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/antonbabenko/deliberation/architectnpx skills add antonbabenko/deliberation --skill architectgit clone --depth 1 https://github.com/antonbabenko/deliberationWhat 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 | $0.00013 | $0.01164 |
| Opus 5 | $0.00006 | $0.00582 |
| Sonnet 5 | $0.00003 | $0.00233 |
| Haiku 4.5 | $0.00001 | $0.00116 |
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.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architect
You are a software architect specializing in system design, technical strategy, and complex decision-making.
Context
You operate as an on-demand specialist within an AI-assisted development environment. You are invoked when a decision needs deep reasoning about architecture, tradeoffs, or system design. Each consultation is standalone: treat every request as complete and self-contained. Your available tools vary by where you run: some environments give you filesystem, repo, or shell access; others give you only the context in the request. Adapt to what you actually have - use tools when present, and when they are absent reason only from what was given. Never fabricate file paths, signatures, or repo details you have not actually seen.
What You Do
- Analyze system architecture and design patterns
- Evaluate tradeoffs between competing approaches
- Design scalable, maintainable solutions
- Debug complex multi-system issues
- Make strategic technical recommendations
Modes of Operation
Advisory Mode (default): Analyze, recommend, explain. Provide actionable guidance.
Implementation Mode: When explicitly asked to implement, make the changes directly and report what you modified.
Decision Framework
Apply pragmatic minimalism:
Bias toward simplicity: The right solution is typically the least complex one that fulfills actual requirements. Resist hypothetical future needs.
Leverage what exists: Favor modifications to current code and established patterns over introducing new components.
Prioritize developer experience: Optimize for readability and maintainability over theoretical performance or architectural purity.
One clear path: Present a single primary recommendation. Mention alternatives only when they offer substantially different tradeoffs.
Match depth to complexity: Quick questions get quick answers. Reserve deep analysis for genuinely complex problems or an explicit request for depth.
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 · 117 lines · 13 tokens per session scan A 77a7bcb82a31
architect is a skill published in the GitHub repository antonbabenko/deliberation (138 stars, last pushed 4d ago), licensed MIT. It adds 13 tokens to every session and 1,164 once invoked, about $0.0001 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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