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/dotclaude/marketplace/orchestrategit clone --depth 1 https://github.com/dotclaude/marketplaceWhat 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 | $0.00009 | $0.02303 |
| Opus 5 | $0.00005 | $0.01151 |
| Sonnet 5 | $0.00002 | $0.00461 |
| Haiku 4.5 | $0.00001 | $0.00230 |
Grade A, and why
orchestrate 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 3d 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent Orchestration Engine
Assemble and coordinate specialized expert teams with dynamic collaboration patterns optimized for specific problem complexity and user sophistication levels. Create seamless multi-agent workflows that adapt to problem evolution and maximize collective intelligence.
Team Assembly Architecture
Complexity Scaling Framework
Simple (3-4 agents)
- Core domain specialist with primary expertise
- Practical implementer with hands-on experience
- Integration coordinator for synthesis and decision-making
- Single-phase analysis with straightforward coordination
Moderate (5-6 agents)
- Primary domain specialist with deep technical knowledge
- Secondary domain specialist covering adjacent areas
- Practical implementer with implementation reality-testing
- Constructive challenger with alternative perspective generation
- Integration lead with cross-domain synthesis capability
- Two-phase analysis with structured disagreement
Complex (7-9 agents)
- Multiple domain specialists with comprehensive coverage
- Technical implementation specialists with practical constraints
- Strategic analyst with long-term perspective evaluation
- Risk assessor with failure mode analysis capability
- Innovation catalyst with creative approach generation
- Constructive challenger with systematic assumption testing
- Integration coordinator with hierarchical synthesis management
- Multi-phase analysis with structured collaboration protocols
Enterprise (10+ agents)
- Comprehensive specialist coverage across all relevant domains
- Teams-of-teams structure with hierarchical coordination
- Meta-integration roles with cross-team synthesis capability
- Multiple challenging perspectives with diverse analytical approaches
- Specialized coordination roles for complex workflow management
Orchestration Pattern Framework
Sequential Pattern
[Extended thinking: Step-by-step expert consultation where each specialist builds on previous analysis. Optimal for problems requiring layered understanding or when expert insights create natural dependency chains.]
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.
- 3d ago First seen · 273 lines · 9 tokens per session scan A b0ff5369f336
orchestrate is a command published in the GitHub repository dotclaude/marketplace (42 stars, last pushed 4mo ago), licensed MIT. It adds 9 tokens to every session and 2,303 once invoked, about $0.0000 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.