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.
git clone --depth 1 https://github.com/jed1978/ddd-architecture-coachWrote 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/commands/jed1978/ddd-architecture-coach/phase-1)<a href="https://agentmods.dev/commands/jed1978/ddd-architecture-coach/phase-1"><img src="https://agentmods.dev/badge/commands/jed1978/ddd-architecture-coach/phase-1.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 | $0.00081 | $0.00441 |
| Opus 5 | $0.00041 | $0.00220 |
| Sonnet 5 | $0.00016 | $0.00088 |
| Haiku 4.5 | $0.00008 | $0.00044 |
Grade A, and why
phase-1 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
請啟動 DDD Architecture Coach（ddd-architecture-coach skill）並強制進入 Phase 1。
Argument handling:
$ARGUMENTS為空 → 進入 Phase 1 system-level（Steps 1–5）。若{coach_output_root}/system/domain-stories.md已存在 → 詢問使用者要 revise 既有 system 文件、還是改傳一個 BC 跑 Steps 6–7。$ARGUMENTS含 BC 名稱 → 進入該 BC 的 Phase 1 Steps 6–7（per-BC Domain Discovery）。Pre-flight：先 probe{coach_output_root}/system/確認 system-level Steps 1–5 已完成；若未完成 → 報錯「System-level Phase 1（Steps 1–5）必須先完成。請先執行不帶參數的/phase-1。」
執行步驟：
- 讀取
.claude/project-context.md（必要）與.claude/arch-state.md（讀取作為 fallback hint，非權威） - 讀取
references/phase1-domain-discovery.md，依「Mode Selection」決定 system-full / system-incremental / per-bc - 跳過 Phase Selection Logic 的自動判斷，直接執行 Phase 1
- 進入 phase 時更新
.claude/arch-state.md的last_touched: { bc, phase, at: <today> }（個人 cursor，不寫團隊狀態）
$ARGUMENTS
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 · 18 lines · 81 tokens per session scan A c9b33d6494d0
phase-1 is a command published in the GitHub repository jed1978/ddd-architecture-coach (5 stars, last pushed 4mo ago), licensed MIT. It adds 81 tokens to every session and 441 once invoked, about $0.0004 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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audit
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a
Intercept Mode - Auto-improve and execute immediately.