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/speckit.tasksgit 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.tasks)<a href="https://agentmods.dev/commands/akiojin/unity-mcp-server/speckit.tasks"><img src="https://agentmods.dev/badge/commands/akiojin/unity-mcp-server/speckit.tasks.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 | $0.00033 | $0.00662 |
| Opus 5 | $0.00016 | $0.00331 |
| Sonnet 5 | $0.00007 | $0.00132 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
speckit.tasks 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 4d 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。
概要
/speckit.tasks は、plan.md と spec.md（必須）を中心に、利用可能な資料からタスクを生成します。タスクはユーザーストーリー単位で整理し、各ストーリーが独立して実装・検証できるようにします。
実行手順
-
リポジトリルートから
.specify/scripts/bash/check-prerequisites.sh --jsonを実行し、JSON出力から以下を取得します（パスはすべて絶対パス）:FEATURE_DIRAVAILABLE_DOCS
-
FEATURE_DIRから設計ドキュメントを読み込みます:- 必須: plan.md（技術スタック、構造）, spec.md（ユーザーストーリーと優先度）
- 任意: data-model.md（エンティティ）, contracts/（API）, research.md（決定事項）, quickstart.md（検証シナリオ）
- ないドキュメントがあっても、存在する情報からタスクを生成します。
-
タスク生成を行います:
- spec.md からユーザーストーリー（P1, P2, P3...）と独立テスト条件を抽出
- plan.md から構造・技術選択・制約を抽出
- data-model.md があれば、エンティティをストーリーへマッピング
- contracts/ があれば、エンドポイントをストーリーへマッピング
- research.md があれば、セットアップ/方針タスクへ反映
-
FEATURE_DIR/tasks.mdを生成します（ファイル書き込みあり）:.specify/templates/tasks-template.mdの構造に従う- Phase 1: Setup、Phase 2: Foundational、Phase 3+: 各ユーザーストーリー（優先度順）
- 各タスクはチェックボックス＋ID（T001..）＋必要に応じて
[P]＋[USx]＋ファイルパスを含める - 依存関係と並列化の説明も含める
-
最後に、ユーザーへ以下を返します:
- 生成した
tasks.mdのパス - 総タスク数とストーリー別内訳
- 並列化可能なポイント
- 次ステップ（
/speckit.implement）への案内
- 生成した
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.
- 4d ago First seen · 46 lines · 33 tokens per session scan A 0a443c59f796
speckit.tasks is a command published in the GitHub repository akiojin/unity-mcp-server (34 stars, last pushed 4d ago), licensed MIT. It adds 33 tokens to every session and 662 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
git
Git operations with intelligent commit messages and workflow optimization.
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.
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.