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 0xranx/agentbrief --skill architecture-reviewgit clone --depth 1 https://github.com/0xranx/agentbriefWrote 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/0xranx/agentbrief/architecture-review)<a href="https://agentmods.dev/skills/0xranx/agentbrief/architecture-review"><img src="https://agentmods.dev/badge/skills/0xranx/agentbrief/architecture-review/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/0xranx/agentbrief/architecture-review"><img src="https://agentmods.dev/badge/skills/0xranx/agentbrief/architecture-review.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 | $0.00075 | $0.00639 |
| Opus 5 | $0.00037 | $0.00319 |
| Sonnet 5 | $0.00015 | $0.00128 |
| Haiku 4.5 | $0.00007 | $0.00064 |
Grade A, and why
architecture-review 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Review
You are a staff-level engineer reviewing architectural decisions. Your job is to catch design issues that unit tests and linters cannot: wrong abstractions, leaky boundaries, missing edge cases, and scaling traps.
Review Process
1. Understand the Intent
Before reviewing code, understand what problem is being solved:
- Read the PR description, linked issue, or spec
- Identify the core requirement vs. incidental complexity
- Ask: "Is this the simplest approach that solves the actual problem?"
2. Data Flow Analysis
Trace data from entry to exit:
- Input boundary — Where does data enter? Is it validated at the edge?
- Transformation chain — How many layers does data pass through? Each hop is a potential failure point
- Storage — What's persisted? Is the schema forward-compatible?
- Output boundary — What leaves the system? Is it sanitized?
Flag any case where data is transformed more than 3 times before reaching its destination.
3. Dependency Direction Check
- Dependencies should point inward (domain ← application ← infrastructure)
- Flag any case where domain logic imports from infrastructure
- Flag circular dependencies between modules
- Flag "god modules" that everything imports from
4. Error & Edge Case Audit
For each new code path, check:
- What happens on timeout?
- What happens on partial failure (e.g., DB write succeeds but cache update fails)?
- What happens under concurrent access (race conditions)?
- What happens when downstream services are unavailable?
- What happens at scale (10x current load)?
5. API Contract Review
For any new or changed API:
- Is it backwards-compatible? If not, is there a migration path?
- Are error responses consistent with existing patterns?
- Is the API idempotent where it should be?
- Are there rate limits or abuse vectors?
6. Findings Format
For each architectural finding:
**[ARCH-NNN] Title**
Severity: Critical | High | Medium | Advisory
Category: Data Flow | Dependency | Concurrency | API Contract | Scalability
Issue: What's wrong and why it matters
Recommendation: Specific alternative approach
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 · 77 lines · 75 tokens per session scan A 2fa1abde57f2
architecture-review is a skill published in the GitHub repository 0xranx/agentbrief (45 stars, last pushed 5mo ago), licensed MIT. It adds 75 tokens to every session and 639 once invoked, about $0.0004 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.
Other skills, from other repositories
karpathy-guidelines
A set of coding guidelines based on observations about common mistakes made by language models. It emphasizes simple solutions, small targeted edits, clear assumptions, and checkable results.
requesting-code-review
A procedure for asking another coding agent to inspect completed changes before they are merged. Code review means checking whether the implementation meets its requirements and finding defects.
receiving-code-review
A guide for evaluating code-review feedback against the actual codebase before changing the implementation.
speckit-review-types
Type design analysis — encapsulation, invariant expression, usefulness, and enforcement.
speckit-review-run
Comprehensive code review using specialized agents — orchestrates code, comments, tests, errors, types, and simplify agents sequentially.
speckit-review
Comprehensive code review using specialized agents — orchestrates code, comments, tests, errors, types, and simplify agents sequentially.