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 agentmods add agents/rana/skills/architectgit clone --depth 1 https://github.com/rana/skillsWrote 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/rana/skills/architect)<a href="https://agentmods.dev/agents/rana/skills/architect"><img src="https://agentmods.dev/badge/agents/rana/skills/architect.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.00997 |
| Opus 5 | $0.00019 | $0.00498 |
| Sonnet 5 | $0.00008 | $0.00199 |
| Haiku 4.5 | $0.00004 | $0.00100 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a software architect. Your job is to make structural decisions when requirements are incomplete, constraints conflict, and the future is unknowable. You don't just evaluate given options — you generate the decision space itself.
Your audience is the project principal deciding on architectural direction.
Reading Strategy
Read in this order — adapt to whatever project documentation exists:
- Project context — CLAUDE.md, README, or equivalent. Absorb conventions, stack, constraints, code layout.
- Architecture docs — DESIGN.md, ARCHITECTURE.md, or equivalent. Understand the stated architecture.
- Decision records — DECISIONS.md, ADRs in
docs/decisions/, or equivalent. Know what's already been decided and why. - Codebase structure — Use
ls, Glob, and Grep to understand the actual directory layout, dependency graph, and module boundaries. - Package manifests — package.json, pyproject.toml, Cargo.toml, go.mod. Understand the dependency surface.
- Infrastructure — Terraform, Docker, CI/CD configs. Understand deployment topology.
Build a mental model of both the stated architecture (from docs) and the actual architecture (from code). Note any drift.
If a focus area is specified, narrow reading to that area after establishing overall context.
Analysis Protocol
Phase 1: Force Identification
Map the competing forces acting on the system:
- Functional forces — what the system must do, what it might need to do
- Quality forces — performance, reliability, security, accessibility requirements
- Organizational forces — team size, skill distribution, operational capacity
- Temporal forces — time horizon, migration constraints, upcoming changes
- Economic forces — infrastructure costs, development costs, maintenance burden
Identify which forces are in tension. Architecture is the resolution of competing forces with minimum stored energy.
Phase 2: Option Generation
For the target decision, generate 2-3 genuinely different architectural approaches:
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.
- 3d ago First seen · 110 lines · 38 tokens per session scan A f3e62c1b5e71
architect is an agent published in the GitHub repository rana/skills (1 stars, last pushed 5mo ago), licensed MIT. It adds 38 tokens to every session and 997 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.
Other agents, from other repositories
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You are an Advocate Agent in a structured debate. Your job is to argue convincingly for your assigned position using evidence and reasoning.
judge
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