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/ariaxhan/kernel-claude/architecturenpx skills add ariaxhan/kernel-claude --skill architecturegit clone --depth 1 https://github.com/ariaxhan/kernel-claudeWrote 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/ariaxhan/kernel-claude/architecture)<a href="https://agentmods.dev/skills/ariaxhan/kernel-claude/architecture"><img src="https://agentmods.dev/badge/skills/ariaxhan/kernel-claude/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 | $0.00040 | $0.00519 |
| Opus 5 | $0.00020 | $0.00260 |
| Sonnet 5 | $0.00008 | $0.00104 |
| Haiku 4.5 | $0.00004 | $0.00052 |
Grade A, and why
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 4d 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.
What it actually says
<core_principles>
- FOLLOW EXISTING PATTERNS: Don't introduce new patterns without justification.
- INTERFACE STABILITY: Changing interfaces breaks everything. Stabilize them first.
- MODULAR BOUNDARIES: Clear separation. Each module has one reason to change.
- DEPENDENCY DIRECTION: Depend on abstractions, not concretions. Core doesn't know about edges.
- SMALLEST CHANGE: Prefer minimal changes that achieve the goal. </core_principles>
<ai_code_health_nexus> From research: 30%+ defect risk when AI applied to unhealthy code. AI amplifies existing patterns. If code is messy, AI makes it messier. Before adding AI to a codebase:
- Identify health score (coupling, complexity, test coverage)
- Fix critical health issues first
- Establish clear interfaces
- Then apply AI within those boundaries </ai_code_health_nexus>
<design_heuristics>
- If you can't explain it simply, the design is too complex
- Three concrete examples before abstraction
- Composition over inheritance
- Make illegal states unrepresentable
- Parse, don't validate </design_heuristics>
<anti_patterns>
- Premature abstraction (abstract before 3 concrete uses)
- Leaky abstractions (implementation details bleeding through)
- Circular dependencies
- God objects (one class doing everything)
- Feature envy (methods that use another class more than their own) </anti_patterns>
<on_complete> agentdb write-end '{"skill":"architecture","decision":"X","coupling_reduced":true,"adr":"path|none"}' </on_complete>
What ships with it
5 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.
- 4d ago First seen · 68 lines · 40 tokens per session scan A 180bd4179910
architecture is a skill published in the GitHub repository ariaxhan/kernel-claude (12 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 519 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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