TAD

TAD Solution Lead (Agent A). Use for new features (>3 files), architecture changes, complex multi-step requirements, multi-module refactoring. Supports modes: *bug, *discuss, *idea, *learn, *publish, *sync, *playground.

TAD Solution Lead (Agent A). Use for new features (>3 files), architecture changes, complex multi-step requirements, multi-module refactoring. Supports modes: *bug, *discuss, *idea, *learn, *publish, *sync, *playground.

TAD Execution Master (Agent B). Use when there is an active handoff from Alex, user says 'start implementation', or for release execution.

Comprehensive help guide for TAD Framework usage, commands, and workflows.

GitHub Awesome-List Registry — discover, browse, and create deep-research notebooks from GitHub repos. 6 commands for Alex research phase.

Hardware circuit design capability pack. Covers component selection with supply-chain risk rating, KiCad schematic design with ERC, PCB layout/routing with DRC and manufacturing export, dual-supplier BOM management with cost analysis, power architecture and battery-life budgeting, 4-phase design review with anti-pattern scanning, and design documentation with decision records. Use for any circuit design, schematic, PCB layout, BOM, power budget, or hardware design review task.

Hardware enclosure design capability pack. Covers parametric OpenSCAD enclosure modeling, PCB fitting, material selection, assembly design, ergonomics, manufacturing export (STL/STEP), and dimension/assembly documentation. Use for any IoT/embedded device enclosure design, PCB housing, 3D-print enclosure, or enclosure manufacturing prep task.

Embedded firmware development capability pack for ESP32-S3/C3 + Arduino framework. Covers firmware architecture (super loop / FreeRTOS / event-driven), peripheral driver wrapping (I2C/SPI), low-power deep-sleep design, communication protocols (WiFi/BLE/MQTT/HTTPS/OTA), arduino-cli build & upload, three-layer firmware testing, and hardware documentation generation. Use for any embedded firmware, ESP32/Arduino, IoT device code, or hardware bring-up task.

Hardware testing capability pack. Covers power-on testing (voltage rails, smoke test), functional peripheral verification, per-mode power measurement and battery life calculation, environmental test planning (IEC/MIL standards), EMC pre-compliance (emissions/ESD), production test fixture design, and human-AI pair testing with physical instruments (4D Protocol) — embedded MCU prototypes first. Use for any hardware bring-up, prototype validation, power profiling, compliance pre-check, or production test task.

Mobile development capability pack. Covers Expo/React Native/Swift framework selection, native UI components, offline-first state and API architecture, platform features (camera, location, notifications, biometrics), mobile performance optimization, and mobile code quality. Use for any mobile app development, React Native/Expo build, offline-first architecture, or mobile performance task.

Mobile release capability pack. Covers App Store metadata & ASO, TestFlight distribution, review compliance checking, privacy policy & App Privacy Labels, version management, release CI/CD automation, and post-release monitoring. Use for any mobile app release, App Store submission, TestFlight beta, app review compliance, or release pipeline task.

Mobile testing capability pack. Covers E2E testing (Detox/Maestro), unit testing (Jest/RNTL), device compatibility matrices, performance budgets, VoiceOver accessibility, human-AI pair testing, and mobile test strategy — iOS/React Native first. Use for any mobile app testing, mobile test strategy, or mobile QA task.

Mobile UI design capability pack. Covers iOS HIG / Material Design 3 platform-guideline research, mobile navigation architecture (Tab Bar/Stack/Modal/Drawer), mobile-viewport wireframing with gesture annotations, platform-native visual design and Design Tokens, gesture interaction specs, native-first mobile design systems, and mobile usability review (touch targets, Dynamic Type, one-hand reachability). Use for any mobile app UI/UX design, wireframe, design token, gesture spec, or mobile design review task.

Supply chain security capability pack. Covers dependency audit, behavioral analysis, provenance verification, lockfile integrity, and typosquat detection. Use for any dependency trust review, pre-install package vetting, SBOM audit, dependency-update PR review, or supply chain security task.

Release + sync runbook for TAD framework. Read BEFORE starting *publish or *sync. Contains the full pre-flight checklist, version-bump file list, sync strategy matrix, known gotchas (jq flags, tad.sh bugs, deprecation mechanics), and post-flight verification. Prevents the recurring errors from past releases.

Capture a reusable pattern from the current conversation into a local skill file under .claude/skills/local/ — LLM-draft + user-confirm, local-only, never synced. Use when the user says *save-skill, 'save this as a skill', '把这个存成 skill', or wants to keep a just-validated pattern.

Capture the workflow (ordered steps + concrete commands) just executed in the current conversation into a reusable local skill file at .claude/skills/local/<workflow-name>.md, with auto-detected trigger keywords. Use when the user says 'save the workflow / steps we just did'. NOT for reusable patterns or judgment rules — that is *save-skill (if present).

Surplus Burn Mode — find + rank the highest value-density backlog work to consume unused Claude usage productively. Phase 1 (--plan) scans and ranks. Phase 2 (+<budget>) auto-executes ranked tasks within a budget envelope (SAFETY tasks routed to needs-you list).

Academic research methodology pack for systematic literature review, citation integrity, and quality evaluation. Covers PRISMA systematic reviews, meta-analysis, PubMed search, literature surveys, and academic writing standards. Use for any academic research, literature review, citation analysis, paper evaluation, or systematic review task.

Decision navigator for designing reliable agent systems. Guides AI agents through 10 architectural decisions derived from 3 production systems and 7 real production disasters, with /design and /audit modes. Use for any agent architecture design, system audit, or production reliability planning task.

AI podcast production judgment for coding agents. Covers script writing, large-chunk TTS generation, dual-BGM music arrangement with envelope follower ducking, show notes, and Colab deployment. Use for any AI-assisted podcast or audio content production task.

AI voice production judgment for coding agents. Covers TTS tool selection, voice cloning, audiobook, podcast, and dubbing pipelines, Apple Silicon optimization, and licensing safety. Use for any AI voice synthesis, voice cloning, audiobook production, or TTS pipeline task.

ML model training on cloud GPU capability pack. Covers platform selection, LoRA and QLoRA fine-tuning, cost estimation, and human-AI collaboration via browser MCP. Use for any ML model fine-tuning, cloud GPU training, or model adaptation task.

Three deep skills that turn any AI agent into a product decision partner. Covers adversarial idea validation, business model generation, and executable product definition across 6 product types. Use for any product strategy, idea validation, business model design, or product definition task.

Professional video production judgment for AI coding agents. Covers storytelling, motion design, audio integration, and tools like HyperFrames and Remotion. Use for any AI-assisted video production, motion graphics, or multimedia content creation task.

Web frontend engineering judgment for React. Covers component architecture, state management, design token consumption, styling, performance, accessibility, testing, and visual-code bridge. Loads DESIGN.md when present and turns design artifacts into production-grade code. Use for any React frontend development, component design, or UI implementation task.

Academic research methodology pack — systematic literature review, citation integrity, quality evaluation. Activates on: 学术, academic, 论文, paper, 文献, literature, meta-analysis, 元分析, PRISMA, systematic review, 系统性综述, PubMed, 文献综述, 学术研究, 科研

Decision navigator for designing reliable agent systems. Guides any AI agent through 10 architectural decisions derived from 3 production systems (Claude Code, OpenClaw, Hermes) and 7 real production disasters. Two modes: /design (new system) and /audit (existing system).

AI voice production judgment for coding agents — TTS tool selection, voice cloning, audiobook/podcast/dubbing pipelines, Apple Silicon optimization, licensing safety

ML model training on cloud GPU — platform selection, LoRA/QLoRA fine-tuning, cost estimation, human-AI collaboration via browser MCP

Three deep skills that turn any AI agent into a product decision partner. Covers adversarial idea validation (/pressure-test), business model generation (/shotgun), and executable product definition (/define) across 6 product types.

Professional video production judgment for AI coding agents — storytelling, motion design, audio, tools (HyperFrames/Remotion)

Web frontend engineering judgment for React — component architecture, state management, design token consumption, styling, performance, accessibility, testing, and visual-code bridge. Loads DESIGN.md when present and turns design artifacts into production-grade code.

Execute TAD Quality Gate. Gate 1 (pre-design), Gate 2 (pre-handoff), Gate 3 (post-implementation), Gate 4 (acceptance).

TAD Research Notebook Manager — NotebookLM multi-source knowledge base for Alex *discuss and research workflows. 19 sub-commands for full research lifecycle management.

Agent computer & browser control capability pack. Gives AI agents the judgment rules for detecting available tools, selecting the right automation layer (engine/data/hybrid/agent/desktop), configuring browser and computer control tools, and handling fallback chains. Covers Playwright, Browser Use, Stagehand, Firecrawl, Claude in Chrome, Computer Use, and 15+ tools across 5 layers. Use for any browser automation, web scraping, desktop control, or tool selection task.

Agent skill evolution capability pack. Gives AI agents the judgment rules for building self-improving agents — architecture decisions (fixed vs evolvable instruction), training loop design (rollout→reflect→edit→gate), edit safety (bounded edit, LR schedule, protected regions), validation gates, offline consolidation (sleep cycles), and multi-timescale memory. Research-grounded rules from SkillOpt (Microsoft, arXiv 2605.23904), SkillOpt-Sleep, and EmbodiSkill. Use for any self-evolving agent design, skill optimization pipeline, or agent self-improvement task.

Turn an EPUB into an e-reader-grade, annotatable HTML reading surface plus an auto-generated active-reading plan. Annotations live in a sidecar data file (W3C TextQuote anchors) and survive HTML regeneration via a paragraph-scoped re-attach algorithm. Use when the user wants to read an EPUB with durable highlights, generate a structure map / reading questions, or export highlights-in-context. STDLIB-ONLY Python tools; no external dependencies.

Knowledge Graph & GraphRAG capability pack. Gives AI agents the judgment rules for building graph-enhanced retrieval systems — Microsoft GraphRAG indexing (Leiden communities, Global/Local/Drift search), LazyGraphRAG vs LightRAG cost selection, LLM knowledge-graph construction (ontology design, extraction prompting), entity resolution & deduplication, graph database selection (Neo4j/Memgraph/FalkorDB, LPG vs RDF-Star), and Text2Cypher/SPARQL-Star query translation. Research-grounded rules from Microsoft Research, Neo4j, LightRAG, OntoDup, and graph database benchmarks. Use for any GraphRAG pipeline, knowledge-graph construction, entity-resolution, graph-DB selection, or graph-query-translation task.

AI guardrails & LLM I/O security capability pack. Gives AI agents the judgment rules for defending LLM and agent pipelines against prompt injection (OWASP LLM01), improper output handling (OWASP LLM05), excessive agency, PII leakage, and unsafe content. Research-grounded rules from OWASP Gen AI Security, Microsoft Presidio, NVIDIA NeMo Guardrails, Meta Llama Guard, Lakera Guard, Rebuff, and Pydantic AI. Use for any guardrail design, prompt-injection defense, PII de-identification, output/tool-call validation, content-moderation, or LLM security review task.