architecture-review

architecture-review is a skill for Claude Code, Codex from jstoup111/ai-conductor. It costs 48 tokens per session (9,353 once invoked), scanned A, original, Apache-2.0.

A restricted architecture review used at defined points in a software project workflow, especially before implementation stories are written.

In plain words
What is it for?
Use it during the active harness lifecycle for pre-story feasibility reviews, batch-level checks for architectural drift, or the final as-built review.
Why use it?
It checks whether a proposed design is feasible, identifies hidden complexity and violations of system boundaries, and records approved architecture decisions before later work depends on them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md; mentions subagents; mentions Claude Code.

Good fit Use it during the active harness lifecycle for pre-story feasibility reviews, batch-level checks for architectural drift, or the final as-built review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jstoup111/ai-conductor/architecture-review
Install

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.

Any agent
npx skills add jstoup111/ai-conductor --skill architecture-review
Clone the repo
git clone --depth 1 https://github.com/jstoup111/ai-conductor

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for architecture-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/jstoup111/ai-conductor/architecture-review/github.svg)](https://agentmods.dev/skills/jstoup111/ai-conductor/architecture-review)
Your own site
<a href="https://agentmods.dev/skills/jstoup111/ai-conductor/architecture-review"><img src="https://agentmods.dev/badge/skills/jstoup111/ai-conductor/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.

agentmods 80×15 button for architecture-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/jstoup111/ai-conductor/architecture-review"><img src="https://agentmods.dev/badge/skills/jstoup111/ai-conductor/architecture-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,353 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 135
    Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.
    Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
  • medium Rogue Agent · line 249
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
  • medium Excessive Agency · line 360
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 372
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 384
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.09353
Opus 5 $0.00024 $0.04677
Sonnet 5 $0.00010 $0.01871
Haiku 4.5 $0.00005 $0.00935

Measured 3d ago against content hash 886cfee1c5c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 3d 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.

skills/architecture-review/SKILL.md · 643 lines

How it starts

The opening of the file, as written. The whole thing — 643 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

Reviews the design through an architectural lens BEFORE stories are written and before any code. Catches technical infeasibility, hidden complexity, architectural drift, and domain violations early — when they're cheap to fix. This is where the how is resolved (so the PRD stays product-only) and captured as APPROVED ADRs.

Read the Scope boundary: from .docs/track/<slug>.md as binding; preserve the confirmed narrow/comprehensive breadth outcome; do not permit a materially broader expansion beyond it unless the operator confirms before it enters the artifact.

Run after /prd (product track) or /explore (technical track), and BEFORE /stories (adr-2026-06-29-architecture-before-stories-convergent-kickback). The review's input is the PRD's functional requirements (product) or the explore output + technical intent (technical) — stories and the plan do not exist yet at this point.

Also invocable at pipeline batch boundaries to verify implementation stays architecturally sound.

Correctness gate: an ADR is the most load-bearing artifact in the flow — everything downstream builds on it. Apply the /verify-claims protocol before writing any APPROVED ADR: state each technical claim with a grounded confidence % and its basis (verified vs inferred), surface every assumption the design rests on, and HARD-BLOCK (operator approval interactive, HALT if autonomous) on any unconfirmed assumption that would change the decision. Do not record a decision as APPROVED while it rests on an unconfirmed load-bearing assumption.

Provider-native delegation

When this review delegates exploration or analysis, use the selected host's available subagent facility. Preserve the scope limits, evidence, ADR output, and veto/gate behavior regardless of host. Claude delegation: Claude uses the Agent tool; any Claude model choice is confined to that facility. A Codex-selected run uses its available subagent facility and configured Codex provider policy, without translating Claude model names.

Read the full file on GitHub · 643 lines

Changes

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.

  1. 3d ago Changed · +56 lines 886cfee1c5c3
  2. 4d ago Changed · +5 lines f1c48e6bdc00
  3. 11d ago First seen · 582 lines · 48 tokens per session scan A b8b51d2dbe75

Subscribe to this mod's changes

architecture-review is a skill published in the GitHub repository jstoup111/ai-conductor (7 stars, last pushed today), licensed Apache-2.0. It adds 48 tokens to every session and 9,353 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 2026-08-31.

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