orchestrator

orchestrator is a command for Claude Code from mizchi/lsmcp. It costs 0 tokens per session (748 once invoked), scanned A, original, MIT.

A task-planning workflow that breaks a complex request into ordered steps, with independent subtasks handled in parallel within each step. It reviews results after each step and can adjust the remaining plan.

In plain words
What is it for?
Use it to plan and execute multi-part work such as analysis, testing, or implementation tasks that need several dependent stages.
Why use it?
It helps manage work with dependencies, so later tasks receive the relevant results from earlier ones. It also keeps large tasks from being handled as one unstructured operation.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/mizchi/lsmcp/orchestrator
Clone the repo
git clone --depth 1 https://github.com/mizchi/lsmcp

Made for: Claude Code.

Wrote 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.

agentmods badge for orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/commands/mizchi/lsmcp/orchestrator.svg)](https://agentmods.dev/commands/mizchi/lsmcp/orchestrator)
Your own site
<a href="https://agentmods.dev/commands/mizchi/lsmcp/orchestrator"><img src="https://agentmods.dev/badge/commands/mizchi/lsmcp/orchestrator.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 748 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00748
Opus 5 $0.00000 $0.00374
Sonnet 5 $0.00000 $0.00150
Haiku 4.5 $0.00000 $0.00075

Measured 5d ago against content hash 4388121666b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

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 5d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.claude/commands/orchestrator.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Orchestrator

Split complex tasks into sequential steps, where each step can contain multiple parallel subtasks.

Process

  1. Initial Analysis

    • First, analyze the entire task to understand scope and requirements
    • Identify dependencies and execution order
    • Plan sequential steps based on dependencies
  2. Step Planning

    • Break down into 2-4 sequential steps
    • Each step can contain multiple parallel subtasks
    • Define what context from previous steps is needed
  3. Step-by-Step Execution

    • Execute all subtasks within a step in parallel
    • Wait for all subtasks in current step to complete
    • Pass relevant results to next step
    • Request concise summaries (100-200 words) from each subtask
  4. Step Review and Adaptation

    • After each step completion, review results
    • Validate if remaining steps are still appropriate
    • Adjust next steps based on discoveries
    • Add, remove, or modify subtasks as needed
  5. Progressive Aggregation

    • Synthesize results from completed step
    • Use synthesized results as context for next step
    • Build comprehensive understanding progressively
    • Maintain flexibility to adapt plan

Example Usage

When given "analyze test lint and commit":

Step 1: Initial Analysis (1 subtask)

  • Analyze project structure to understand test/lint setup

Step 2: Quality Checks (parallel subtasks)

  • Run tests and capture results
  • Run linting and type checking
  • Check git status and changes

Step 3: Fix Issues (parallel subtasks, using Step 2 results)

  • Fix linting errors found in Step 2
  • Fix type errors found in Step 2
  • Prepare commit message based on changes Review: If no errors found in Step 2, skip fixes and proceed to commit

Step 4: Final Validation (parallel subtasks)

  • Re-run tests to ensure fixes work
  • Re-run lint to verify all issues resolved
  • Create commit with verified changes Review: If Step 3 had no fixes, simplify to just creating commit

Key Benefits

  • Sequential Logic: Steps execute in order, allowing later steps to use earlier results
  • Parallel Efficiency: Within each step, independent tasks run simultaneously
  • Memory Optimization: Each subtask gets minimal context, preventing overflow
  • Progressive Understanding: Build knowledge incrementally across steps
  • Clear Dependencies: Explicit flow from analysis → execution → validation

Read the full file on GitHub · 90 lines

Changes

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.

  1. 5d ago First seen · 90 lines · 0 tokens per session scan A 4388121666b6

Subscribe to this mod's changes

orchestrator is a command published in the GitHub repository mizchi/lsmcp (453 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 748 tokens. 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.