By dbc-oduffy
Research YouTube, podcasts, and media Claude can't access directly — NotebookLM integration with structured claims extraction, adversarial coverage checking, and notebook preservation for follow-up queries.
npx claudepluginhub dbc-oduffy/coordinator-claude --plugin notebooklmHaiku scout for Agent Teams-based NotebookLM research. Spawned as a teammate by the notebooklm-research command. Reads strategy.md, finds the best YouTube videos, podcasts, and articles for each notebook's topic area via web search, and writes sources.md for workers to consume. <example> Context: EM has written strategy.md with search guidance for 2 notebooks. user: "Find the best YouTube videos and podcasts for the notebooks in strategy.md" assistant: "I'll read the strategy, execute searches for each notebook's topic area, vet accessibility, and write sources.md." <commentary> Scout reads strategy.md, executes searches per notebook's 'search guidance for scout' field, writes sources.md with ## Sources for Notebook A/B/C convention. Task completion unblocks workers. </commentary> </example>
Opus sweep agent for Agent Teams-based NotebookLM research. Spawned as a teammate by the notebooklm-research command. Blocked until all worker tasks complete, then reads structured claims from disk, assesses coverage, fills gaps, frames the final research document, and deletes all notebooks. <example> Context: All workers have completed their notebooks and written claims. user: "Sweep findings from 3 NotebookLM notebooks into a final research document" assistant: "I'll wait for all DONE messages, read the claims files, assess coverage and gaps, fill negative space, and clean up the notebooks." <commentary> Sweep waits for DONE messages from all workers, reads {letter}-claims.json and {letter}-summary.md files, produces polished output, then deletes notebooks using IDs from the summary.md YAML frontmatter. </commentary> </example>
Sonnet worker that executes NotebookLM MCP operations as a teammate in an Agent Teams research session. Blocked by the scout until sources are ready, then creates its own notebook, ingests assigned sources, runs queries, extracts structured claims, and writes {letter}-claims.json + {letter}-summary.md. Sends DONE to sweep when complete. <example> Context: Scout has written sources.md. Worker is assigned Notebook B. user: "Execute NotebookLM research for Notebook B on 'agent evaluation frameworks'" assistant: "I'll check my task is unblocked, read strategy.md and sources.md for Notebook B, bootstrap MCP, create the notebook, ingest sources, run queries, extract structured claims, and write B-claims.json and B-summary.md." <commentary> Worker checks TaskList FIRST (read-after-unblock sequencing), reads its Notebook B sections from shared artifacts, bootstraps MCP tools, executes the full research pipeline, writes B-claims.json and B-summary.md, marks task complete, sends DONE. </commentary> </example>
Standalone image generation plugin using Nano Banana MCP server. Generates and edits images, icons, diagrams, patterns, and visual assets via Gemini image models. No Gemini CLI dependency required.
Comprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns
Memory compression system for Claude Code - persist context across sessions
Qiushi Skill: methodology skills for AI agents guided by seeking truth from facts, with Claude Code, Cursor, OpenClaw, Codex, OpenCode, and Hermes guidance.
AI image generation Creative Director powered by Google Gemini Nano Banana models. Claude interprets intent, selects domain expertise, constructs optimized prompts, and orchestrates Gemini for best results.
Uses power tools
Uses Bash, Write, or Edit tools
Share bugs, ideas, or general feedback.
A PM-native operating layer for AI engineering work. A Claude Code plugin that turns product intent into scoped plans, delegated implementation, evidence, and ship/no-ship decisions. You're PM. Claude is EM. You stay technical enough to spot when something's wrong; the EM handles the rest.
You don't need to write code. You need to know enough to evaluate it — to spot when something smells wrong, to ask the right questions, to set direction. Amjad Masad (Replit's founder) opined that people who don't program may actually be better positioned for the LLM-coding world: they won't micromanage implementation. This plugin leans into that. It gives Claude standing authority to make engineering decisions — how to build, who to delegate to, when to refactor — while you hold product authority: what to build, what to cut, what ships. Just like an EM-PM dynamic.
This isn't a collection of prompt tricks. It's a decision architecture: routines (session orientation, plan review, multi-source code review, structured handoffs, daily flows) plus authority boundaries (EM owns implementation, PM owns scope/ship) plus reviewer personas that push back. It maps to how real engineering teams operate. The difference is that your "team" can work autonomously for hours, and you can review the output when you're ready.
/mise-en-place, /autonomous) exist for execution sprints, not for product authority.You don't install this. Your agent does. Open Claude Code in any project and paste:
Install coordinator-claude. The playbook is at
https://github.com/dbc-oduffy/coordinator-claude/blob/main/docs/agent-install.md
— read it, follow it, and queue /project-onboarding as the immediate next step
after I restart Claude Code.
Claude clones the repo, runs the installer, validates the result, and tells you when to restart. After restart, /project-onboarding bootstraps tracking infrastructure in your project.
Auditing & uninstall → docs/safety.md — what the installer changes, what it does not do, audit commands, and exact uninstall steps.
| coordinator-claude | Claude Code | OS tested | Notes |
|---|---|---|---|
| v1.9.0 | tested with Claude Code 2026-05-06 release; minimum version not formally established | macOS, Linux, WSL, Windows (Git Bash) | Reference: setup/install.sh |
Most tools hand you a bag of commands and wish you luck. This system has routines — things that happen automatically because they should always happen, woven into the session lifecycle so you don't have to remember them.
Starting up. When Claude opens a supported project, a SessionStart hook fires automatically — loading the current branch, pending handoffs, lessons from past sessions, project vitals, and an orientation cache. No cold start. Claude lands in the middle of the context window where performance is strongest, with forward-looking state already loaded. This is deliberate: research shows LLMs degrade toward the end of their context and, to a lesser extent, at the beginning (Liu et al. 2023, "Lost in the Middle"). The orientation hook front-loads context so the working session occupies the optimal window.
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