Borrowing it
Nothing to install: this file belongs to akiojin/playfab-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/playfab-mcp-server/main/.claude/commands/speckit.specify.mdgit clone --depth 1 https://github.com/akiojin/playfab-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/playfab-mcp-server/speckit.specify)<a href="https://agentmods.dev/commands/akiojin/playfab-mcp-server/speckit.specify"><img src="https://agentmods.dev/badge/commands/akiojin/playfab-mcp-server/speckit.specify.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 | $0.00019 | $0.02513 |
| Opus 5 | $0.00010 | $0.01256 |
| Sonnet 5 | $0.00004 | $0.00503 |
| Haiku 4.5 | $0.00002 | $0.00251 |
Grade A, and why
speckit.specify 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 8d 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.
This is a copy
69% identical to specify — 213 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ユーザー入力
$ARGUMENTS
(空でない場合)続行する前に、ユーザー入力を必ず考慮してください。
概要
/speckit.specify の後にユーザーが入力したテキストが機能の説明です。以下に文字通り $ARGUMENTS と表示されていても、この会話で常に利用可能であると想定してください。空のコマンドを提供した場合を除き、ユーザーに繰り返し尋ねないでください。
機能の説明が与えられた場合、以下を実行します:
-
SPEC IDを生成(ブランチは作成しない):
a. まず、すべてのリモートブランチをフェッチして最新情報を取得します:
git fetch --all --pruneb. スクリプトを実行して新しいSPEC IDを生成します(--no-branch オプションを必ず指定):
.specify/scripts/bash/create-new-feature.sh --json --no-branch "$ARGUMENTS"- 例:
.specify/scripts/bash/create-new-feature.sh --json --no-branch "ユーザー認証を追加"
重要:
- --no-branch オプション: ブランチを作成せず、現在のブランチで作業を続けます(worktree設計思想に準拠)
- このスクリプトは機能ごとに1回だけ実行する必要があります
- JSONは端末に出力として提供されます - 探しているコンテンツを取得するために常にそれを参照してください
- JSON出力にはBRANCH_NAME、SPEC_FILE、SPEC_IDが含まれます
- スクリプトは自動的に一意のSPEC ID(SPEC-xxxxxxxx形式)を生成します
- シングルクォートを含む引数("I'm Groot"など)の場合は、エスケープ構文を使用: 例 'I'''m Groot'(または可能であればダブルクォート: "I'm Groot")
- 例:
-
Load
.specify/templates/spec-template.mdto understand required sections. -
Follow this execution flow:
- Parse user description from Input If empty: ERROR "No feature description provided"
- Extract key concepts from description Identify: actors, actions, data, constraints
- For unclear aspects:
- Make informed guesses based on context and industry standards
- Only mark with [NEEDS CLARIFICATION: specific question] if:
- The choice significantly impacts feature scope or user experience
- Multiple reasonable interpretations exist with different implications
- No reasonable default exists
- LIMIT: Maximum 3 [NEEDS CLARIFICATION] markers total
- Prioritize clarifications by impact: scope > security/privacy > user experience > technical details
- Fill User Scenarios & Testing section If no clear user flow: ERROR "Cannot determine user scenarios"
- Generate Functional Requirements Each requirement must be testable Use reasonable defaults for unspecified details (document assumptions in Assumptions section)
- Define Success Criteria Create measurable, technology-agnostic outcomes Include both quantitative metrics (time, performance, volume) and qualitative measures (user satisfaction, task completion) Each criterion must be verifiable without implementation details
- Identify Key Entities (if data involved)
- Return: SUCCESS (spec ready for planning)
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.
- 8d ago First seen · 227 lines · 19 tokens per session scan A 52862b03ad8e
speckit.specify is a command published in the GitHub repository akiojin/playfab-mcp-server (3 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 2,513 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 69% identical to specify, differing in 213 lines, and is treated as a copy.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.