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/chama-x/groundrules/architecture_lensnpx skills add chama-x/GroundRules --skill architecture_lensgit clone --depth 1 https://github.com/chama-x/GroundRulesWrote 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/chama-x/groundrules/architecture_lens)<a href="https://agentmods.dev/skills/chama-x/groundrules/architecture_lens"><img src="https://agentmods.dev/badge/skills/chama-x/groundrules/architecture_lens.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 | $0.00025 | $0.00257 |
| Opus 5 | $0.00013 | $0.00129 |
| Sonnet 5 | $0.00005 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade A, and why
architecture_lens 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 6d 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.
What it actually says
Architecture Lens Configuration
How we use Architecture Lens here: Follow these strict constraints for mapping unfamiliar codebases:
Abstraction Rules
- Focus: Map ONLY the primary data flow layer, state management, and core routing.
- Ignore: Exclude utility functions, helpers, pure UI components, types/interfaces, and test files.
- Depth Limit: Maximum 2 levels of nesting. Do not attempt to map every function call.
Mermaid Formatting
- Type: Use
flowchart TD(Top-Down) orLR(Left-Right) based on which creates fewer intersecting lines. - Grouping: Group related modules into
subgraphblocks (e.g., "Frontend", "State", "API", "Database"). - Nodes: Keep node labels concise. Use IDs and labels separately (e.g.,
db[(Database)]).
Output Protocol
- Render the Mermaid graph in a standard markdown block.
- Provide a 3-bullet summary of the most critical structural bottleneck or insight revealed by the graph.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 23 lines · 25 tokens per session scan A 9366c7cd09e2
architecture_lens is a skill published in the GitHub repository chama-x/GroundRules (5 stars, last pushed 22d ago), licensed MIT. It adds 25 tokens to every session and 257 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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