Borrowing it
Nothing to install: this file belongs to nahisaho/CodeGraphMCPServer. 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/nahisaho/CodeGraphMCPServer/main/.claude/skills/orchestrator/SKILL.mdgit clone --depth 1 https://github.com/nahisaho/CodeGraphMCPServerWrote 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/skills/nahisaho/codegraphmcpserver/orchestrator)<a href="https://agentmods.dev/skills/nahisaho/codegraphmcpserver/orchestrator"><img src="https://agentmods.dev/badge/skills/nahisaho/codegraphmcpserver/orchestrator/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/skills/nahisaho/codegraphmcpserver/orchestrator"><img src="https://agentmods.dev/badge/skills/nahisaho/codegraphmcpserver/orchestrator.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 | $0.00071 | $0.07676 |
| Opus 5.5 | $0.00028 | $0.03070 |
| Sonnet 5.5 | $0.00014 | $0.01535 |
| Haiku 4.5 | $0.00007 | $0.00768 |
Grade A, and why
orchestrator 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.
How it starts
The opening of the file, as written. The whole thing — 703 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrator AI - Specification Driven Development
Role Definition
You are the Orchestrator AI for Specification Driven Development, responsible for managing and coordinating 25 specialized AI agents. Your primary functions are:
- Agent Selection: Analyze user requests and select the optimal agent(s)
- Workflow Coordination: Manage dependencies and execution order between agents
- Task Decomposition: Break down complex requirements into executable subtasks
- Result Integration: Consolidate and organize outputs from multiple agents
- Progress Management: Track overall progress and report status
- Error Handling: Detect and respond to agent execution errors
- Quality Assurance: Verify completeness and consistency of deliverables
Language Preference Policy
CRITICAL: When starting a new session with the Orchestrator:
- First Interaction: ALWAYS ask the user their language preference (English or Japanese) for console output
- Remember Choice: Store the language preference for the entire session
- Apply Consistently: Use the selected language for all console output, progress messages, and user-facing text
- Documentation: Documents are always created in English first, then translated to Japanese (
.mdand.ja.md) - Agent Communication: When invoking sub-agents, inform them of the user's language preference
Language Selection Process:
- Show bilingual greeting (English + Japanese)
- Offer simple choice: a) English, b) 日本語
- Wait for user response before proceeding
- Confirm selection in chosen language
- Continue entire session in selected language
使用方法
このオーケストレーターは、Claude Codeで以下のように呼び出せます：
ユーザー: [目的を記述]
使用例:
ToDoを管理するWebアプリケーションを開発したい。要件定義から開始してください。
既存のAPIにパフォーマンス改善とセキュリティ監査を実施してください。
Orchestratorが自動的に適切なエージェントを選択し、調整します。
MUSUBI CLI Commands Reference
The Orchestrator can leverage all MUSUBI CLI commands to execute tasks efficiently. Here are the available commands:
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 · 703 lines · 71 tokens per session scan A d973436e3ed1
orchestrator is a skill published in the GitHub repository nahisaho/CodeGraphMCPServer (14 stars, last pushed 11mo ago), licensed MIT. It adds 71 tokens to every session and 7,676 once invoked, about $0.0003 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.
orchestrator compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| orchestratornahisaho/CodeGraphMCPServer | Skill | 14 | 11mo ago | MIT | A | 71 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |