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 StChiotis/Library-First-Engineering --skill lfe-improve-architecturegit clone --depth 1 https://github.com/StChiotis/Library-First-EngineeringWrote 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/stchiotis/library-first-engineering/lfe-improve-architecture)<a href="https://agentmods.dev/skills/stchiotis/library-first-engineering/lfe-improve-architecture"><img src="https://agentmods.dev/badge/skills/stchiotis/library-first-engineering/lfe-improve-architecture.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 | $0.00043 | $0.00772 |
| Opus 5 | $0.00022 | $0.00386 |
| Sonnet 5 | $0.00009 | $0.00154 |
| Haiku 4.5 | $0.00004 | $0.00077 |
Grade A, and why
lfe-improve-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 8d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LFE Improve Architecture
Position in Pipeline
- Phase: 5 (Hygiene sub-pipeline, Step 2)
- Persona: Architect
- Trigger: Scheduled every 5 sessions (tracked in
pipeline_status.md)
Vocabulary
Use these terms exactly; keep "component," "service," "API," and "boundary" out of architectural suggestions. See LANGUAGE.md for full definitions.
- Module — anything with an interface and an implementation
- Interface — everything a caller must know to use the module
- Implementation — the code inside
- Depth — leverage at the interface: a lot of behavior behind a small interface
- Seam — where an interface lives; a place behavior can be altered without editing in place
- Adapter — a concrete thing satisfying an interface at a seam
- Leverage — what callers get from depth
- Locality — what maintainers get from depth
Key Principles
- 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.
Process
1. Explore
Read the project's domain glossary (CONTEXT.md) and any ADRs first.
Then walk the codebase organically and note friction:
- Where does understanding one concept require bouncing between many small modules?
- Where are modules shallow — interface nearly as complex as the implementation?
- Where have pure functions been extracted just for testability, but real bugs hide in how they're called?
- 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 suspected shallow.
2. Present candidates
Numbered list of deepening opportunities. For each:
- Files — which files/modules are involved
- Problem — why the current architecture causes friction
- Solution — plain English description of what would change
- Benefits — in terms of locality and leverage, and how tests would improve
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.
- 8d ago First seen · 69 lines · 43 tokens per session scan A 7417ed759963
lfe-improve-architecture is a skill published in the GitHub repository StChiotis/Library-First-Engineering (43 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 772 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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