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 skills add sammcj/agentic-coding --skill improve-codebase-architecturegit clone --depth 1 https://github.com/sammcj/agentic-codingWrote 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/sammcj/agentic-coding/improve-codebase-architecture)<a href="https://agentmods.dev/skills/sammcj/agentic-coding/improve-codebase-architecture"><img src="https://agentmods.dev/badge/skills/sammcj/agentic-coding/improve-codebase-architecture/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/skills/sammcj/agentic-coding/improve-codebase-architecture"><img src="https://agentmods.dev/badge/skills/sammcj/agentic-coding/improve-codebase-architecture.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 | $0.00066 | $0.01587 |
| Opus 5.5 | $0.00026 | $0.00635 |
| Sonnet 5.5 | $0.00013 | $0.00317 |
| Haiku 4.5 | $0.00007 | $0.00159 |
Grade A, and why
improve-codebase-architecture 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 18d 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.
This is a copy
86% identical to improve-codebase-architecture — 71 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Improve Codebase Architecture
Surface architectural friction and propose deepening opportunities - refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.
Glossary
Use these terms exactly in every suggestion. Consistent language is the point - don't drift into "component," "service," "API," or "boundary." Full definitions in LANGUAGE.md.
- Module - anything with an interface and an implementation (function, class, package, slice).
- Interface - everything a caller must know to use the module: types, invariants, error modes, ordering, config. Not just the type signature.
- Implementation - the code inside.
- Depth - leverage at the interface: a lot of behaviour behind a small interface. Deep = high leverage. Shallow = interface nearly as complex as the implementation.
- Seam - where an interface lives; a place behaviour can be altered without editing in place. (Use this, not "boundary.")
- Adapter - a concrete thing satisfying an interface at a seam.
- Leverage - what callers get from depth.
- Locality - what maintainers get from depth: change, bugs, knowledge concentrated in one place.
Key principles (see LANGUAGE.md for the full list):
- Deletion test: imagine deleting the module. If complexity vanishes, it was a pass-through. If complexity reappears across N callers, it was earning its keep.
- The interface is the test surface.
- One adapter = hypothetical seam. Two adapters = real seam.
This skill is informed by the project's domain model. The domain language gives names to good seams; ADRs record decisions the skill should not re-litigate.
Process
1. Explore
Scope before you scan - YAGNI. Deepening a module pays off by making future changes to it easier, so a deepening opportunity in code nobody touches is a refactor you never cash in. Decide where to look before you look:
- If the user named a direction - a module, a subsystem, a pain point - take it and skip the inference below.
- Otherwise, read back over the last ~20 commits (
git log --oneline -20 --name-only) to find the hot spots - the files and areas that keep coming up - and let those paths pull your attention first. If the changes are scattered with no clear hot spot, widen the net.
What ships with it
4 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.
- 18d ago Changed 0690ed038fdc
- 19d ago Changed b441270fd8dc
- 1mo ago First seen · 89 lines · 66 tokens per session scan A 7a9cb134503d
improve-codebase-architecture is a skill published in the GitHub repository sammcj/agentic-coding (167 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 1,587 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to improve-codebase-architecture, differing in 71 lines, and is treated as a copy.
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