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/zebbern/claude-code-guide/deep-module-refactornpx skills add zebbern/claude-code-guide --skill deep-module-refactorgit clone --depth 1 https://github.com/zebbern/claude-code-guideWhat 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 | $0.00062 | $0.00866 |
| Opus 5 | $0.00031 | $0.00433 |
| Sonnet 5 | $0.00012 | $0.00173 |
| Haiku 4.5 | $0.00006 | $0.00087 |
Grade A, and why
deep-module-refactor 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- improve-codebase-architecture — 97% identical, 2 lines differ
- improve-codebase-architecture — 97% identical, 2 lines differ
- improve-codebase-architecture — 97% identical, 3 lines differ
- improve-codebase-architecture — 97% identical, 2 lines differ
- improve-codebase-architecture — 97% identical, 2 lines differ
- improve-codebase-architecture — 97% identical, 5 lines differ
- improve-codebase-architecture — 95% identical, 6 lines differ
- improve-codebase-architecture — 84% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Improve Codebase Architecture
Explore a codebase like an AI would, surface architectural friction, discover opportunities for improving testability, and propose module-deepening refactors as GitHub issue RFCs.
A deep module (John Ousterhout, "A Philosophy of Software Design") has a small interface hiding a large implementation. Deep modules are more testable, more AI-navigable, and let you test at the boundary instead of inside.
Process
1. Explore the codebase
Use the Agent tool with subagent_type=Explore to navigate the codebase naturally. Do NOT follow rigid heuristics — explore organically and note where you experience friction:
- Where does understanding one concept require bouncing between many small files?
- Where are modules so shallow that the interface is nearly as complex as the implementation?
- Where have pure functions been extracted just for testability, but the real bugs hide in how they're called?
- Where do tightly-coupled modules create integration risk in the seams between them?
- Which parts of the codebase are untested, or hard to test?
The friction you encounter IS the signal.
2. Present candidates
Present a numbered list of deepening opportunities. For each candidate, show:
- Cluster: Which modules/concepts are involved
- Why they're coupled: Shared types, call patterns, co-ownership of a concept
- Dependency category: See REFERENCE.md for the four categories
- Test impact: What existing tests would be replaced by boundary tests
Do NOT propose interfaces yet. Ask the user: "Which of these would you like to explore?"
3. User picks a candidate
4. Frame the problem space
Before spawning sub-agents, write a user-facing explanation of the problem space for the chosen candidate:
- The constraints any new interface would need to satisfy
- The dependencies it would need to rely on
- A rough illustrative code sketch to make the constraints concrete — this is not a proposal, just a way to ground the constraints
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.
- 2d ago First seen · 77 lines · 62 tokens per session scan A 1c407bbba0bf
deep-module-refactor is a skill published in the GitHub repository zebbern/claude-code-guide (4,597 stars, last pushed yesterday), licensed MIT. It adds 62 tokens to every session and 866 once invoked, about $0.0003 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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