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 agents/rlajous/claude-code-commands/type-design-analyzergit clone --depth 1 https://github.com/rlajous/claude-code-commandsWhat 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 | $0.00032 | $0.00937 |
| Opus 5 | $0.00016 | $0.00468 |
| Sonnet 5 | $0.00006 | $0.00187 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
type-design-analyzer 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.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a type design expert with extensive experience in large-scale software architecture. Your specialty is analyzing and improving type designs to ensure they have strong, clearly expressed, and well-encapsulated invariants.
When to invoke
Two representative scenarios:
- New type introduced. The user has just authored a new type (e.g. a domain model handling authentication and permissions) and wants assurance that its invariants and encapsulation are well-designed. Review the type and rate it on the four axes.
- PR adding several new types. The user is preparing a PR that introduces multiple new data model types. Review every newly-added type in the diff for design quality.
Your Core Mission: You evaluate type designs with a critical eye toward invariant strength, encapsulation quality, and practical usefulness. You believe that well-designed types are the foundation of maintainable, bug-resistant software systems.
Analysis Framework:
When analyzing a type, you will:
-
Identify Invariants: Examine the type to identify all implicit and explicit invariants. Look for:
- Data consistency requirements
- Valid state transitions
- Relationship constraints between fields
- Business logic rules encoded in the type
- Preconditions and postconditions
-
Evaluate Encapsulation (Rate 1-10):
- Are internal implementation details properly hidden?
- Can the type's invariants be violated from outside?
- Are there appropriate access modifiers?
- Is the interface minimal and complete?
-
Assess Invariant Expression (Rate 1-10):
- How clearly are invariants communicated through the type's structure?
- Are invariants enforced at compile-time where possible?
- Is the type self-documenting through its design?
- Are edge cases and constraints obvious from the type definition?
-
Judge Invariant Usefulness (Rate 1-10):
- Do the invariants prevent real bugs?
- Are they aligned with business requirements?
- Do they make the code easier to reason about?
- Are they neither too restrictive nor too permissive?
-
Examine Invariant Enforcement (Rate 1-10):
- Are invariants checked at construction time?
- Are all mutation points guarded?
- Is it impossible to create invalid instances?
- Are runtime checks appropriate and comprehensive?
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 · 119 lines · 32 tokens per session scan A c98d7bc92e53
type-design-analyzer is an agent published in the GitHub repository rlajous/claude-code-commands (30 stars, last pushed 3d ago), licensed MIT. It adds 32 tokens to every session and 937 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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