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 skills/notysoty/openagentskills/architecture-explainernpx skills add Notysoty/openagentskills --skill architecture-explainergit clone --depth 1 https://github.com/Notysoty/openagentskillsWrote 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/notysoty/openagentskills/architecture-explainer)<a href="https://agentmods.dev/skills/notysoty/openagentskills/architecture-explainer"><img src="https://agentmods.dev/badge/skills/notysoty/openagentskills/architecture-explainer.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 5.1 | $0.00022 | $0.01656 |
| Opus 5 | $0.00011 | $0.00828 |
| Sonnet 5 | $0.00004 | $0.00331 |
| Haiku 4.5 | $0.00002 | $0.00166 |
Grade A, and why
Architecture Explainer 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 5d 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Explainer
What this skill does
This skill directs the agent to explore a codebase or system description and produce a clear, structured architecture overview. It maps out layers, major components, data flows, and external dependencies, then renders ASCII diagrams showing how the pieces connect. The result is a document a new engineer could read in 10 minutes and understand how the system works.
Use this when onboarding new team members, preparing for an architecture review, creating documentation for a system you inherited, or clarifying your own mental model before a large refactor.
How to use
Claude Code / Cline
Copy this file to .agents/skills/architecture-explainer/SKILL.md in your project root.
Then ask:
- "Use the Architecture Explainer skill to document this entire repo."
- "Explain the architecture of the
server/directory using the Architecture Explainer skill." - "I'll describe our system. Use the Architecture Explainer skill to turn it into a structured overview."
Cursor
Add the instructions below to your .cursorrules or paste them into the Cursor AI pane before asking for the architecture overview.
Codex
Provide a directory listing or paste key files and ask Codex to follow the instructions below to produce the architecture document.
The Prompt / Instructions for the Agent
When asked to explain or document an architecture, follow these steps:
Step 1 — Explore the codebase
Start by reading:
- The root directory listing
package.json,pyproject.toml,go.mod, or the equivalent dependency manifest- Entry point files (e.g.,
main.ts,index.ts,app.py,cmd/main.go) - Top-level directory names and their
indexorREADMEfiles if present - Any existing architecture or design docs
Do not read every file. Use the directory structure and entry points to infer the layering.
Step 2 — Identify the major components
Extract:
- Layers: presentation, business logic, data access, infrastructure
- Services or modules: each significant unit of functionality
- External dependencies: databases, caches, third-party APIs, message queues
- Entry points: HTTP routes, CLI commands, event listeners, cron jobs
- Shared utilities: auth, logging, config, error handling
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.
- 5d ago First seen · 202 lines · 22 tokens per session scan A 0a83677434d1
Architecture Explainer is a skill published in the GitHub repository Notysoty/openagentskills (9 stars, last pushed 22d ago), licensed MIT. It adds 22 tokens to every session and 1,656 once invoked, about $0.0001 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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