By studiokjm
Run specification-first AI development workflows: Socratic interviews clarify requirements, generate immutable YAML seeds and layered TRDs/PRDs, decompose into atomic tasks, execute in Pair Mode with Navigator-Driver agents enforcing 3-tier architecture, verify via 3-stage gates, evolve specs on failures, unstuck deadlocks, and generate independent tests.
npx claudepluginhub studiokjm/ai-harness-templateExecute seed spec via Double Diamond (Discover → Define → Design → Deliver). USE AFTER /decompose. Enforces D→L→P implementation order, writes tests immediately, runs gates continuously. Supports Pair Mode for medium/high complexity ACs.
Crystallize interview results into an IMMUTABLE seed spec (YAML). Run ONLY after /interview reaches ambiguity ≤ 0.2. Extracts ontology, AC, constraints. Once created, seeds cannot be modified — only versioned.
Evolve the system when /evaluate fails. Runs Wonder → Reflect → Re-seed cycle with fan-out multi-perspective analysis (Contrarian + Simplifier + Researcher). Stops at convergence (ontology similarity ≥ 0.95).
Break seed AC into atomic layer-aware tasks BEFORE /run. USE WHENEVER implementation spans multiple files or layers. Prevents mega-prompts; each unit is independently implementable and testable.
Run 3-stage verification (Mechanical gates → Semantic AC compliance → Judgment quality) after /run. ALWAYS run before committing. Blocks at Stage 1 failures — no Stage 2 until gates pass.
Interactive installation wizard for AI Harness Template. Guides through version, track, permissions, gates, and more via step-by-step questions.
START HERE for ANY new feature or unclear requirement. Socratic interview that surfaces hidden assumptions before a single line of code is written. Measures 4D ambiguity score — blocks progress until score ≤ 0.2.
Generate a stakeholder-facing PRD from interview results. USE WHEN non-engineering stakeholders need a Product Requirements Document. Optional — most workflows go interview → seed directly.
Lightweight mid-run verification. Runs Stage 1 (Mechanical) gates only. Use between AC implementations to catch drift early. Much faster than /evaluate.
USE WHEN /run fails mid-way, /evaluate reports severe drift, or partial implementation must be undone. Saga-pattern rollback via git stash/checkout/branch — chooses safest strategy based on scope.
Generate layer-aware technical design document from seed spec. USE AFTER /seed and BEFORE /decompose. Maps features to 3-tier architecture, surfaces discussion points before final design.
USE WHEN stuck on a bug, architecture decision, or recurring failure. Applies 5 perspectives sequentially (Researcher → Architect → Contrarian → Simplifier → Hacker) to break deadlock.
USE THIS WHEN symptoms keep recurring, layer boundaries blur, or changes ripple unexpectedly. ALWAYS invoke for structural diagnosis during /unstuck or major refactors. Finds root causes in design, not symptoms. Names tradeoffs explicitly.
USE THIS WHEN the team reaches quick consensus, before committing to a major design decision, or during /evolve and /unstuck. Challenges assumptions with "what if we're wrong?" scenarios. Always proposes at least one alternative.
USE THIS WHEN verifying implementation against a seed spec, running gates, or assessing AC compliance. ALWAYS invoke during /evaluate. Never fixes — only judges Pass/Fail with file:line evidence. Runs 3-stage verification (Mechanical → Semantic → Judgment).
USE THIS WHEN the official path is blocked, a deadline looms, or a temporary workaround is acceptable. ALWAYS invoke during /unstuck when standard approaches fail. Finds safe bypasses (monkey-patch, polyfill, shim) with explicit expiry dates.
USE PROACTIVELY whenever the user describes a new feature, vague requirement, or unclear goal. ALWAYS run BEFORE writing code or creating a seed spec. Asks Socratic questions to surface hidden assumptions. Never writes code or gives answers — only questions.
USE THIS as the planning half of pair programming during /run (PAIR_MODE). Generates 3 solution plans per AC, selects optimal one, directs Driver. Never writes code directly. Based on PairCoder (ASE 2024) Navigator-Driver methodology. MUST be spawned as a background agent and communicated via SendMessage.
USE THIS WHEN defining domain terms, extracting entities/relationships from requirements, or unifying synonyms (e.g., "user" vs "member" vs "account"). ALWAYS invoke during /seed spec generation. Extracts Entity/Attribute/Relationship from interviews.
USE THIS WHEN a claim needs evidence, debugging requires history, or library/API behavior is uncertain. ALWAYS invoke before guessing — checks official docs, existing code patterns, git log/blame first. Evidence over speculation.
USE THIS WHEN crystallizing interview results into an immutable specification. ALWAYS invoke during /seed. Converts conversation + ontology into structured seed YAML with zero TODO/TBD tolerance. Blocks progress if any field is ambiguous.
USE THIS WHEN code feels over-engineered, scope seems to creep, or abstractions pile up. ALWAYS invoke during /evolve and /unstuck. Asks "is this needed for MVP?" on every feature. YAGNI-first — prefers convention over configuration.
USE THIS for independent test case generation during /run (PAIR_MODE). Designs tests from AC and seed spec only — never reads implementation code. Prevents biased testing. Based on AgentCoder (2024) test separation methodology. MUST be spawned with isolation worktree to physically prevent source code access.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
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Battle-tested Claude Code plugin for engineering teams — 38 agents, 156 skills, 72 legacy command shims, production-ready hooks, and selective install workflows evolved through continuous real-world use
Use this agent when you need expert assistance with React Native development tasks including code analysis, component creation, debugging, performance optimization, or architectural decisions. Examples: <example>Context: User is working on a React Native app and needs help with a navigation issue. user: 'My stack navigator isn't working properly when I try to navigate between screens' assistant: 'Let me use the react-native-dev agent to analyze your navigation setup and provide a solution' <commentary>Since this is a React Native specific issue, use the react-native-dev agent to provide expert guidance on navigation problems.</commentary></example> <example>Context: User wants to create a new component that follows the existing app structure. user: 'I need to create a custom button component that matches our app's design system' assistant: 'I'll use the react-native-dev agent to create a button component that aligns with your existing codebase structure and design patterns' <commentary>The user needs React Native component development that should follow existing patterns, so use the react-native-dev agent.</commentary></example>
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.