cook
Implement, build, create, or add any feature, endpoint, page, component, or functionality. Use this skill whenever the user asks you to write new code or make code changes — whether it's adding an API endpoint, building a UI page, creating an export feature, wiring up a webhook, implementing a search/filter, or any other hands-on coding task. This is the default skill for all 'build this', 'add this', 'create this', 'wire up', 'implement' requests. Covers the full cycle: clarify requirements, plan if needed, write code, verify, and review. Do NOT use for pure research, debugging, documentation, or explanation — only when the user wants working code delivered.
git clone --depth 1 https://github.com/avibebuilder/claude-prime /tmp/cook && cp -r /tmp/cook/.claude/skills/cook ~/.claude/skills/cookSKILL.md
ultrathink. ## How cook works Cook is an incremental loop: break work into tasks, implement one, verify it works, move to the next. The key discipline is that nothing is "done" until there's evidence it works — but *how* you verify adapts to the situation. ## Before you start If the request is clear, start. If it's ambiguous or multi-faceted, ask clarifying questions. If the work is large or multi-path, plan first (`/give-plan`). Otherwise, just start. ## The loop ### 1. Break into tasks only when it helps For a small single-concern request, just implement, verify, and continue. For multi-step work or collaboration, use `.claude/scripts/tasks.py` to track concrete outcomes. Task files persist in `.tasks/`, so a fresh context can pick up where the last one left off. Every task requires three fields: `title`, `desc`, `expected`. Read the authoring rubric before writing tasks — bad tasks are worse than no tasks: - `.claude/scripts/tasks.py --help` for the short-form rubric and examples - `.claude/scripts/tasks-authoring.md` for the full guide ``` .claude/scripts/tasks.py --task-file <slug> add "<title>" "<desc>" "<expected>" .claude/scripts/tasks.py --task-file <slug> list .claude/scripts/tasks.py --task-file <slug> verify <id> "<evidence>" .claude/scripts/tasks.py --task-file <slug> done <id> ``` ### 2. Implement → Verify → Review → Next Pick the next unblocked task, make the change, then hand off to a **tester** and (for risky work) a **reviewer** — isolated teammates that judge the change independently. See `.claude/skills/test/teammate.md` and `.claude/skills/review-code/teammate.md` for how to spawn them. `/cook` owns implementation. The tester owns verification. Give the tester: - the user-visible claim or acceptance criteria - the files or behavior you changed - the most likely regression surface - any constraints that matter You can still add durable tests, fixtures, or stable selectors when they belong to the product change itself. Do not stuff temporary verification tactics into `/cook` just to get through one run. Before invoking verification, confirm the edits actually landed on disk. If the change you expect is missing from the diff, fix that first; a passing check against unchanged code is worthless evidence. Do not mark a task done on confidence alone. The tester proves the behavior. The reviewer checks that the implementation is correct, scoped, and aligned with the repo. For risky or non-trivial work, spawn a reviewer before marking the task complete. Update task status as you go so the execution trail stays trustworthy. ### 3. Review the whole change set After the task list is complete, review the combined diff before declaring success. Cross-task issues often appear only in the final aggregate: mismatched assumptions, naming drift, incomplete ripple updates, or verification that was too narrow. Spawn a reviewer for this final pass. ### 4. Report When done, summarize: - what changed - how each claim was verified - decisions that materially shaped the implementation - any follow-up the user should know about ## Request <request>$ARGUMENTS</request>
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Answer questions about code, architecture, and technical decisions — no implementation. Trigger on questions asking 'why', 'what does this do', 'what is the purpose of', 'explain', 'what's the difference', 'compare', or 'what are the tradeoffs' — even when referencing specific files, code snippets, or inline code. The key signal is the user wants to UNDERSTAND something, not change it. Do NOT trigger for requests to build, fix, plan, review, research, or add/modify code.
Use when the user wants to save knowledge as a file so others don't have to rediscover it — \"turn this into a doc\", \"write this up\", \"document how X works\", \"we figured this out and want to capture it\", \"nobody should have to figure this out again\". Covers any request to create or update durable written artifacts: onboarding guides, runbooks, ADRs, API docs, architecture notes, postmortems, changelogs, setup guides. The trigger: user wants knowledge captured in a file for future reference, not just a conversation. Do NOT use when still making decisions (→ give-plan), just asking for explanation without a file (→ ask), or writing code (→ cook).
Investigate unexpected behavior and mysterious bugs. Use when the cause of a problem is unknown and the user needs to understand WHY something is happening — symptoms like: sudden unexplained changes in metrics or behavior, works locally but not in staging/production, inconsistent or intermittent failures, correct code producing wrong results, operations succeeding but having no effect, environment-specific failures, duplicate executions, stale data, or any \"why did this change?\" or \"why is this happening?\" situation. Covers infrastructure anomalies (cache hit rates dropping, latency spikes, queue behavior shifts) as well as code bugs. The key signal is confusion about root cause, not a request to implement a known fix. Do NOT use for feature requests, known fixes, planning, or documentation tasks.
Brainstorms and debates approaches, then drives toward an actionable decision. Use whenever someone needs a thinking partner for a decision they're facing: 'discuss', 'debate', 'brainstorm', 'weigh options', 'tradeoffs', 'should I do X or Y', 'help me decide', 'I'm torn between', 'sanity check my thinking', or 'what do you think about'. The user must be asking for help reasoning through a choice — not asking to build, fix, evaluate, plan, or modify something (even if the topic involves this skill itself). Picks the right decision lens, surfaces tradeoffs and blind spots, pushes back when reasoning is genuinely weak, and never implements.
Fetch up-to-date documentation for any library, framework, API, or service into context. Use when the user wants to look up API references, check function signatures or required fields, find feature-specific docs, or verify how an external tool actually works. Triggers for queries about third-party libraries like Stripe, SQLAlchemy, Tailwind, FastAPI, shadcn, Drizzle, Hono, Better Auth — any time the answer lives in official docs rather than in the project codebase. Use this instead of guessing from trained knowledge, which is stale.
Fix bugs and broken behavior when there is enough evidence to act on a repair path. Use for errors, crashes, incorrect results, API failures (500, 404, 403), CORS problems, database exceptions, broken rendering, duplicated or wrong data, off-by-one mistakes, timezone/date bugs, broken forms, config-caused runtime failures, and regressions. Trigger when the user wants the bug repaired and the conversation already contains a clear failing area, a reproducible failing test, a concrete error path, or a prior diagnosis to implement. Do NOT use for new features, pure explanation, architecture discussion, broad research, or bug reports where the main need is figuring out why the behavior happens — use diagnose for that.
Builds distinctive, production-grade UIs that avoid generic AI aesthetics. Use whenever the user wants to build, restyle, or give visual direction to any interface — pages, dashboards, landing pages, components, onboarding flows, mobile screens, or design systems — even without an explicit 'design' request. Also triggers for: picking an aesthetic direction, improving the look of a dull/generic existing page, adding visual personality, or choosing colors/typography. Includes a bundled design intelligence database for concrete guidance across web (React, Next.js, Vue, Tailwind) and mobile (React Native, Flutter, SwiftUI).