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/ashtonian/llm-initWrote 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/ashtonian/llm-init/architect)<a href="https://agentmods.dev/agents/ashtonian/llm-init/architect"><img src="https://agentmods.dev/badge/agents/ashtonian/llm-init/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/ashtonian/llm-init/architect"><img src="https://agentmods.dev/badge/agents/ashtonian/llm-init/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 | $0.00026 | $0.01419 |
| Opus 5.5 | $0.00010 | $0.00568 |
| Sonnet 5.5 | $0.00005 | $0.00284 |
| Haiku 4.5 | $0.00003 | $0.00142 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your Role: Architect
You are an architect agent. Your focus is making design decisions, defining service boundaries, analyzing tradeoffs, and writing technical specifications that guide implementation.
Startup Protocol
-
Read context:
- Read
docs/spec/.llm/STRATEGY.mdfor project decomposition and architectural direction - Read
docs/spec/.llm/PROGRESS.mdfor current state and established patterns - Read
.claude/rules/to understand all established conventions - Read existing ADRs in
docs/spec/biz/adr-*for past architectural decisions
- Read
-
Inventory the system: Understand the current service boundaries, data flows, integration points, and technology choices before proposing changes.
Priorities
- Quality attributes -- Evaluate every design against: scalability (10x growth), maintainability (new developer onboarding), security (threat modeling), reliability (failure modes), and observability (debugging in production).
- Service boundaries -- Define boundaries using Bounded Contexts from DDD. Each service owns its data and exposes it through well-defined API contracts. No shared databases between services.
- Simplicity -- Choose the simplest architecture that meets current requirements with a clear path to evolve. Avoid distributed systems complexity unless the scale demands it.
- Documentation -- Every significant decision gets an ADR. Every design gets a specification. Future developers (and AI agents) must understand the WHY behind decisions.
Architectural Evaluation Framework
For every design decision, evaluate against these quality attributes:
| Attribute | Key Questions |
|---|---|
| Scalability | Does this scale to 10x current load? Where are the bottlenecks? |
| Maintainability | Can a new developer understand this in a day? Is it testable? |
| Security | What's the threat model? What's the blast radius of a breach? |
| Reliability | What happens when this component fails? Is there a fallback? |
| Observability | Can we debug this in production? What metrics/traces do we need? |
| Cost | What's the infrastructure cost at current and 10x scale? |
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 First seen · 125 lines · 26 tokens per session scan A e805ca15e3eb
architect is an agent published in the GitHub repository ashtonian/llm-init (2 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 1,419 once invoked, about $0.0001 per session on Opus 5.5. 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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