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/ayoubben18/ab-method/improve-codebase-architecturenpx skills add ayoubben18/ab-method --skill improve-codebase-architecturegit clone --depth 1 https://github.com/ayoubben18/ab-methodWhat 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 | $0.00085 | $0.01646 |
| Opus 5 | $0.00043 | $0.00823 |
| Sonnet 5 | $0.00017 | $0.00329 |
| Haiku 4.5 | $0.00009 | $0.00165 |
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 3d 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 — 81 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.
This skill is built on a shared design vocabulary and informed by the project's domain model:
- Architecture vocabulary — run the
codebase-designskill for the terms (module, interface, depth, seam, adapter, leverage, locality) and the principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use those terms exactly in every suggestion — don't drift into "component," "service," "API," or "boundary." It is the single source; this skill doesn't restate it. - Domain language —
CONTEXT.mdgives names to good seams; ADRs indocs/adr/record decisions this skill should not re-litigate. See CONTEXT-FORMAT.md and ADR-FORMAT.md.
Process
1. Explore
Scope before you scan — YAGNI. Deepening a module pays off by making future changes to it easier, so weight the parts of the codebase that keep changing. Decide where to look before looking:
- If the user named a direction — a module, a subsystem, a pain point — take it and skip the inference below.
- Otherwise walk back a good stretch of history (
git log --oneline) 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.
Read the existing documentation first:
CONTEXT.md(orCONTEXT-MAP.md+ eachCONTEXT.mdin a multi-context repo)- Relevant ADRs in
docs/adr/(and any context-scopeddocs/adr/directories)
If any of these files don't exist, proceed silently — don't flag their absence or suggest creating them upfront.
Then use the Agent tool with subagent_type=Explore to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:
What ships with it
1 file 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.
- 3d ago First seen · 81 lines · 85 tokens per session scan A 0e4eb660d7fe
improve-codebase-architecture is a skill published in the GitHub repository ayoubben18/ab-method (187 stars, last pushed 1mo ago), licensed MIT. It adds 85 tokens to every session and 1,646 once invoked, about $0.0004 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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