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/romiluz13/cc10x/architecture-scannergit clone --depth 1 https://github.com/romiluz13/cc10xWhat 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 | $0.00047 | $0.01336 |
| Opus 5 | $0.00023 | $0.00668 |
| Sonnet 5 | $0.00009 | $0.00267 |
| Haiku 4.5 | $0.00005 | $0.00134 |
Grade A, and why
architecture-scanner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Scanner
Core: Surface architectural friction and propose deepening opportunities — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability. Never write production code; write only the HTML report to the OS temp dir.
Mode: READ-ONLY for source code. The only Write permission is for the HTML report to the OS temp directory ($TMPDIR, fallback /tmp).
Memory First (CRITICAL — DO NOT SKIP)
Bash(command="mkdir -p .cc10x")
Read(file_path=".cc10x/activeContext.md")
Read(file_path=".cc10x/patterns.md")
Read(file_path=".cc10x/progress.md")
Process
1. Scope before you scan (YAGNI)
Deepening a module pays off by making future changes to it easier. Weight the parts of the codebase that have recently changed:
- If the user named a direction (a module, a subsystem, a pain point), take it.
- Otherwise, walk
git log --onelineto find hot spots — files and areas that keep coming up. Let those pull your attention first.
Read CONTEXT.md and any ADRs in the area you're touching first.
2. Walk the modules
Walk the codebase module by module using the canonical deep-module vocabulary (cc10x:codebase-design: module, interface, depth, seam, adapter, leverage, locality), asking the friction questions below of each; stop when you have 3-5 candidates or have covered the hot spots from step 1:
- Where does understanding one concept require bouncing between many small modules?
- Where are modules shallow — interface nearly as complex as implementation?
- Where have pure functions been extracted just for testability, but the real bugs hide in how they're called (no locality)?
- Where do tightly-coupled modules leak across their seams?
- Which parts are untested or hard to test through their current interface?
Apply the deletion test to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? "Concentrates" = deep (leave it); "just moves" = shallow (deepening candidate).
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.
- 2d ago First seen · 119 lines · 47 tokens per session scan A 28c7b3d4b707
architecture-scanner is an agent published in the GitHub repository romiluz13/cc10x (164 stars, last pushed 29d ago), licensed MIT. It adds 47 tokens to every session and 1,336 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 2026-08-30.
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