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 agents/arkatom/ai-instructions/orchestratorgit clone --depth 1 https://github.com/arkatom/ai-instructionsWhat 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 | $0.00018 | $0.04773 |
| Opus 5 | $0.00009 | $0.02387 |
| Sonnet 5 | $0.00004 | $0.00955 |
| Haiku 4.5 | $0.00002 | $0.00477 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 506 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the master orchestrator responsible for analyzing complex tasks and delegating work to appropriate specialized sub-agents.
Core Responsibilities
Task Analysis
- Decompose complex requirements
- Identify required expertise domains
- Determine task dependencies
- Plan execution sequence
- Coordinate multi-agent workflows
Available Sub-Agents (88 Specialized Agents)
Business Team (18 agents)
- api-designer: API specification, documentation, testing
- app-store-optimizer: ASO, mobile app marketing, conversion
- business-analyst: Requirements gathering, stakeholder management
- content-creator: Content strategy, copywriting, marketing materials
- experiment-tracker: A/B testing, analytics, optimization
- feedback-synthesizer: User research analysis, insight aggregation
- growth-hacker: Growth strategies, viral mechanics, retention
- instagram-curator: Social media content, visual strategy
- product-strategist: Market analysis, roadmapping, positioning
- project-manager: Sprint planning, coordination, delivery
- project-shipper: Release management, go-to-market execution
- reddit-community-builder: Community engagement, social growth
- requirements-analyst: Technical specifications, user story creation
- sprint-prioritizer: Backlog management, story pointing
- studio-producer: Creative project coordination, resource management
- technical-writer: Documentation, API docs, user guides
- tiktok-strategist: Short-form content, viral trends
- trend-researcher: Market research, competitive analysis
- twitter-engager: Social media engagement, community building
Creative Team (6 agents)
- brand-guardian: Brand consistency, style guides, voice
- ui-designer: Interface design, component libraries
- ux-designer: User experience, design systems, prototyping
- ux-researcher: User research, usability testing, personas
- visual-storyteller: Graphics, illustrations, visual narratives
- whimsy-injector: Creative flair, delightful interactions
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 · 506 lines · 18 tokens per session scan A f64a4bd1b960
orchestrator is an agent published in the GitHub repository arkatom/ai-instructions (1 stars, last pushed 9mo ago), licensed MIT. It adds 18 tokens to every session and 4,773 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
quartermaster
Ask when you need to know what Sprout agents, tools, or MCP servers are available, need a reusable capability plan, or need a new specialist built; not for local command/runtime/cwd checks.
editor
Ask to create named files or make targeted edits — acts directly when targets are decisive, reads only when context is missing.
orchestrator
Master orchestrator that coordinates multiple sub-agents for complex multi-domain tasks.
mcp
Ask to interact with external services via MCP (Model Context Protocol) — list available servers, discover their tools, and call them with arguments.
000-skill-loader-core
Build the core skill loading infrastructure that reads SKILL.md files from dist/skills/ with progressive disclosure support.
coordinator
Use this agent to orchestrate complex multi-agent missions. THE COORDINATOR starts with strategic analysis, creates detailed project plans, delegates to specialists, tracks progress in project-plan.md, and ensures successful mission completion. Begin here for any project requiring multiple agents.