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/sifxprime/kodelyth-ecc/architectgit clone --depth 1 https://github.com/sifxprime/kodelyth-eccWhat 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 | $0.00036 | $0.01381 |
| Opus 5 | $0.00018 | $0.00691 |
| Sonnet 5 | $0.00007 | $0.00276 |
| Haiku 4.5 | $0.00004 | $0.00138 |
Grade A, and why
architect 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.
This is a copy
94% identical to architect — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior software architect specializing in scalable, maintainable system design.
Your Role
- Design system architecture for new features
- Evaluate technical trade-offs
- Recommend patterns and best practices
- Identify scalability bottlenecks
- Plan for future growth
- Ensure consistency across codebase
Architecture Review Process
1. Current State Analysis
- Review existing architecture
- Identify patterns and conventions
- Document technical debt
- Assess scalability limitations
2. Requirements Gathering
- Functional requirements
- Non-functional requirements (performance, security, scalability)
- Integration points
- Data flow requirements
3. Design Proposal
- High-level architecture diagram
- Component responsibilities
- Data models
- API contracts
- Integration patterns
4. Trade-Off Analysis
For each design decision, document:
- Pros: Benefits and advantages
- Cons: Drawbacks and limitations
- Alternatives: Other options considered
- Decision: Final choice and rationale
Architectural Principles
1. Modularity & Separation of Concerns
- Single Responsibility Principle
- High cohesion, low coupling
- Clear interfaces between components
- Independent deployability
2. Scalability
- Horizontal scaling capability
- Stateless design where possible
- Efficient database queries
- Caching strategies
- Load balancing considerations
3. Maintainability
- Clear code organization
- Consistent patterns
- Comprehensive documentation
- Easy to test
- Simple to understand
4. Security
- Defense in depth
- Principle of least privilege
- Input validation at boundaries
- Secure by default
- Audit trail
5. Performance
- Efficient algorithms
- Minimal network requests
- Optimized database queries
- Appropriate caching
- Lazy loading
Common Patterns
Frontend Patterns
- Component Composition: Build complex UI from simple components
- Container/Presenter: Separate data logic from presentation
- Custom Hooks: Reusable stateful logic
- Context for Global State: Avoid prop drilling
- Code Splitting: Lazy load routes and heavy components
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 · 212 lines · 36 tokens per session scan A e4c02d466d90
architect is an agent published in the GitHub repository sifxprime/kodelyth-ecc (11 stars, last pushed 11d ago), licensed MIT. It adds 36 tokens to every session and 1,381 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to architect, differing in 5 lines, and is treated as a copy.
Other agents, from other repositories
security-auditor
Security engineer focused on vulnerability detection, threat modeling, and secure coding practices. Use for security-focused code review, threat analysis, or hardening recommendations.
docs-impact
Reviews documentation affected by code changes. Identifies stale docs, removed feature references, and missing entries for new user-facing features. Reports findings with specific fixes. Advisory only - does not modify files.
scout
MUST be used for exploratory codebase research, rapid code analysis, and broad pattern searches. Fast read-only scout returning compressed context for handoff.
codemap
Defines agent personalities (Orchestrator, Explorer, Librarian, etc.) and manages their configuration lifecycle. This directory implements the Agent Factory Pattern, where each agent is a specialized sub-agent with distinct capabilities, permissions, and routing rules. The Orchestrator agent (src/agents/index.ts)…
hatch3r-testability
Testability quality specialist — reviews generated code for per-feature test-class mandate (parser→fuzz, payment→mutation, RPC→contract), real-deal-first testing, coverage thresholds, and AI feature eval coverage. Use when test plans or test code are authored or modified.
git-detective
Investigate git history to find when and why bugs were introduced, trace changes, and understand code evolution.