Borrowing it
Nothing to install: this file belongs to akiojin/unity-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/akiojin/unity-mcp-server/main/.claude/commands/speckit.clarify.mdgit clone --depth 1 https://github.com/akiojin/unity-mcp-serverWrote 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/akiojin/unity-mcp-server/speckit.clarify)<a href="https://agentmods.dev/commands/akiojin/unity-mcp-server/speckit.clarify"><img src="https://agentmods.dev/badge/commands/akiojin/unity-mcp-server/speckit.clarify/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/akiojin/unity-mcp-server/speckit.clarify"><img src="https://agentmods.dev/badge/commands/akiojin/unity-mcp-server/speckit.clarify.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00033 | $0.00603 |
| Opus 5.5 | $0.00013 | $0.00241 |
| Sonnet 5.5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00060 |
Grade A, and why
speckit.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 2mo 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
/speckit.plan の前に、仕様の曖昧さ/未決定事項を減らし、後工程の手戻りリスクを下げます。
実行手順
-
リポジトリルートから
.specify/scripts/bash/check-prerequisites.sh --json --paths-onlyを1回だけ実行し、FEATURE_SPEC（spec.mdの絶対パス）とFEATURE_DIRを取得します。 -
spec.md を読み込み、曖昧点をスキャンします（例）:
- スコープ/境界（含む/含まない）
- 役割/権限（誰が何できるか）
- 例外/エラー時の挙動
- 成功基準の測定可能性
- セキュリティ/プライバシー（重要な前提）
- データの一意性/ライフサイクル（データがある場合）
-
質問を最大5問に絞って、1問ずつ提示します:
- それぞれが「実装/テスト/UX/運用」に実質的影響を持つものだけ
- 可能なら2〜5択、または「5語以内」で答えられる形式にする
- 先に次の質問を並べて提示しない
-
回答を受け取ったら、spec.md に反映します（ファイル書き込みあり）:
## Clarificationsセクションがなければ追加### Session YYYY-MM-DDに、- Q: ... → A: ...を追記- 影響するセクション（要件/ストーリー/成功基準/エッジケースなど）へ具体的に反映
- 矛盾する古い記述が残らないよう置換する
-
最後にユーザーへ以下を報告します:
- 質問数（≤5）
- 更新した spec.md のパス
- 触ったセクション
- まだ残る重要な不明点（あれば）
- 次ステップ（
/speckit.plan）の推奨
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.
- 2mo ago First seen · 46 lines · 33 tokens per session scan A e3b05db60ded
speckit.clarify is a command published in the GitHub repository akiojin/unity-mcp-server (35 stars, last pushed 3d ago), licensed MIT. It adds 33 tokens to every session and 603 once invoked, about $0.0001 per session on Opus 5.5. 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.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.