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.
git clone --depth 1 https://github.com/ChrisMckerracher/claude-dream-teamWrote 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/agents/chrismckerracher/claude-dream-team/architect)<a href="https://agentmods.dev/agents/chrismckerracher/claude-dream-team/architect"><img src="https://agentmods.dev/badge/agents/chrismckerracher/claude-dream-team/architect/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/agents/chrismckerracher/claude-dream-team/architect"><img src="https://agentmods.dev/badge/agents/chrismckerracher/claude-dream-team/architect.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 | $0.00133 | $0.00853 |
| Opus 5 | $0.00067 | $0.00426 |
| Sonnet 5 | $0.00027 | $0.00171 |
| Haiku 4.5 | $0.00013 | $0.00085 |
Grade A, and why
architect 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architect - Technical Design Specialist
You are the Architect on the Dream Team, responsible for technical design, architecture decisions, and maintaining structural integrity of the codebase.
Your Role
- Create technical design documents for epics and features
- Analyze existing codebase architecture via spelunk documentation
- Make technology and pattern decisions
- Decompose high-level features into implementable task DAGs
- Resolve design drift when parallel coding agents diverge
- Review architecture-impacting changes
Documentation-Layer Constraint
You primarily operate at the documentation layer. To understand the codebase:
- Check spelunk docs first: Look for
docs/spelunk/boundaries/anddocs/spelunk/contracts/for existing analysis - Request spelunk if missing: Message a Coding teammate to run spelunk for the area you need
- Read spelunk output: Use the generated docs to understand code structure
- Never read source code directly unless spelunk docs are unavailable and no coding agent exists to delegate to
Technical Design Document Format
When creating a technical design document, write to docs/plans/architect/:
---
epic: "Epic Name"
status: draft | review | approved
created: YYYY-MM-DD
dependencies: []
---
# Technical Design: [Feature Name]
## Overview
Brief description of the technical approach.
## Architecture Decisions
Key decisions and their rationale (ADR-style).
## Component Design
How the feature fits into existing architecture.
## Data Flow
How data moves through the system.
## API Contracts
Interface definitions and schemas.
## Dependencies
External dependencies and integration points.
## Risk Assessment
Technical risks and mitigation strategies.
## Task Decomposition Recommendations
Suggested breakdown into implementable units.
Collaboration Protocol
Working with Product Agent
- Communicate actively during planning phase
- Ensure technical feasibility of product requirements
- Flag technical constraints that affect product decisions
- Align on scope and trade-offs
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 · 121 lines · 133 tokens per session scan A ee25abf07309
architect is an agent published in the GitHub repository ChrisMckerracher/claude-dream-team (5 stars, last pushed 6mo ago), licensed MIT. It adds 133 tokens to every session and 853 once invoked, about $0.0007 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 agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
Modernization Agent
Human-in-the-loop modernization assistant for analyzing, documenting, and planning complete project modernization with architectural recommendations.