Инструменты: Frontend

A full development methodology for coding agents: brainstorm a design, break it into an implementation plan, dispatch subagents to build and review each task, with mandatory TDD and systematic debugging. Installed as a plugin, it injects its bootstrap automatically.

A complete development methodology for coding agents: brainstorm to clarify requirements, write an implementation plan, then build with subagents, with red-green TDD, systematic debugging and code review throughout. In the official Claude Code and Codex marketplaces.

Matt Pocock's engineering skills: grill-me interrogates you to align on requirements, to-spec turns discussion into a spec, to-tickets breaks it into tickets, plus tdd, diagnosing-bugs, code-review and more. Run setup-matt-pocock-skills once per repo first.

Matt Pocock's engineering skills: /grill-me interrogates requirements to align on intent, then a spec-and-ticket flow, TDD, code review and domain modeling. Small, composable skills, listed in the official Claude Code plugin marketplace.

Has the agent commit to a visual direction before building or redesigning an interface, making deliberate choices on color, type and layout instead of generic, templated AI UI. Official Anthropic skill.

Anthropic's terminal coding agent: understands your codebase, edits code, runs commands and handles git workflows, with plugins, MCP and a headless mode (claude -p). Sign in with a Claude account or set an API key.

Reviews pull requests with several parallel subagents, scores each finding by confidence to filter out false positives, and can post the results as PR comments. Official Anthropic plugin; requires a logged-in GitHub CLI.

Has the agent settle on a clear aesthetic direction first, then write distinctive, production-ready frontend interfaces that avoid the generic AI look. Official Anthropic plugin.

OpenAI's coding agent that runs locally, written in Rust: reads and writes code and runs commands inside an OS-level sandbox. Sign in with a ChatGPT plan or use an API key.

Persistent memory across sessions: hooks record tool calls and generate semantic summaries, then inject relevant context into new sessions, with history search and a web viewer. The hosted memory service needs sign-in, or use your own Anthropic plan or model key.

Injects up-to-date, version-specific docs and code examples for libraries and frameworks into the agent's context, so it stops using outdated or invented APIs. By Upstash; works anonymously, and a free API key raises the limits.

GitHub's official CLI: manage pull requests, issues, releases and Actions workflows from the terminal. Most commands support --json output that agents can parse, and an official agent skill is available. Run gh auth login first.

Lets agents drive a real browser through the accessibility tree: navigate, click, fill forms and take screenshots, without needing a vision model. Maintained by Microsoft.

GitHub's official MCP server: lets agents read and write repositories and code, manage issues and pull requests, and check Actions workflows and code-scanning alerts. Use the hosted remote server or run it locally in Docker; needs a personal access token or OAuth.

Figma's official remote MCP: hands components, variables and layout from your designs to the agent to generate code, and can create and edit designs on the canvas. Needs Figma sign-in; Starter plans and View or Collab seats get only 6 read calls a month.

Sets up an isolated workspace before feature work: uses the agent's built-in worktree tool when available, otherwise falls back to git worktree, then installs dependencies and runs baseline tests to confirm a clean start. From Superpowers.

Requires the agent to run the full verification commands and read the output before claiming work is done, fixed or passing, backing claims with evidence and ruling out unverified success reports. From the Superpowers workflow.

Before finishing a task or merging, dispatches an independent reviewer subagent over a git commit range to check the work against the plan and requirements, then handles feedback by severity: critical, important, minor. Part of obra/superpowers.

A four-phase root-cause debugging method: investigate the root cause, compare against working examples, test one hypothesis at a time, then fix the root cause. Guessing at code changes before locating the cause is not allowed. From the Superpowers workflow.

Once requirements or a spec exist and before touching code, writes multi-step work as a fine-grained implementation plan listing the files, interface signatures and tests to verify each step. A core Superpowers skill.

Before writing code, asks questions one at a time to clarify intent, constraints and success criteria, turning a vague idea into a reviewable design; implementation starts only after you approve it. A core Superpowers skill.

Test-driven development in vertical slices: agree on test seams with the user first, verify behavior only through public interfaces, and avoid listed anti-patterns such as implementation coupling and tautological tests. From Matt Pocock's skills collection.

A complete harness for coding agents: dozens of subagents, nearly 300 skills, hooks, rules, memory and continuous learning, plus the AgentShield security scanner. Built mainly for Claude Code, with Codex support.

A disciplined process for hard bugs and performance regressions: build a reliable reproduction loop, reproduce and minimize, form hypotheses, instrument to verify, then fix and add a regression test, redacting secrets in output. By Matt Pocock.