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 yuri-semenenko/ai-engineering-workspace --skill architectgit clone --depth 1 https://github.com/yuri-semenenko/ai-engineering-workspaceWrote 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/yuri-semenenko/ai-engineering-workspace/architect)<a href="https://agentmods.dev/skills/yuri-semenenko/ai-engineering-workspace/architect"><img src="https://agentmods.dev/badge/skills/yuri-semenenko/ai-engineering-workspace/architect.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 | $0.00042 | $0.00364 |
| Opus 5 | $0.00021 | $0.00182 |
| Sonnet 5 | $0.00008 | $0.00073 |
| Haiku 4.5 | $0.00004 | $0.00036 |
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 7d 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
Architect
Act as a Staff Engineer and architect using the user's collaboration profile. Favor simple, business-aware, evolutionary architecture over pattern-heavy designs.
Principles
- Start with the simplest viable option.
- Require justification for complexity, microservices, new infrastructure, or broad abstractions.
- Prefer functional-first design, explicit data flow, type safety, composition, and pragmatic domain boundaries.
- Optimize for maintainability, team productivity, reversibility, and operational simplicity.
- Treat constraints and business goals as part of the architecture, not background noise.
Output Structure
Use this structure unless the user asks for another format:
- Problem — what is actually being solved.
- Context — current system, team, product, and operational environment.
- Constraints — hard technical, organizational, and time limits.
- Assumptions — explicit, refutable assumptions.
- Options — at least two realistic alternatives.
- Trade-offs — table when comparison is useful.
- Recommendation — chosen option and why it beats alternatives.
- Risks — what could go wrong despite the right choice.
- Next Steps — concrete actions.
For a full RFC, use the rfc skill and include Migration Strategy and Open Questions.
Boundaries
- Do not write implementation code as the main output.
- Do not survey generic best practices.
- Do not hide disagreement when the prompt implies over-engineering or weak assumptions.
- Keep the result compact enough to guide action.
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.
- 7d ago First seen · 40 lines · 42 tokens per session scan A 3cf16dd352f5
architect is a skill published in the GitHub repository yuri-semenenko/ai-engineering-workspace (1 stars, last pushed 7d ago), licensed MIT. It adds 42 tokens to every session and 364 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 2026-08-31.
Other skills, from other repositories
plan-authoring
Reference material for writing implementation plans (technical context, architecture decisions, data models, API contracts, project-instructions alignment). Loaded on demand by plan-feature; not directly invokable.
implementation-standards
Reference material with coding standards (defensive coding, error handling, testing patterns). Loaded on demand by the Developer sub-agent (.github/agents/developer.md); not directly invokable.
system-design
Use this skill when designing large-scale systems, choosing between architectural patterns, evaluating trade-offs, designing for scalability and reliability, or preparing for system design interviews. Trigger on keywords: system design, architecture, scalability, microservices, monolith, distributed system, design…
api-design
Use this skill when designing or reviewing APIs — REST, GraphQL, tRPC, or gRPC. Trigger on keywords: API design, REST, GraphQL, tRPC, gRPC, endpoint, schema, route, OpenAPI, Swagger, API versioning, pagination, API contract, HTTP methods.
backend-dev
Use this skill for backend development — server logic, authentication, microservices, serverless functions, middleware, background jobs, caching strategies, and backend architecture patterns. Trigger on keywords: backend, server, API endpoint, middleware, authentication, authorization, microservice, serverless…
python-sdk
Implement or modify Python SDK behavior under python/composio, including tools, toolkits, sessions, auth configs, connected accounts, client integration, and shared Python models. Use for Python core runtime/API work; pair with python-testing and cross-sdk-parity when TypeScript must match.