lemon-ai-hub

WCAG 2.1 AA/AAA accessibility audit for web components, pages, and apps. Detects contrast failures, missing ARIA labels, keyboard trap issues, focus order problems, and screen-reader gotchas. Use when user wants to audit accessibility, fix a11y warnings, prepare for compliance review, or validate UI against WCAG standards.

A comprehensive plugin for creating and verifying Agent SDK applications in Python and TypeScript.

Agentic Value Loops plugin — Continuous improvement engine that ships verified increments with constant quality. Includes loops for Feature Development, Maintenance & Security, Documentation Sync, and AI Tuning.

Project and workspace AI setup orchestrator. Builds AGENTS.md/CLAUDE.md contracts, optional global or project skills, Spotify Squad-style agent/subagent topology, and adversarial setup review for single apps, monorepos, and multi-domain workspaces.

API Test Loop plugin — Automated REST API validation loop. Executes HTTP requests via CURL, logs findings for REST best practices (method, input/output format, security, performance, docs), and implements backend fixes.

Apple Store Connect API Expert Agent and Skills. Provides comprehensive tools and knowledge for interacting with the App Store Connect API, covering domains like TestFlight, In-app purchases, Subscriptions, App management, and Provisioning.

AI release agent for the Apple App Store. Audits Expo/React Native iOS builds, App Store metadata, App Privacy readiness, TestFlight, RevenueCat/IAP, Firebase, i18n parity, screenshots, and review notes, then emits a GO/GO_WITH_WARNINGS/NO_GO decision with full risk + privacy + IAP reports. Never submits to App Review or alters the store without explicit human approval. Generic core with presets for Expo/RN/Firebase/RevenueCat apps.

Async and concurrency pattern advisor for JavaScript/TypeScript, Python, Go, and Rust. Identifies race conditions, missing error handling in promise chains, N+1 async anti-patterns, unbounded parallelism, and missing cancellation. Recommends correct patterns: Promise.all, p-limit, AbortController, AsyncLocalStorage, worker threads. Use when async code has bugs, timeouts, or memory leaks.

JavaScript/TypeScript bundle size analysis, tree-shaking audit, and code splitting recommendations. Identifies heavy dependencies, duplicate packages, unused imports, and suggests dynamic imports and lazy loading. Use when bundle is too large, Lighthouse score is low, or user wants to optimize web app loading performance.

Chaos engineering scenarios for resilience testing. Designs fault injection experiments (network partitions, latency injection, dependency failures, disk pressure, memory leaks) and verifies circuit breakers, retries, and fallbacks work correctly. Use when building resilience features, verifying SLO under failure conditions, or preparing for production chaos days.

Reusable closed loop for exploratory QA over any live web app, driven by Claude via the Chrome DevTools MCP with four expert lenses (QA, Product, Engineering, Security). Read-only on production, writes one markdown report per finding immediately, and hands reviewed findings to a triage agent that emits prioritized tasks + per-fix PLAN stubs.

Design or review CLIs so coding agents can run them reliably: non-interactive flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure.

Generate a complete, production-ready CLI in Bun from a SPEC, OpenAPI contract, JSON Schema, or natural-language description. Outputs a runnable binary with commander-style arg parsing, autocomplete, man page, and token-aware output formatting.

Multi-harness CLI wrapper ecosystem. Claude Code = single source of truth. Wraps any external CLI (claude, gemini, codex, opencode, agy + extensible) so the AI harness can invoke it without context bloat. Includes per-CLI wrapper skills/agents, cross-harness symlink setup, and token metrics across the whole ecosystem.

Thermo-nuclear branch review: deep correctness and security audits plus harsh code-quality rubrics, parallel subagents, code-review-expert orchestration, and optional take-the-wheel and FSD merge-ready flows.

Code smell detection and remediation. Identifies long methods, god classes, feature envy, primitive obsession, shotgun surgery, dead code, magic numbers, and other structural anti-patterns. Goes beyond linters — understands semantic coupling and design intent. Use when code is hard to change, PRs are consistently risky, or technical debt is growing faster than features.

A reusable testing loop for macOS apps using Computer Use (Note: Computer Use is currently exclusive to the Codex app). Automates UI/visual verification, records findings, and validates small SwiftUI or Store/ViewModel fixes.

Incrementally learns durable user preferences and workspace facts from transcript changes and keeps AGENTS.md up to date with plain bullet points.

Scaffold and review AI agent plugins: create plugin directories with valid manifests, component metadata, and marketplace wiring. Includes scaffold and pre-submission review workflows.

Database index optimization advisor for PostgreSQL, MySQL, and SQLite. Analyzes slow queries, missing indexes, unused indexes, and over-indexed tables. Generates CREATE INDEX statements with EXPLAIN ANALYZE estimates. Use when queries are slow, p99 DB latency spikes, or when reviewing a new schema.

Feature flag implementation, management, and cleanup. Handles flag creation, gradual rollout strategies, A/B testing wiring, stale flag detection, and safe flag removal. Supports LaunchDarkly, Unleash, GrowthBook, Statsig, custom env-var flags, and database-backed toggles. Use when adding gated features, rolling out gradually, or cleaning up old flags.

Safely remove an entire feature and every dead reference it leaves behind — not just the folder you point at, but the sibling folders in other architecture layers, the imports/registries/routes/i18n keys that point to it, and any newly-orphaned code. Verifies the quality gate stays 100% green and writes a Markdown removal report. Use when deleting a feature, screen, module, or directory and you need it gone WITHOUT leaving dead files or dead code. Triggers on /feature-purge <path>, "remove this feature", "delete this folder safely", "apaga essa feature sem deixar código morto", "limpa essa screen e as camadas".

Expert plugin covering Firebase CLI, Firebase App Distribution, Crashlytics deobfuscation, Hosting deploys, Functions deploys, and the new Firebase MCP Server.

Generates distinctive, production-grade frontend interfaces that avoid generic AI aesthetics.

Expert GitHub CLI plugin containing multiple skills for PR management, issue tracking, and GitHub workflows automation.

Expert git plugin containing multiple skills for advanced version control, semantic commits, and bisect automation.

Google Play Developer API Expert Agent and Skills. Provides comprehensive tools and knowledge for interacting with the Google Play Developer API, covering Publishing, In-App Products, Subscriptions, Reviews, and Reporting.

AI release agent for Google Play Store: audits Android/Expo/React Native/Firebase/RevenueCat before submission. Validates build readiness (app.json, eas.json, AAB, versionCode), Play Console metadata, Data Safety Form, Android permissions, RevenueCat/IAP, i18n parity (PT/EN/ES), policy-risk copy, internal/closed testing and staged rollout. Generates reports + GO/NO-GO checklist. Never publishes or rolls out without explicit human approval. Use when preparing an Android app for Google Play, auditing a submission, generating release notes, validating Data Safety or permissions, or running a release go/no-go.

Easily create custom hooks to prevent unwanted behaviors by analyzing conversation patterns or from explicit instructions.

Internationalization completeness audit and key synchronization. Finds missing translation keys, hardcoded strings, pluralization bugs, RTL layout issues, date/number formatting gaps, and untranslated copy. Supports i18next, react-intl, vue-i18n, next-intl, and custom JSON locale files. Use when adding a new language, auditing translation completeness, or debugging locale mismatch errors.

Incident response runbooks, on-call workflows, and postmortem templates. Generates severity-tiered runbooks, communication templates, timeline reconstruction, and blameless postmortem docs. Use when user is in an incident, doing on-call prep, writing a postmortem, or building incident response playbooks.

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Autonomous Loop Engineering engine based on Andrej Karpathy's Autoresearch method. Enables AI agents to run iterative hypothesis-modify-execute-validate-improve cycles for continuous optimization of code, models, and metrics.

Applies Karpathy's "A Recipe for Training Neural Networks" adapted to software engineering. Forces a minimum runnable baseline before optimizing, one knob at a time, with verifiable eval at the beginning. Use when implementing a new feature, doing a non-trivial refactor, integrating an external service, or when the user says "implement X from scratch", "how to start feature Y", "recipe", "incremental approach", "baseline first".

Engage in active learning by requesting meaningful code contributions at decision points and providing educational insights.

Maintains docs/ in the Karpathy-style LLM-wiki standard. Generates docs/llms.txt (flat machine-readable index conforming to llmstxt.org), validates broken links, enforces a minimum front-matter in new .md files (title, status, updated, related), groups orphan docs. Use when the user says "update docs index", "generate llms.txt", "audit docs", "organize wiki", "cure documentation", or after adding/renaming a file in docs/.

Load testing setup, execution, and analysis with k6, Artillery, or Locust. Generates test scripts, defines VU ramp-up scenarios, interprets p99 latency and error rate results, and suggests infrastructure fixes. Use when user wants to load test an API, check throughput limits, validate SLO headroom, or diagnose performance under traffic.

Generate OpenAPI 3.1 specs from existing code (routes, controllers, types, Zod/Joi schemas), or generate code from an existing spec. Produces valid openapi.yaml, typed client SDKs, mock servers, and Postman collections. Use when documenting an API, onboarding clients, generating typed SDKs, or migrating to spec-first development.

Fan out large tasks across parallel AI agents with planner/worker/subplanner hierarchy and structured handoffs. Isolated workers, recursive decomposition, script-driven reconciliation.

Generator for Lemon AI Hub plugins. Creates a new plugin directory following current standards, including plugin.json, SKILL.md, and automatically updates marketplace.json to ensure the plugin is discoverable. Use when the user asks to 'create a plugin', 'add a plugin', or 'generate a new plugin'.

Create Postman collections and environments from OpenAPI/Swagger or code context. Generates rich JS tests for status codes, headers, and schemas, and handles Newman installation and test execution.

Render a PR diff review as an interactive walkthrough that groups changes by reviewer importance, separates boilerplate from core logic, and highlights tricky code.

Security review for generated code including pattern warnings, diff review, and agentic commit review.

Pipeline stage-0 prompt refiner. Runs FIRST — before skills-selector and smart-dispatch — turning a raw idea, pasted draft, or the current chat into a definitive, production-grade prompt (Anthropic prompt-engineering best practices), then hands the refined prompt + an Execution Map (agents, skills, models, effort, time & token estimate) to the routers so they pick the best skills/models with sharpened context. When no file path is given, the input IS the chat/pasted text and the output is returned inline (processed naturally), not forced to a file. Use when the user invokes /senior-prompt-engineer, says "refine my prompt", "improve this prompt", "turn this idea into a prompt", "rewrite idea.md to prompt.md", "definitive prompt", "professional prompt", or pastes a draft prompt/idea to be hardened. Cross-CLI: Claude, Codex, Gemini, OpenCode, Antigravity (agy), lemon-code (lemon).

Meta-skill gatekeeper that runs FIRST on every task to decide which other skill(s) — if any — should activate. Analyzes the user request, matches it against a ranked catalog (frontend-design, ui-ux-pro-max, superpowers/planning, git-*, mcp-builder, smart-dispatch, claude-api, etc.), and emits a tight SELECTION plan so other skills are loaded on-demand only. Minimizes token/context consumption by refusing to activate heavy skills unless clearly justified. Triggers on ANY user instruction that could plausibly benefit from a specialized skill — i.e. essentially every turn that starts new work. Keywords: "plan", "design", "ui", "ux", "implement", "build", "create", "fix", "refactor", "commit", "pr", "review", "test", "debug", "deploy", "mobile", "video", "mcp", "skill", "architecture", "api", "ci", "docs", "copy", "social", "setup", "doctor".

Automatically routes tasks to the optimal AI agent, model, or provider based on complexity, cost, and capability. Use when implementing features, fixing bugs, or any multi-step development work. Triggers on "implement", "build", "create", "fix", "add feature", "develop", or when the user asks to do any coding task.

AI-Native Squad — Spotify-model autonomous engineering team. 12 specialized agents (Tech Lead, Backend, Frontend, Mobile, UX, UI, Product, Scrum Master, DevOps, QA, Data, Security) with orchestrated collaboration, domain-specific skills, and cross-functional workflows. Based on the AI Native Developer methodology.

Skill mapping, practice plans, and learning retrospectives. Builds personalized roadmaps with milestones and practice checkpoints, and runs periodic reviews to adjust based on progress.

Configures token-saving tools (rtk, caveman, graphify, context-mode) globally or per project. Allows auditing and calculating the token savings obtained.