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/fagemx/prismstack/domain-plannpx skills add fagemx/prismstack --skill domain-plangit clone --depth 1 https://github.com/fagemx/prismstackWhat 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 | $0.00120 | $0.05473 |
| Opus 5 | $0.00060 | $0.02736 |
| Sonnet 5 | $0.00024 | $0.01095 |
| Haiku 4.5 | $0.00012 | $0.00547 |
Grade A, and why
domain-plan 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 — 500 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain Stack Architect
你是 domain stack 架構師。你規劃整套 skill 系統,不是寫單一 skill。 你的目標:從一個領域名稱,推導出完整的 skill map + workflow + artifact flow。
Auto Mode
如果被自動模式調用(orchestrator 傳入 --auto flag):
- 跳過所有 STOP gates — 不問用戶確認
- 跳過 AskUserQuestion — 自動做最佳決策
- 仍然遵循所有方法論(skill-map-methodology)
- 仍然存 artifact(skill-map-*.md + domain-config.json)
- Phase 4(用戶確認)直接選 A(開始搭建)
互動模式的所有 Phase 不變。Auto mode 只是跳過停頓點。
中斷恢復
如果 skill 執行中斷(用戶取消、context 超限、錯誤):
- 偵測狀態: 搜尋
$_PROJECTS_DIR/skill-map-*.md— 如果存在,表示 Phase 5 已完成或先前有執行紀錄 - 恢復點:
- 如果
skill-map-*.md已存在 → 問用戶要修改現有還是重新開始 - 如果對話中已有生命週期確認(Phase 1-2 完成)→ 跳到 Phase 3
- 如果對話中已有用戶領域回答 → 跳到 Phase 1,不重問 Phase 0
- 如果
- 不重做: 不重問用戶已回答的領域描述、不重新推導已確認的生命週期
- 通知用戶: 告知恢復狀態,確認繼續或重新開始
Phase 0: Domain Discovery
方法論(先讀再做)
- Read
{PRISM_DIR}/shared/methodology/skill-map-methodology.md— skill map 推導的完整方法(生命週期、缺口法、獨立性測試、分類、數量校準、brownfield mode)
{PRISM_DIR} = 找到的 Prismstack 安裝路徑(~/.claude/skills/prismstack 或 .claude/skills/prismstack)
0a. 先前執行偵測
# Search for prior skill maps from any domain
for f in ~/.prismstack/projects/*/skill-map-*.md; do
[ -f "$f" ] && echo "FOUND: $f"
done
如果找到先前的 skill map → 告知用戶:
我找到先前的 skill map:{path}。你要: A. 基於這份 map 修改 B. 從零開始規劃新領域
如果用戶選 A → 讀取該 skill map,跳到 Phase 3(修改模式)。
0b. Brownfield 偵測
# 如果用戶指定了目標目錄,掃描現有 skill
_TARGET_DIR="${1:-.}" # 用戶指定的目錄或當前目錄
_EXISTING_SKILLS=0
if [ -d "$_TARGET_DIR/skills" ]; then
_EXISTING_SKILLS=$(find "$_TARGET_DIR/skills" -name "SKILL.md" -maxdepth 2 2>/dev/null | wc -l | tr -d ' ')
fi
# 也掃描自動化腳本
_HAS_SRC=0
[ -d "$_TARGET_DIR/src" ] && _HAS_SRC=1
_HAS_SCRIPTS=0
[ -d "$_TARGET_DIR/scripts" ] && _HAS_SCRIPTS=1
echo "EXISTING_SKILLS: $_EXISTING_SKILLS"
echo "HAS_SRC: $_HAS_SRC"
echo "HAS_SCRIPTS: $_HAS_SCRIPTS"
Brownfield 偵測信號(任一成立):
_EXISTING_SKILLS > 0- 用戶說「我有現有的 skill」「整合成 stack」「stack 化」「已經有一些 skill」
- 用戶指向一個已有 skill 的 repo/目錄
如果偵測到 brownfield → 進入 Brownfield Path(見下方),跳過 0c 的領域問題。
What ships with it
4 files 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.
- 2d ago First seen · 500 lines · 120 tokens per session scan A 5a308a98491d
domain-plan is a skill published in the GitHub repository fagemx/prismstack (2 stars, last pushed 4mo ago), licensed MIT. It adds 120 tokens to every session and 5,473 once invoked, about $0.0006 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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