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 commands/akiojin/unity-mcp-server/clarifygit clone --depth 1 https://github.com/akiojin/unity-mcp-serverWhat 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 | $0.00033 | $0.00897 |
| Opus 5 | $0.00016 | $0.00449 |
| Sonnet 5 | $0.00007 | $0.00179 |
| Haiku 4.5 | $0.00003 | $0.00090 |
Grade A, and why
clarify 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.
What it actually says
ユーザー入力
$ARGUMENTS
空でない場合、続行する前にユーザー入力を考慮する必要があります。
目的
仕様の曖昧点や未決定事項を解消し、計画フェーズへの準備を整える。
実行手順
1. コンテキスト初期化
{SCRIPT} を1回だけ実行し、FEATURE_SPEC（spec.mdの絶対パス）と FEATURE_DIR を取得。
2. 仕様分析
spec.md を読み込み、以下を抽出:
曖昧さ検出対象:
[要明確化]マーカー- 曖昧な形容詞（高速、スケーラブル、セキュア、直感的）
- 未解決のプレースホルダー
- 測定可能な基準のない要件
- 矛盾する要件
- 未定義の用語
優先度付け基準:
- スコープに影響する項目
- セキュリティ/プライバシーに影響する項目
- ユーザー体験に影響する項目
- 技術的詳細
3. 質問生成と提示
最大5問に絞り、以下の形式で提示:
## 質問 [N]: [トピック]
**コンテキスト**: [仕様からの引用]
**明確化が必要**: [具体的な質問]
**選択肢**:
| オプション | 回答 | 影響 |
|-----------|------|------|
| A | [1つ目の回答] | [機能への影響] |
| B | [2つ目の回答] | [機能への影響] |
| C | [3つ目の回答] | [機能への影響] |
| カスタム | 独自の回答 | [カスタム入力の説明] |
**選択**: _[ユーザーの回答を待機]_
4. 回答反映
回答を得たら spec.md に反映:
-
明確化セクション追加/更新:
## 明確化 ### セッション YYYY-MM-DD **Q1**: [質問] **A1**: [回答] -
関連セクション更新:
- 要件セクション
- ユーザーストーリー
- 成功基準
- エッジケース
- 前提条件
-
[要明確化]マーカー削除: 回答を反映した箇所のマーカーを削除
5. 完了報告
- 質問数（≤5）
- 更新した spec.md のパス
- 残っている曖昧点（あれば）
- 次ステップ
/speckit.plan
ガイドライン
- 1回のセッションで最大5問まで
- 各質問は具体的で、選択肢を提示
- 回答はspec.mdに直接反映
- 新しい曖昧点が見つかった場合は再度
/speckit.clarifyを推奨
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 · 107 lines · 33 tokens per session scan A 71171fadb2de
clarify is a command published in the GitHub repository akiojin/unity-mcp-server (34 stars, last pushed 9d ago), licensed MIT. It adds 33 tokens to every session and 897 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.