ai-project-starter-kit

Phase 2 - Clarify technical requirements from product specs. Requires product-adr.md as input. Outputs tech-adr.md. Use when running /technical-requirements, clarifying technical ADRs, or moving from product requirements to a fully-specified technical specification via research, approach selection, and 15 sequential categories.

Use when finding validated tiny iOS app ideas or explicitly validating a wedge for one opportunity from an existing App Tiny Bets report. Phase 1 performs keyword-first discovery with Astro and competitor evidence. Phase 2 runs only when explicitly requested with a report and one selected opportunity, then mines competitor reviews and creates a wedge brief.

Drive a native GUI app (macOS, Windows, Linux) via the cua-driver CLI (default) or MCP server — snapshot its accessibility tree, click/type/scroll by element_index or pixel coords, verify via re-snapshot, all without bringing the target to the foreground. Use when the user asks you to operate, drive, automate, or perform a GUI task in a real application on the host.

Orchestrate and judge an issue-to-PR pipeline without editing artifacts directly. Use when the user wants an issue-to-PR workflow, task-to-PR pipeline, or structured path from request to PR readiness. Routes each stage to the owning skill or subagent, checks gate outputs, asks for revisions when the pipeline drifts, and keeps PR as a placeholder.

Review agentic system quality with a lean heuristic gate. Use when auditing, approving, improving, or quality-checking skills, agents, prompts, or agentic workflows and a verdict is needed.

Reusable verification gate for completed work before commit or merge. Use when implementation is done and Claude must prove the task works, verify the main user flow, route verification by platform, and return a PASS/FAIL/BLOCKED verdict with evidence. Web and mobile-web verification uses agent-browser. iOS and macOS verification uses xcodebuildmcp-cli.

Fresh-subagent code quality review gate after implementation and before verification. Use when code changes are complete and the orchestrator needs APPROVE_CODE, REVISE_CODE, or ASK_USER based on plan fidelity, simplicity, tests, repo style, security, and maintainability. Does not implement or write files.

Research first SOP before implementing any code change. Use when starting any task that involves modifying an existing codebase features bugs refactors open source contributions. Triggers when I want to work on X help me implement or fix or refactor X gather relevant context for X lets work on this. Launches parallel atlas subagents for local codebase evidence plus voyager external signal research, then presents 3 ranked approaches minimal diff first for user approval before any code is written.

Lean standalone gate for reviewing create-issue plan artifacts before implementation. Use after `{ISSUE_DIR}/plan.md` exists to check format, proposal fidelity, actionability, and ETHOS alignment without doing architecture review or implementation.

Judge proposed approaches from a gather-context task artifact. Use after `{ISSUE_DIR}/issue.md` contains candidate approaches and research artifacts exist. Scores options against hard gates, ETHOS, and evidence; writes the selected decision back into issue.md or returns ASK_USER with one focused question. Does not implement anything.

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. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

Run adaptive iOS simulator localization QA for Expo or React Native apps across one or more locales. Use when the user wants to verify localized UI strings, capture locale screenshots, test onboarding/main app screens in Simulator, or repeat QA for newly added languages. Prefer this skill for multi-locale iOS QA even when the user does not explicitly say "skill".

When the user wants to analyze their own app's actual performance data from App Store Connect — downloads, revenue, IAP, subscriptions, trials, country breakdowns, analytics, or sales reports via the App Store Connect CLI. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For ASO keyword/ranking evidence, use Astro MCP. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.

When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.

When the user wants to analyze competitors' App Store strategy, find keyword gaps, or understand competitive positioning. Also use when the user mentions "competitor analysis", "competitive research", "keyword gap", "what are my competitors doing", or "compare my app to". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.

When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit.

When the user wants to optimize App Store metadata — title, subtitle, keyword field, or description. Also use when the user mentions "optimize my title", "ASO metadata", "keyword field", "character limits", "app description", or "write my subtitle". For keyword discovery, see keyword-research. For full ASO audits, see aso-audit.

Shape a messy workflow or system into one simple reliable flow. Use when the user wants to design a process, reduce brittleness, define owners, choose one source of truth, or turn an idea into a minimal operating model.

Autonomous App Store keyword optimizer — researches, audits, and updates metadata to improve organic search rankings.

Spec-in, content-out Reel renderer. Receives a complete production spec (format tier, topic, hook, CTA, caption, imagery direction) from the viral-ig-marketer orchestrator and produces a rendered .mp4 + caption file + metadata. Use this skill whenever you need to render a faceless Instagram Reel from a fully-defined spec. Trigger when creating Reels, rendering animations, or producing video from a production spec. Also trigger when referencing Remotion, fal.ai, video rendering, or motion graphics. This skill does NOT make creative decisions — format selection, virality scoring, caption writing, and content strategy are handled upstream by viral-ig-marketer. It validates the incoming spec, generates assets, renders via Remotion, saves the caption, and packages output.

Instagram growth orchestrator for any iOS app. Delegates research to viral-research and production to viral-producer. Owns the growth loop: pull analytics, select content direction from existing research briefs, run the virality gate, delegate rendering, send drafts to human via Telegram, reflect and update strategy. Pulls analytics via Instagram Graph API + RevenueCat every cycle and iterates experiments until MRR reaches the target. Use when running the marketing loop, checking analytics, or updating content strategy. Requires references/config.json to be filled before Cycle 0.

Search Reddit posts and comments with PullPush, then return citation-safe findings with direct Reddit URLs.

Viral content research and DNA extraction for Instagram Reels. Use this skill whenever you need to research what's performing in a niche on Instagram, find viral faceless Reels, download and analyze them frame-by-frame, identify patterns, and produce a structured research brief. Trigger whenever the user mentions viral content research, Instagram research, Reel analysis, content DNA, swipe file building, niche research, competitor analysis for social content, or wants to understand why certain content performs. Also trigger when the user wants to find content formats to adapt, study what's working in a niche, or build a research-backed content strategy. This skill is research-only — it does not generate or publish content.

Design a closed autonomous loop for a measurable goal. Use when the user wants to create an agentic loop, digital worker, autonomous operator, long-running agent, or SKILL.md that can observe act verify record and continue with minimal human intervention.

Lightweight SOP for reproducing bugs and proving whether a reported issue can be triggered. Use when Claude needs to reproduce a bug, validate a bug report, capture a repro video or screenshot, and return a clear REPRODUCED/NOT_REPRODUCED/BLOCKED result. When browser-based reproduction is needed, rely on the dogfood skill for browser setup, navigation, and evidence capture.

Root cause analysis for software bugs using the 5 Whys technique. Use when the user wants to find the underlying cause of a bug, error, or technical issue. Triggers include phrases like "why is this happening", "root cause", "debug this", or when investigating software problems.

Query local Astro Mac app database for ASO insights. Use when the user asks about keyword rankings, historical ranking data, trend analysis, competitor keywords, app ratings, keyword opportunities, or ASO health metrics.

Graph-aware triage engine for Beads projects.

Git commit workflow and message format. Use when making commits, asking about commit conventions, or after completing code changes. Enforces atomic commits with structured messages (type/scope/summary + what/why body).

Analyze GitHub repositories by converting to LLM-readable text. TRIGGER when user pastes github.com URL, asks "how does [library] work", or references external codebases. Supports public/private repos and subdirectories.

Import specific directories from external GitHub repos without cloning. Uses tarball extraction to pull only what you need. TRIGGER when user wants to copy files/folders from another repo.

Semantic code search using natural language queries. Use when users ask "where is X implemented", "how does Y work", "find the logic for Z", or need to locate code by concept rather than exact text. Returns file paths with line numbers and code snippets.

Setup and configure React Grab to let you click elements in your running app and send them directly to Claude Code for editing. Use when setting up React Grab, when the user wants to click UI elements to modify them, or mentions wanting visual element selection for development. Makes AI coding agents 66% faster.

React best practices and anti-patterns reference. Use when writing React components, reviewing code for anti-patterns, debugging useEffect issues, optimizing performance, or deciding between state vs derived values. Covers Effects, state design, component patterns, performance, and event handling.

Add and manage shadcn/ui components via CLI. Use when installing new UI components, building forms with validation, creating modals/dialogs/sheets, adding navigation menus, setting up data tables or charts, or updating existing shadcn components.

Manage concurrent background processes using tmux. Use when spawning dev servers, running long-running tasks, monitoring multiple processes, or capturing output from background commands without blocking the main session.