Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mnzralee/claude-multi-agent-architecture --skill module-planninggit clone --depth 1 https://github.com/mnzralee/claude-multi-agent-architectureWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mnzralee/claude-multi-agent-architecture/module-planning)<a href="https://agentmods.dev/skills/mnzralee/claude-multi-agent-architecture/module-planning"><img src="https://agentmods.dev/badge/skills/mnzralee/claude-multi-agent-architecture/module-planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mnzralee/claude-multi-agent-architecture/module-planning"><img src="https://agentmods.dev/badge/skills/mnzralee/claude-multi-agent-architecture/module-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.02061 |
| Opus 5 | $0.00015 | $0.01030 |
| Sonnet 5 | $0.00006 | $0.00412 |
| Haiku 4.5 | $0.00003 | $0.00206 |
Grade A, and why
module-planning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Module Planning Skill
Skill Metadata
- Name: module-planning
- Description: Plan a new module or feature area end-to-end using a structured Explore, Plan, and Document workflow before any code is written
- User Invocable: Yes (via
/module-planning)
Overview
This skill guides the comprehensive planning of new modules for any software project. It follows the established Explore, Plan, Implement pattern to ensure thorough preparation before writing code. The discipline is stack-agnostic; the examples below use TypeScript / Node.js / Express / Vitest / Zod for concreteness, but the same phases apply to any language or framework.
The skill separates thinking from typing. A module plan written before the first file is touched is cheaper to revise than one discovered mid-implementation. The three phases below each have a distinct agent role and a concrete output artifact.
Workflow
Phase 1: Research (Researcher Agent)
Objective: Understand existing patterns and gather reference implementations before designing anything new.
1. Find similar existing modules
- Search for comparable implementations in the codebase
- Identify reusable patterns and utilities
- Note what worked and what created friction
2. Document conventions already in use
- File structure patterns
- Naming conventions
- Code organization and layering decisions
3. List relevant existing code
- Related services or packages
- Shared utilities and helpers
- Common interfaces and types
Output: A pattern-reference document with file paths, conventions, and any prior art worth reusing.
Phase 2: Architecture (Architect Agent)
Objective: Design the module structure and interfaces based on the patterns the Researcher surfaced.
1. Module Structure
- Define service or package boundaries
- Identify components needed
- Plan data models and their relationships
2. API Design
- Define endpoints or function signatures
- Specify request / response formats
- Document authentication and authorization requirements
3. Data Layer
- Define schema models (using your ORM or migration tool of choice)
- Plan migrations and rollback paths
- Consider indexes and query performance
4. Integration Points
- Inter-service or inter-package communication
- External dependencies and their contracts
- Events emitted or consumed
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 286 lines · 29 tokens per session scan A ccb7c558cec6
module-planning is a skill published in the GitHub repository mnzralee/claude-multi-agent-architecture (6 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 2,061 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
coordinate-agents
Route Codex-native multi-agent orchestration in a Git repository through a local-first, recoverable Agent Bus. Use for role-based planning, task execution, review, recovery, adapters, and human-gated release workflows. The plugin supports Codex CLI, Google Antigravity CLI, Claude, and other configured coding agents.…
coordinate-task
Run a Coordinate Agents Task from requirement clarification through planning, implementation, review, and the human release gate. Hide Agent Bus transport details behind the durable Task API.
coordinate-recover
Diagnose and safely resume Coordinate Agents Tasks after executable failure, non-zero exit, timeout, stale claim, processing message, or Implementer ERROR. Recovery is explicit and never an automatic retry loop.
coordinate-setup
Discover coding CLIs on the current computer and configure a Coordinate Agents implementation agent. Use for setup, executable checks, registered agents, user-level configuration, and project-over-user precedence.
coordinate-review
Review a Coordinate Agents implementation as the Codex Reviewer. Verify the real commit, diff, tests, validation evidence, and specification without modifying the Implementer's product code.
antigravity-agents
This document manages all domain-specific .agents/skills/ /SKILL.md files.