Communitygithub.com

BIGboss248/nextjs-wordpress

Spawn multiple agents into a shared conversation where they debate, disagree, and converge on a solution via a shared chat.json file. Use for architecture decisions, code review debates, design trade-offs, or any problem that benefits from adversarial reasoning. Triggers on "chatroom", "agent debate", "have agents discuss", "agent chatroom", "debate this", or /agent-chatrooms. Also triggers on phrases like "have 3 agents argue about", "multi-agent discussion", or "let them debate".

What is nextjs-wordpress?

nextjs-wordpress is a Claude Code agent skill that spawn multiple agents into a shared conversation where they debate, disagree, and converge on a solution via a shared chat.json file. Use for architecture decisions, code review debates, design trade-offs, or any problem that benefits from adversarial reasoning. Triggers on "chatroom", "agent debate", "have agents discuss", "agent chatroom", "debate this", or /agent-chatrooms. Also triggers on phrases like "have 3 agents argue about", "multi-agent discussion", or "let them debate".

Works with~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/BIGboss248/nextjs-wordpress/tree/HEAD/.agents/skills/agent-chatrooms

Ask in your favorite AI

Open a new chat with this agent skill pre-loaded.

Documentation

Agent Chatrooms

Spawn N agents (default 3) into a simulated shared conversation. Each agent reads the full chat history before responding, building on, challenging, or refining previous contributions. You (the orchestrator) act as PM — moderating rounds, reading the debate, and extracting the final output.

Why this works: Sequential handoffs lose context — the second model doesn't know WHY the first made its decisions. A shared conversation preserves reasoning chains and enables genuine debate. When Agent A says "this needs a queue" and Agent B says "a simple loop is fine," that disagreement is more valuable than either agent's confident solo answer. Agents challenge assumptions, catch errors, and synthesize diverse reasoning paths.

Execution

1. Parse the request

Extract from the user's message:

  • Problem/question to debate
  • Agent count N — default 3. User can override ("have 5 agents debate")
  • Round count R — default 3 rounds. User can override ("debate for 5 rounds")
  • Agent roles (optional) — user may specify roles ("have an architect, a security engineer, and a frontend dev debate this"). If not specified, assign diverse default roles.

If the problem is vague, ask the user to sharpen it before spawning.

2. Assign agent roles

Each agent gets a distinct perspective to maximize productive disagreement. If the user didn't specify roles, choose from these defaults based on the problem domain:

Software engineering:

  1. Architect — thinks in systems, interfaces, scalability, and long-term maintainability
  2. Pragmatist — optimizes for shipping fast, minimal complexity, "good enough" solutions
  3. Critic — finds edge cases, failure modes, security holes, and unstated assumptions

Product/design:

  1. User advocate — optimizes for UX, simplicity, user delight
  2. Business strategist — optimizes for revenue, growth, competitive advantage
  3. Engineer — grounds the discussion in technical feasibility and cost

Strategy/decisions:

  1. Optimist — sees opportunity, upside potential, reasons to act
  2. Skeptic — sees risk, downside, reasons to wait
  3. Synthesizer — finds the middle path, integrates both perspectives

For N > 3, add more roles that create productive tension with the existing ones.

3. Initialize the chat file

Create active/chatroom/chat.json with the initial structure:

{
  "problem": "{problem statement}",
  "context": "{any relevant context, code, constraints}",
  "agents": [
    {"name": "Agent A", "role": "{role}", "framing": "{role description}"},
    {"name": "Agent B", "role": "{role}", "framing": "{role description}"},
    {"name": "Agent C", "role": "{role}", "framing": "{role description}"}
  ],
  "rounds": [],
  "final_output": null
}

4. Run debate rounds

For each round (1 through R), spawn all N agents in parallel. Each agent reads the full chat history and contributes.

Agent spawn config:

  • subagent_type: "general-purpose"
  • model: "sonnet" (default — user can override to opus for deeper reasoning)
  • mode: "bypassPermissions"

Round procedure:

Round 1 — Opening positions: Each agent states their initial take on the problem.

Agent prompt:

You are {role}: {role_description}

PROBLEM:
{problem}

CONTEXT:
{context}

This is Round 1 of a multi-agent debate. State your initial position on this problem. Be specific and concrete — propose actual solutions, not vague principles. Take a clear stance.

Other agents will challenge your position in subsequent rounds, so make your reasoning explicit.

Respond in this format:
POSITION: [Your one-sentence stance]
REASONING: [Your detailed argument — 3-5 key points]
PROPOSAL: [Your concrete recommendation]
CONCERNS: [What could go wrong with your approach]

Write your response directly — do not write to any files.

Rounds 2+ — Debate: Each agent reads all previous responses and responds.

Agent prompt:

You are {role}: {role_description}

PROBLEM:
{problem}

PREVIOUS DISCUSSION:
{all previous round entries, formatted as "Agent X (Role): response"}

This is Round {N} of a multi-agent debate. Read the previous discussion carefully.

Your job:
1. Respond to the strongest counterargument against your position
2. Identify where you AGREE with other agents (concede good points)
3. Identify where you still DISAGREE and why
4. Refine your proposal based on the discussion so far

Do NOT just repeat your previous position. Engage with what others said. Change your mind if they made a better argument.

Respond in this format:
AGREEMENTS: [What other agents got right]
DISAGREEMENTS: [Where you still differ and why]
REFINED PROPOSAL: [Your updated recommendation]
CONFIDENCE: [1-10 how confident you are in your refined position]

Write your response directly — do not write to any files.

After each round:

  1. Collect all agent responses
  2. Append to the rounds array in chat.json:
{
  "round": 1,
  "entries": [
    {"agent": "Agent A", "role": "Architect", "response": "..."},
    {"agent": "Agent B", "role": "Pragmatist", "response": "..."},
    {"agent": "Agent C", "role": "Critic", "response": "..."}
  ]
}
  1. Check for convergence: if all agents agree (confidence 8+, proposals aligned), stop early — no need for more rounds.

5. Synthesize the final output

After the last round, you (the orchestrator) read the full debate and produce a synthesis. Do NOT spawn another agent for this — you do it yourself.

Analyze:

  • Where did agents converge? — these are high-confidence conclusions
  • Where did they remain split? — these are genuine trade-offs the user needs to decide
  • What concerns were raised but unresolved? — these are risks to monitor
  • Did any agent change their mind? — mind-changes are strong signals

6. Write the final report

Update active/chatroom/chat.json with the final_output, and write a human-readable summary to active/chatroom/chatroom_report.md:

# Agent Chatroom Report

**Problem**: {problem}
**Agents**: {N} | **Rounds**: {R}
**Date**: {date}

## Participants
| Agent | Role | Final Confidence |
|-------|------|-----------------|
| Agent A | {role} | {confidence}/10 |
| Agent B | {role} | {confidence}/10 |
| Agent C | {role} | {confidence}/10 |

## Consensus
{What all agents agreed on by the final round}

## Key Disagreements
{Where agents remained split — present both sides fairly}

## Recommended Action
{Your synthesis as orchestrator — the best path forward considering all perspectives}

## Unresolved Risks
{Concerns raised during debate that weren't fully addressed}

## Debate Highlights
{The most interesting exchanges — where minds changed or strong counterarguments emerged}

## Full Transcript
{Link to chat.json or inline the key exchanges}

7. Deliver results

Present to the user:

  • One-paragraph synthesis of the debate outcome
  • The recommended action (your call as orchestrator, informed by the debate)
  • The sharpest disagreement (where the user's judgment is needed)
  • File paths to report and chat.json

Configuration

ParameterDefaultDescription
N3Number of agents in the chatroom
R3Number of debate rounds
modelsonnetModel for each agent
rolesautoAgent roles (auto-assigned or user-specified)

User can override: "have 5 opus agents debate for 4 rounds" or "debate between an architect and a junior dev".

Cost considerations

  • 3 sonnet agents x 3 rounds = 9 agent calls (~$0.30-0.50)
  • 3 opus agents x 3 rounds = 9 agent calls (~$3-5)
  • 5 agents x 5 rounds = 25 calls — gets expensive with opus
  • Default to sonnet. Only use opus if user explicitly requests it or the problem requires deep technical reasoning.
  • Early convergence saves cost — stop if agents agree before all rounds complete.

Edge cases

  • N < 2: Warn the user — a chatroom needs at least 2 agents. Minimum 2.
  • Agents all agree immediately: Stop after round 1. Report unanimous consensus. This is a valid (and cheap) outcome.
  • Agents deadlock: After R rounds with no convergence, report the deadlock honestly. The finding is that this is a genuine judgment call with no dominant answer.
  • Agent goes off-topic: Exclude that response from synthesis and note the effective agent count.
  • Existing chatroom files: Check active/chatroom/ for existing files. Overwrite without asking (these are ephemeral debate artifacts, not persistent data).
  • User specifies custom roles: Use exactly what they specify. Don't add extra roles unless asked.

Output files

FileDescription
active/chatroom/chat.jsonFull structured debate transcript
active/chatroom/chatroom_report.mdHuman-readable synthesis report

Previous reports are overwritten — these are ephemeral debate tools, not archives.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

BIGboss248/nextjs-wordpress

Create, configure, manage, and validate Google Antigravity customizations including skills, rules, MCP servers, lifecycle hooks, plugins, and custom JSON configs. Use when adding new capabilities to Antigravity, configuring MCP servers, writing rules, creating skills, setting up hooks, or modernizing legacy workflows.

BIGboss248/nextjs-wordpress

Always-active code intelligence, search, and navigation skill utilizing the codebase-memory MCP server. Enforces an index-first protocol (verifying and refreshing the knowledge graph via index_repository or index_status before searching, required because background auto_watch is disabled to eliminate editor stutter and system lag), followed by graph-first exploration (search_graph, trace_path, get_code_snippet, query_graph, get_architecture, detect_changes) instead of naive text grep or full-file reads. Always activate before searching the codebase, inspecting unknown architecture, finding symbols, or tracing callers/callees.

BIGboss248/nextjs-wordpress

>- Discover, interview, and craft comprehensive UX/UI design specifications (design-spec.md) and design tokens for web components. Triggers on "/component-design", "design component", "design section", "design UI", "wireframe component", or "create design spec".

BIGboss248/nextjs-wordpress

>- Configure and query WooCommerce APIs including WPGraphQL, WooGraphQL, and JWT auth for headless frontends. Use when connecting Next.js to WooCommerce or fetching store catalog data.

BIGboss248/nextjs-wordpress

Orchestrate parallel browser automation using multiple Chrome DevTools MCP instances. Use when a task requires doing the same browser action across many targets simultaneously (e.g., submitting contact forms, filling applications, scraping pages that need JS rendering). Spin up 1-5 parallel Chrome agents.

BIGboss248/nextjs-wordpress

Workflow for spawning an independent subagent to conduct unbiased code reviews and inject adversarial edge-case tests ([ComponentName].edge.test.tsx).

BIGboss248/nextjs-wordpress

>- Build Next.js App Router React components with Suspense skeletons, semantic OKLCH tokens, Jest + RTL unit tests, Playwright visual/hydration checks, and Tailwind logical styling. Triggers on "/nextjs-component-dev", "create component", "new component", "build component", or "develop component".

BIGboss248/nextjs-wordpress

>- Bootstrap, configure, and verify the complete Next.js App Router development environment, developer tooling, testing suites, MCP servers, Docker containerization, and CI/CD. Triggers on "/nextjs-dev-setup", "setup nextjs dev environment", "start a nextjs project", or "containerize nextjs app".

BIGboss248/nextjs-wordpress

>- Configure production health monitoring endpoints (/api/health), Docker Compose probes, and runtime metrics in Next.js App Router applications. Use when asked to "setup health check", "add health endpoint", "docker compose healthcheck nextjs", "configure health monitor", or "/nextjs-healthcheck".

BIGboss248/nextjs-wordpress

Bootstrap, configure, and verify next-intl App Router internationalization (proxy.ts/middleware.ts, next/root-params, [locale] layout, routing). Triggers on "/nextjs-i18n-setup", "setup i18n", "install next-intl", "configure next-intl", "add internationalization", "setup locale routing", "migrate to [locale]".

BIGboss248/nextjs-wordpress

Read/write translation dictionaries (messages/[locale].json), next-intl hooks (getTranslations/useTranslations), providers (Storybook/tests/subtrees), and BiDi styling. Triggers on "/nextjs-i18n-usage", "i18n dictionary", "use translations", "read dictionary", "i18n provider", "next-intl hooks", "storybook i18n", "test i18n", "add translation keys", "localize component", "create a component", "update a component".

BIGboss248/nextjs-wordpress

>- Configure, test, and verify OpenTelemetry (OTel) observability in Next.js App Router applications. Triggers on "/nextjs-otel", "setup otel", "configure opentelemetry", "test otel", or "verify opentelemetry".

BIGboss248/nextjs-wordpress

Step-by-step workflow for designing and building Next.js App Router pages (RSC page.tsx, loading skeleton, metadata, JSON-LD schema, and dynamic static params). Triggers on "/nextjs-page-dev", "create page", "new page", "develop page", "build route", or "implement page".

BIGboss248/nextjs-wordpress

>- Orchestrate end-to-end planning for Next.js App Router projects, generating canonical specifications, design systems, and a 7-phase modular implementation roadmap in docs/plan/. Triggers on "/nextjs-plan", "plan a nextjs project", "plan nextjs app", "create nextjs project plan", "outline nextjs architecture", or "generate plan".

BIGboss248/nextjs-wordpress

Workflow and engineering standards for crafting co-located Storybook CSF3 stories ([ComponentName].stories.tsx) with interactive controls, action spies, and 4 canonical theme variants.

BIGboss248/nextjs-wordpress

>- Build Next.js e-commerce frontends backed by WooCommerce APIs, handling ISR catalogs, cart sessions, and JWT authentication. Use when building or querying Next.js stores with WooCommerce.

BIGboss248/nextjs-wordpress

Self-correcting rules engine and feedback loop that learns from user corrections, mistakes, and project-specific constraints by maintaining a persistent autofix ruleset. Scans learned rules before starting any task, resolves conflicts, and automatically appends new rules upon corrections. Triggers on user corrections ("no, do it this way", "never do X", "always use Y"), /learn, "self repair", "add rule", "update rules", or when diagnosing assumptions and bugs. CRITICAL ALWAYS-ACTIVE LIFECYCLE SKILL. Must always be kept in context, loaded at session start, and consulted before starting ANY task to read and apply active constraints from autofix.json. MUST ALWAYS be triggered immediately whenever the user provides ANY correction, preference, criticism, rejection of an approach, or adjustment ("no", "don't do X", "use Y", "remember", "prefer"), or when any mistake/bug is identified. Automatically and immediately formulates and appends the new imperative rule to the project's autofix.json ruleset file.

BIGboss248/nextjs-wordpress

Setup, automate, and execute SEO audits, CI/CD pre-push/pre-deploy checks, and ranking optimizations using the seo CLI and MCP server.

BIGboss248/nextjs-wordpress

End-to-end repository onboarding and development environment setup skill. Scans repository structure, configures project metadata (docs/project.json), sets up the codebase-memory-mcp code intelligence knowledge graph server (in workspace mcp.json and globally for AGY only), configures git hooks with Husky and Commitlint, establishes multi-stage production Docker containerization, and automates credit-optimized Release Please CI/CD with multi-arch (AMD64 & ARM64) GHCR package deployment. Triggers on "/setup-repository", "setup repository", "setup repo", "initialize repository", "new repo setup", or when preparing any repository for development and AI agent workflows.

BIGboss248/nextjs-wordpress

AI screen scaffolding, layout generation, and variant exploration workflow powered by Google Stitch (StitchMCP). Consumes a component design specification (docs/design/components/[page name]/[component name]/design-spec.md), verifies and reuses the central Stitch project in docs/project.json (or creates/persists one if absent), seeds the project's design system into Stitch, synthesizes layout prompts to generate a screen and create one variant of the given design spec file, downloads and saves Stitch JPG screenshots and HTML code files directly into docs/design/components/[page name]/[component name]/stitch/ using binary-safe PowerShell Invoke-WebRequest, outputs image prompts to the user if visual assets are needed (without calling generate_image to conserve tokens), updates design-spec.md with Stitch layout benchmarks, and audits asset download integrity with an independent subagent. Triggers on "/stitch-design", "generate stitch screen", "create stitch variant", "scaffold screen with stitch", or "stitch...

Related Skills