orchestrate

orchestrate is a skill for Claude Code from andrehuang/researcher-pack. It costs 119 tokens per session (4,380 once invoked), scanned A, original, MIT.

A coordinator for using multiple specialist AI agents on complex research, analysis, planning, debugging, or refactoring tasks. It assigns work, collects results, and combines them into a response.

In plain words
What is it for?
It helps plan investigations, run parallel reviews, brainstorm, debug, refactor, and synthesize findings from several agents.
Why use it?
It organizes multi-step work and brings together different expert viewpoints instead of relying on one line of analysis.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: reads .claude/ paths; mentions CLAUDE.md; built for openclaw.

Good fit It helps plan investigations, run parallel reviews, brainstorm, debug, refactor, and synthesize findings from several agents.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/andrehuang/researcher-pack/orchestrate
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.

Any agent
npx skills add andrehuang/researcher-pack --skill orchestrate
Clone the repo
git clone --depth 1 https://github.com/andrehuang/researcher-pack

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 orchestrate

README.md
[![agentmods](https://agentmods.dev/badge/skills/andrehuang/researcher-pack/orchestrate.svg)](https://agentmods.dev/skills/andrehuang/researcher-pack/orchestrate)
Your own site
<a href="https://agentmods.dev/skills/andrehuang/researcher-pack/orchestrate"><img src="https://agentmods.dev/badge/skills/andrehuang/researcher-pack/orchestrate.svg" alt="Measured on agentmods" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,380 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00119 $0.04380
Opus 5 $0.00060 $0.02190
Sonnet 5 $0.00024 $0.00876
Haiku 4.5 $0.00012 $0.00438

Measured 7d ago against content hash 2b1de1505d59, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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 7d 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.

skills/orchestrate/SKILL.md · 354 lines

How it starts

The opening of the file, as written. The whole thing — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-Agent Orchestrator

You are the Orchestrator — a senior advisor coordinating a team of specialist agents. Your job is to understand the user's request, deploy the right combination of workers, collect their outputs, synthesize findings, and drive iterative improvement through dialogue with the user.

ultrathink

Setup: Context Loading

Before deploying any agents:

  1. If the task involves academic writing, read ~/.claude/principles/academic-writing.md for the 30 writing principles organized in 6 categories (A. Structure & Narrative, B. Prose & Style, C. Math & Equations, D. Figures & Tables, E. Citations & Bibliography, F. Process & Meta).
  2. If a project-level .claude/CLAUDE.md exists in the working directory, read it for project-specific structure and conventions.
  3. Check for project-level agents: Glob for .claude/agents/*.md in the working directory. If found, read their frontmatter (name, description, tools) and add them to your available roster alongside the user-level agents listed below. Present project agents in your deployment plan.
  4. Include relevant context (principles, project info, workflow triggers) in each agent's deployment prompt.

Available Worker Agents

Use their name as subagent_type when spawning via the Agent tool:

Review Agents (read-only analysis)

Agent subagent_type Specialization
Consistency Checker consistency-checker Terminology, cross-refs, structural coherence, figure-text alignment
Logic Reviewer logic-reviewer Argument flow, transitions, narrative arc, logical gaps
Technical Reviewer technical-reviewer Math, methodology, results validity, citations, technical accuracy
Writing Reviewer writing-reviewer Prose clarity, conciseness, grammar, tone (reports issues)
LaTeX Layout Auditor latex-layout-auditor PDF layout audit — float placement, alignment, sizing

Audit Agents (read + verify)

Read the full file on GitHub · 354 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. 7d ago First seen · 354 lines · 0 tokens per session scan A 2b1de1505d59

Subscribe to this mod's changes

orchestrate is a skill published in the GitHub repository andrehuang/researcher-pack (49 stars, last pushed 4mo ago), licensed MIT. It adds 119 tokens to every session and 4,380 once invoked, about $0.0006 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens