By rczamor
AI Researcher strategic routine for Riché Zamor's agent team. Fires via Claude Code Routines when a Linear ticket labeled type:research moves to Ready for Claude routines. Produces method evaluations, eval specs, ablation study designs, and literature reviews. Feeds recommendations to the AI Engineer execution agent.
Design an ablation or comparative study — isolate variables, compare variants, produce a recommendation grounded in eval results. Use when the ticket asks which of several variants (prompt versions, hyperparameters, architecture choices) works best.
Design an evaluation for an AI capability — rubric, dataset, methodology, success criteria. Use when the ticket asks how to measure something (prompt quality, retrieval relevance, consolidation, etc.) without pre-selecting a specific technique.
Survey the current SOTA on a topic with synthesis, gaps, and implications. Use when the ticket asks what's new in a space, what's state of the art, or wants orientation on a topic before method selection.
Evaluate a single AI technique against Riché's setup and produce an adopt/trial/hold/reject recommendation. Use when the ticket asks whether a specific method (new retrieval technique, prompting pattern, model, fine-tuning approach) is worth adopting.
Must invoke first on every AI Researcher routine session. Sets persona, operating rules, and session flow. Reads the triggering Linear ticket, loads relevant Notion AI Research hub context, and routes to the appropriate output skill (method-eval, eval-spec, ablation-study, or literature-review).
Versioned configuration for Riché's 11-agent OpenClaw team. The agents build and maintain the app portfolio: SIA, richezamor.com, and 6 prototypes (Recipe Remix, Ploppy, Blocade, Ascend, Trend Analyzer, AI Onboarding).
The authoritative design lives in Notion under 🤖 Agent Team. This repo is the deployable artifact — the markdown each OpenClaw instance reads at startup.
.
├── README.md This file
├── TEAM.md Full roster — identical copy on every instance
├── USER.md Riché's working context + app registry pointers — identical copy on every instance
├── identities/ One IDENTITY.md per agent (11 total)
│ ├── conductor.md
│ ├── pm-lite.md
│ ├── researcher.md
│ ├── designer.md
│ ├── backend-eng.md
│ ├── data-eng.md
│ ├── ai-eng.md
│ ├── ui-eng.md
│ ├── qa-eng.md
│ ├── devops-eng.md
│ └── tech-writer.md
├── corpus/ Knowledge corpus seeds for each role (Cowork research input)
├── connect.sh SSH helper for the Hostinger VPS
└── .env.local.example Template for local connection vars
Each of the 11 OpenClaw instances on the Hostinger VPS (/docker/openclaw-*/) loads three identity files at startup:
TEAM.md → identical across all instancesUSER.md → identical across all instancesIDENTITY.md → the role-specific file from identities/{role}.md, copied to the instance's working directory as IDENTITY.mdA future deployment script will sync these files from this repo to each /docker/openclaw-{role}/ directory on the VPS. Until that script exists, propagate by hand:
# Example for the conductor instance
scp identities/conductor.md [email protected]:/docker/openclaw-<conductor-instance>/data/IDENTITY.md
scp TEAM.md USER.md [email protected]:/docker/openclaw-<conductor-instance>/data/
docker compose -f /docker/openclaw-<conductor-instance>/docker-compose.yml restart
Every /docker/openclaw-*/.env on the VPS must contain:
ANTHROPIC_API_KEY=... # Opus 4.7 — primary for Conductor + AI Eng, escalation for everyone else
OLLAMA_API_KEY=... # Ollama Cloud — workhorse inference for the other 9 roles
Local Ollama (ollama-apvg container) on the VPS is reserved for embeddings only (nomic-embed-text model). Do not configure agents to use it for chat completion.
app_id). Cross-app work splits into sequential sub-sessions.agent_memory schema (persistent, partitioned by app_id).app_id + agent role + session ID.Full operating rules live in the Notion Operating Rules & Conventions page.
@conductor, @pm, @researcher, @designer, @backend-eng, @data-eng, @ai-eng, @ui-eng, @qa-eng, @devops-eng, @tech-writer).scripts/deploy-identities.sh)agent_memory Postgres schema migrationsOwn this plugin?
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npx claudepluginhub rczamor/rz-agent-team --plugin rz-ai-researcherTechnical Architect strategic routine for Riché Zamor's agent team. Fires via Claude Code Routines when a Linear ticket labeled type:architect moves to Ready for Claude routines. Produces ADRs, integration designs, architecture reviews, and tech stack evaluations in Notion.
Riché Zamor's personal skill bundle for Claude Code. Includes 10 skills (rz-copywriting, rz-product-management, rz-growth-marketing, rz-networking, rz-networking-hand-curated-import, rz-graphic-design, rz-product-design, rz-draft-content, rz-content-optimize, rz-self-improve) that share a 553-entry corpus of canonical knowledge across voice, content, PM frameworks, audience growth, brand system, UX principles, AI product UX, and evaluation frameworks.
User Researcher strategic routine for Riché Zamor's agent team. Fires via Claude Code Routines when a Linear ticket labeled type:ux moves to Ready for Claude routines. Produces interview synthesis, personas, journey maps, and usability audits in Notion.
Analyst strategic routine for Riché Zamor's agent team. Fires via Claude Code Routines when a Linear ticket labeled type:analyst moves to Ready for Claude routines. Produces competitive matrices, market analysis briefs, pricing/packaging studies, and opportunity briefs in Notion.
AI Agent Team Operating System for Claude Code — persistent team management, meetings, task wall, company loop engine, and real-time dashboard
Enterprise AI agent orchestration plugin with 150+ commands, 74+ specialized agents, SPARC methodology, swarm coordination, GitHub integration, and neural training capabilities
Multi-agent team orchestration for Claude Code. Set up parallel AI agent teams with file-based planning, progress tracking, and role-based collaboration.
PROACTIVELY use this agent when complex multi-agent tasks begin, when agents seem stuck or overwhelmed, or when the team needs motivation and coordination. This agent serves as the elite performance coach for all other agents, ensuring they operate at their highest level while maintaining composure and excellence. Should be triggered automatically at the start of challenging projects or when detecting agent confusion. Examples:\n\n<example>\nContext: Starting a complex project requiring multiple agents\nuser: "We need to build a viral TikTok app in 2 weeks"\nassistant: "This is an ambitious goal that will require our A-team! Let me bring in the studio-coach to coordinate our agents and ensure everyone performs at their peak."\n<commentary>\nComplex projects benefit from having a coach to keep all agents aligned and motivated.\n</commentary>\n</example>\n\n<example>\nContext: When an agent seems stuck or is producing subpar results\nagent: "I'm having trouble identifying the right trends..."\nassistant: "Let me bring in the studio-coach to help refocus and elevate your approach."\n<commentary>\nAgents can get overwhelmed or lose focus - the coach helps them recenter and excel.\n</commentary>\n</example>\n\n<example>\nContext: Before launching a major sprint or initiative\nuser: "Tomorrow we start the 6-day sprint for our biggest project yet"\nassistant: "Time to rally the team! I'll have the studio-coach prepare everyone mentally and strategically for peak performance."\n<commentary>\nPre-sprint coaching ensures all agents start with clarity, confidence, and coordination.\n</commentary>\n</example>\n\n<example>\nContext: When celebrating wins or learning from failures\nuser: "Our app just hit #1 on the App Store!"\nassistant: "Incredible achievement! Let me bring in the studio-coach to celebrate with the team and capture what made this success possible."\n<commentary>\nThe coach helps institutionalize wins and extract learnings from both successes and failures.\n</commentary>\n</example>
AI team role and worker manager for multi-agent development workflows.
Dynamically assemble expert agent teams for complex tasks using Claude Code's agent teams feature