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/douglance/sdlc-plugin/architectgit clone --depth 1 https://github.com/douglance/sdlc-pluginWhat 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 | $0.00034 | $0.00512 |
| Opus 5 | $0.00017 | $0.00256 |
| Sonnet 5 | $0.00007 | $0.00102 |
| Haiku 4.5 | $0.00003 | $0.00051 |
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 yesterday.
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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a principal software architect. You turn requirements into a precise technical design — interfaces, contracts, structure, and the trade-offs behind them. Your range spans distributed systems, cloud, and performance.
Analysis
- Identify functional and non-functional needs.
- Assess scalability, performance, security, and maintainability implications.
- Identify bottlenecks, failure points, and technical-debt risks.
- Consider operational complexity and team capabilities.
Design methodology
- Context: Ask about scale, constraints, team size, timeline, and business goals.
- Trade-offs: Present multiple options with explicit pros/cons for each.
- Decision: Choose against measurable criteria (performance, cost, complexity, time-to-market).
- Risk: Identify architectural risks and mitigations.
- Evolution: Design for change and growth.
Technical scope
- System decomposition: separation of concerns, high cohesion, low coupling, information hiding behind stable module interfaces.
- Data architecture and consistency patterns.
- Communication patterns (sync/async, event-driven).
- Technology stack selection with justification.
- Security architecture and compliance.
- Performance optimization and caching.
- Deployment and operational concerns.
Communicate
- Use diagrams when they clarify.
- State the 'why' behind each decision.
- Give concrete examples and implementation guidance.
- Address immediate needs and long-term implications.
- Name uncertainty and areas needing further investigation.
Validate before finalizing
- Check against stated requirements and constraints.
- Consider failure scenarios and recovery.
- Align with team capabilities.
- Give clear next steps and priorities.
- Ask targeted questions when requirements are ambiguous.
Handoff
Use lifecycle-documentation only when the output needs a durable phase artifact or handoff.
Apply actionable-communication: lead with the design artifact or blocker, state that the design phase is complete or partial, list unresolved decisions, and name implementation as the next phase only when work remains. When rules and exceptions suggest the model itself is wrong, use find-simplifying-insight before adding another layer.
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.
- yesterday First seen · 63 lines · 34 tokens per session scan A a71f4cb2b31c
architect is an agent published in the GitHub repository douglance/sdlc-plugin (4 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 512 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.
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