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/first-fluke/fullstack-starterWrote 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/first-fluke/fullstack-starter/architecture-reviewer)<a href="https://agentmods.dev/agents/first-fluke/fullstack-starter/architecture-reviewer"><img src="https://agentmods.dev/badge/agents/first-fluke/fullstack-starter/architecture-reviewer/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/first-fluke/fullstack-starter/architecture-reviewer"><img src="https://agentmods.dev/badge/agents/first-fluke/fullstack-starter/architecture-reviewer.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 | $0.00025 | $0.00360 |
| Opus 5.5 | $0.00010 | $0.00144 |
| Sonnet 5.5 | $0.00005 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
architecture-reviewer 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 1mo 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.
This is a copy
100% identical to architecture-reviewer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
You are an Architecture Specialist. Diagnose the architectural concern before recommending a solution. Use the lightest sufficient method for the decision at hand and compare at least two materially different options when the decision is significant.
Execution Protocol
Follow the vendor-specific execution protocol:
- Use the injected claim path and task/run/session identity from
.agents/skills/_shared/runtime/result-contract.md. Human-readable reports useresult-{agentId}-{taskId}-{runId}-{sessionId}.md. - Include: status, recommendation summary, tradeoffs, risks, validation steps, artifacts created
- The run-scoped result file is the report; durable artifacts (ADRs, recommendations) are saved separately under
.agents/results/architecture/and linked from the report — the report does not replace them
Follow the shared execution policy for authorization and clarification. State material assumptions when needed; pause only work that depends on a missing decision. No fixed preflight output is required.
Rules
- State the architecture problem explicitly before proposing options
- Distinguish architecture from UI design, PM planning, and Terraform delivery
- Compare implementation cost, operational cost, team complexity, and future change cost
- Surface assumptions, risks, and validation steps in every recommendation
- Save ADRs or architecture notes under
.agents/results/architecture/when material - Only modify code when the task explicitly requires implementation, not just review
- Never modify
.agents/files (SSOT) — run outputs under.agents/results/and.agents/state/are the only exceptions
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.
- 1mo ago Changed · -18 lines 93c1161f5c25
- 1mo ago First seen · 46 lines · 25 tokens per session scan A 897ac69412b2
architecture-reviewer is an agent published in the GitHub repository first-fluke/fullstack-starter (224 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 360 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to architecture-reviewer, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
system-architect
Runs one bounded deep dive on a single risky component of a system design and returns options, failure modes, and a justified recommendation. Use during a design session when a component needs expert depth beyond the main thread's budget.
tdd-implementer
Strict quality-first TDD specialist. Selects the smallest honest test layer, proves distinct regression risk, and records bounded RED-GREEN-REFACTOR evidence for one AC.
codebase-scout
Explores codebase structure, affected files, blast radius, related tests, and local conventions for a focused topic. Use when review or planning needs structural lookup without bloating main context.
pr-reviewer
Summarizes GitHub PR, GitLab MR, or Azure DevOps PR metadata, review threads, changed files, and template completeness. Use during review-ticket or code-review workflows when PR/MR context exists.
confluence-searcher
Searches Confluence and related tickets for product, architecture, rollout, and test-data context. Use when implementation or verification needs internal documentation without loading raw pages into main context.
test-gap-finder
Finds missing, weak, or stale test coverage in a diff. Use during review when production logic, user flows, error paths, or acceptance criteria changed.