Validates documentation builds successfully. Use when checking Sphinx/RTD build integrity or diagnosing build failures. Reports errors, warnings, and build configuration issues.

Guide for building the tool when asked by the user or testing a code change that requires a new build of the tool

Determines which of PRD, ADR, UI Spec, Design Doc, and Work Plan a change requires, and where each is stored. Use when deciding documentation scope, or when creating or reviewing a technical document.

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.

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.

Writes pytest unit and integration tests for a use case's backend, against an ephemeral Postgres container, and updates the use-case-to-test traceability matrix. Use when the user asks to "write tests for UC-xxx", "add pytest coverage", "test the backend", or mentions unit tests, integration tests, or pytest for a specific use case.

Implements a use case's frontend: a React view, form, or grid wired to the backend API, covering the main flow and every alternative/failure flow. Use when the user asks to "implement the frontend for UC-xxx", "build the React view", "wire up the form", "add the page for", or mentions React implementation for a specific use case.

Scaffolds or extends a Terraform module for this project's AWS infrastructure, wired to input.yaml, tagged per the cost-allocation strategy, and following least-privilege IAM. Use when the user asks to "create a Terraform module", "provision the VPC/Aurora/Lambda/Cognito", "add infrastructure for", or mentions Terraform, IaC, or AWS resource provisioning for this project.

Writes Playwright end-to-end functional tests and visual regression baselines for a use case, and updates the use-case-to-test traceability matrix. Use when the user asks to "write E2E tests for UC-xxx", "add Playwright coverage", "add a visual regression test", or mentions end-to-end testing or screenshot testing for a specific use case.

Creates versioned Alembic migration scripts with tables, columns, primary keys, foreign keys, unique and functional constraints (e.g. case-insensitive uniqueness), and reference-data seeds, all derived from the entity model. Use when the user asks to "create a migration", "add a database migration", "write an Alembic migration", "add a column", "add a foreign key", "seed reference data", or mentions Alembic, schema migration, or database schema changes.

Use when asked to debug, fix a bug, investigate an error, or do root cause analysis, and when users report errors, stack traces, unexpected behavior, or say something stopped working.

List, find, and show Azure resources across subscriptions or resource groups. Handles prompts like "list the websites in my subscription", "list my web apps", "show my app services", "list virtual machines", "list my VMs", "show storage accounts", "find container apps", and "what resources do I have". USE FOR: list websites, list web apps, list app services, show websites in subscription, resource inventory, find resources by tag, tag analysis, orphaned resource discovery (not for cost analysis), unattached disks, count resources by type, cross-subscription lookup, and Azure Resource Graph queries. DO NOT USE FOR: deploying/changing resources (use azure-deploy), cost optimization (use azure-cost), or non-Azure clouds.

Run Google searches and fetch JS-rendered web pages as Markdown via `google-search-cli`, a Patchright-based CLI invoked through `uvx` from its GitHub repo (no local install needed). Use when the agent needs (1) fresh Google search results from a query, (2) the Markdown of a URL that plain HTTP fetch (curl/WebFetch) cannot render because it requires JavaScript or evades bots, or (3) inspection of the raw HTML of a Google results page. Trigger phrases include "google for ...", "search the web for ...", "fetch this page as markdown", "this page needs JS to render". Do not use for static doc URLs that WebFetch handles cleanly, or when Chromium cannot be installed on the machine.

Fetch transcripts and create structured watching guides / summaries for YouTube videos. Use when the user asks to (1) get, fetch, extract, or download a transcript or captions from a YouTube video URL, or (2) summarize, create a watching guide, or produce a structured summary of a YouTube video. Trigger on youtube.com/watch, youtu.be, or youtube.com/shorts links.

Runs Fastly Compute WASM binaries locally and serves as the authoritative reference for Compute platform internals. The fastlike source code is highly readable and covers the host ABI, caching and purging APIs, KV/config/secret store interfaces, rate limiting with counters and penalty boxes, ACL lookups, the full request lifecycle, backend fetch semantics, and a built-in per-request profiler with hostcall spans, backend waterfalls, native CPU samples, and optional deep metrics (body bytes, cache outcomes, header summaries, wasm heap curve). Use when working with Compute runtime internals or host calls, understanding how edge data stores behave at runtime, profiling local Compute apps, or testing WASM binaries locally. Prefer this skill over Viceroy for any non-Rust Compute work — its source code is easier to understand as a Fastly Compute API reference.

Configures, manages, and debugs the Fastly CDN platform — covering service and backend setup, caching and VCL, security features like DDoS/WAF/NGWAF/rate limiting/bot management, TLS certificates and cache purging, the Compute platform, and the REST API. Use when working with Fastly services or domains, setting up edge caching or origin shielding, configuring security features, making Fastly API calls, enabling products, or looking up Fastly documentation. Also applies when troubleshooting 503 errors or SSL/TLS certificate mismatches on Fastly, and for configuring logging endpoints, load balancing, ACLs, or edge dictionaries. Read the relevant reference file before writing any Fastly API call or curl command — request field names (e.g. the backend fields override_host, ssl_cert_hostname, ssl_sni_hostname, use_ssl) are easy to misremember, and a wrong name causes a silent 503 instead of an error, so do not rely on training-knowledge field names.

Runs Fastly Compute WASM applications locally with Viceroy, specifically for Rust and Component Model projects. Use when starting a local Fastly Compute dev server with Viceroy, configuring fastly.toml for local backend overrides and store definitions, running Rust unit tests with cargo-nextest against the Compute runtime, debugging Compute apps locally, adapting core WASM modules to the Component Model, or troubleshooting local Compute testing issues (connection refused, missing backends, store config). For non-Rust Compute work or understanding the Compute API, prefer the fastlike skill instead — its source code is easier to understand as a Fastly Compute API reference.

Executes Fastly CLI commands for managing CDN services, Compute deploys, and edge infrastructure. Use when running `fastly` CLI commands, creating or managing Fastly services from the terminal, deploying Fastly Compute applications, managing backends/domains/VCL snippets via command line, purging cache, configuring log streaming, setting up TLS certificates, managing KV/config/secret stores, checking service stats, authenticating with Fastly SSO, or working with fastly.toml. Also applies when working with Fastly service IDs in CLI context, or with `fastly service`, `fastly compute`, `fastly auth`, or any Fastly CLI subcommand. Covers service CRUD, version management, autocloning, and troubleshooting common CLI errors.

Lints, tests, simulates, and formats Fastly VCL code using the falco tool. Also serves as the authoritative VCL reference via the falco Go source, which implements Fastly's full VCL dialect. Use when validating VCL syntax, running VCL linting, testing VCL locally, simulating VCL request handling, formatting VCL files, writing VCL unit tests with assertions, debugging VCL logic errors, looking up VCL function signatures or variable scopes, understanding VCL subroutine behavior, or running `falco lint`/`falco simulate`/`falco test`/`falco fmt`. Also applies when working with VCL syntax errors, type mismatches in VCL, choosing which VCL subroutine to use, or setting up a local VCL development and testing environment.

Facilitates deliberate skill development during AI-assisted coding. Offers interactive learning exercises after architectural work (new files, schema changes, refactors). Use when completing features, making design decisions, or when user asks to understand code better. Triggers on "learning exercise", "help me understand", "teach me", "why does this work", or after creating new files/modules. Do NOT use for urgent debugging, quick fixes, or when user says "just ship it".