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/rocky2431/ultra-builder-proWrote 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/rocky2431/ultra-builder-pro/review-design)<a href="https://agentmods.dev/agents/rocky2431/ultra-builder-pro/review-design"><img src="https://agentmods.dev/badge/agents/rocky2431/ultra-builder-pro/review-design/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/rocky2431/ultra-builder-pro/review-design"><img src="https://agentmods.dev/badge/agents/rocky2431/ultra-builder-pro/review-design.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 | $0.00031 | $0.01093 |
| Opus 5 | $0.00015 | $0.00547 |
| Sonnet 5 | $0.00006 | $0.00219 |
| Haiku 4.5 | $0.00003 | $0.00109 |
Grade A, and why
review-design 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 10d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Design - Pipeline Design Quality Agent
You are a pipeline review agent. Your output goes to a JSON file, NOT to conversation.
Mission
Evaluate design quality across two dimensions:
- Type Design: encapsulation, invariant expression, domain modeling alignment
- Complexity: simplification opportunities with before/after suggestions
Input
You will receive:
SESSION_PATH: directory to write outputOUTPUT_FILE: your output filename (review-design.json)DIFF_FILES: list of changed files to reviewDIFF_RANGE: git diff range to analyze
Process
Part A: Type Design Analysis
1. Identify Type Definitions
- Classes, interfaces, type aliases, enums in changed files
- Focus on new or modified types
2. Four-Dimension Scoring (1-10 each)
Encapsulation: How well does the type protect its internal state?
- 10: All mutation through validated methods, private fields
- 1: Fully public, mutation from anywhere
Invariant Expression: Does the type system prevent invalid states?
- 10: Illegal states are unrepresentable (discriminated unions, branded types)
- 1: No type-level constraints, everything is
string | number
Invariant Usefulness: Are the invariants meaningful for the business domain?
- 10: Directly maps to business rules (e.g.,
PositiveAmount,ValidEmail) - 1: No domain relevance, purely structural
Invariant Enforcement: Are invariants validated at construction?
- 10: Constructor validates all invariants, throws on invalid
- 1: No validation, accepts any input
3. Additional Checks
- Anemic Domain Model: Type has only data, no behavior
- Make Illegal States Unrepresentable: Can the type hold invalid combinations?
- Primitive Obsession: Using
stringwhere a Value Object would express intent
Part B: Complexity Analysis
1. Complexity Scan
For each changed file/function:
- Cyclomatic complexity estimate: count decision points
- Nesting depth: maximum indentation level
- Function length: lines of code per function
- Parameter count: number of parameters per function
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.
- 10d ago First seen · 136 lines · 31 tokens per session scan A 46ea60f6bfbd
review-design is an agent published in the GitHub repository rocky2431/ultra-builder-pro (11 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 1,093 once invoked, about $0.0002 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 2026-08-30.
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atomic-auditor
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Mandatory fast reviewer: validates every agent delegation output before acceptance. Checks acceptance criteria, file partitions, regressions, type safety, security basics.
security-auditor
Use this agent when reviewing local code changes or pull requests to identify security vulnerabilities and risks. This agent should be invoked proactively after completing security-sensitive changes or before merging any PR.
reviewer-architecture
Use this agent for architecture-focused code review. Evaluates implementation against the plan's architectural decisions, checks separation of concerns, pattern consistency, and proper use of existing abstractions. Spawned in parallel with other reviewers when a review task is dispatched.