA, keyboard navigation, screen readers, color contrast, and automated a11y validation.

Comprehensive WCAG 2.1 AA compliance testing combining automated axe-core scans with manual keyboard navigation, screen reader compatibility, and focus management verification

Fast Rust-based headless browser automation CLI with Node.js fallback for AI agents, featuring navigation, clicking, typing, snapshots, and structured commands optimized for agent workflows.

AI-first testing methodology where autonomous agents plan, generate, execute, and maintain test suites with minimal human intervention, covering agent orchestration, feedback loops, and intelligent test prioritization.

Comprehensive evaluation patterns for AI agents including multi-turn conversation testing, LLM-as-judge frameworks, benchmark suites, regression detection, and systematic eval pipelines for measuring agent quality and safety.

AI-powered test orchestration skill covering intelligent test selection, risk-based test prioritization, flaky test management, test impact analysis, parallel execution optimization, and predictive test failure detection using machine learning.

Configure and generate rich Allure test reports with test categorization, historical trends, environment details, and CI/CD integration for comprehensive test visibility

Comprehensive API security testing based on OWASP API Security Top 10 including broken authentication, injection attacks, rate limiting, BOLA/BFLA vulnerabilities, and automated security scanning with ZAP and custom scripts.

Comprehensive website auditing skill using Lighthouse, PageSpeed Insights, and web performance APIs to audit performance, accessibility, SEO, best practices, and security.

Cloud-based cross-browser and cross-device testing with BrowserStack including Automate, App Automate, Percy visual testing, Observability, and integration with Playwright, Selenium, and CI/CD pipelines.

Fast test execution with Bun's built-in test runner including snapshot testing, mocking, code coverage, lifecycle hooks, DOM testing with happy-dom, and migration from Jest and Vitest to Bun test.

Map changelog entries and release notes to affected test cases, ensuring every user-facing change has corresponding test coverage verification.

Optimize CI test pipelines through intelligent test splitting, parallelization, caching strategies, and selective test execution based on code changes.

Evaluate interface complexity by measuring information density, decision points, visual hierarchy, and task completion paths to reduce user cognitive burden.

Systematically detect, capture, and categorize browser console errors, warnings, and unhandled exceptions during automated test execution

Generate consumer-driven contract tests using Pact framework to verify API provider-consumer compatibility and prevent integration breaking changes

Effective patterns for using GitHub Copilot to generate, refactor, and maintain test code including prompt engineering for test generation, Copilot Chat for debugging, inline suggestions for assertions, and workspace context optimization.