coordinate

coordinate is a skill for Claude Code from QwenLM/qwen-code. It costs 43 tokens per session (788 once invoked), scanned A, original, Apache-2.0.

A workflow for coordinating a small team of Qwen Code teammates, with assigned tasks, shared work, messages, and controls over whether teammates can edit files.

In plain words
What is it for?
Use it to delegate up to a small number of research or implementation tasks, track their progress, exchange findings, and reconcile their results.
Why use it?
It helps divide an investigation into clear workstreams and combine the results while keeping ownership and editing permissions explicit.

Skill for Claude Code ✓ vendor

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions subagents.

Good fit Use it to delegate up to a small number of research or implementation tasks, track their progress, exchange findings, and reconcile their results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/qwenlm/qwen-code/coordinate
About the project

Qwen Code is an open-source AI coding agent that runs in a terminal and helps developers work with code through language models. It supports multiple model providers and can also be used through IDEs, desktop software, SDKs, and messaging bots.

QwenLM/qwen-code · 28,565 stars · on GitHub · qwenlm.github.io

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 QwenLM/qwen-code --skill coordinate
Clone the repo
git clone --depth 1 https://github.com/QwenLM/qwen-code

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 coordinate

README.md
[![agentmods](https://agentmods.dev/badge/skills/qwenlm/qwen-code/coordinate/github.svg)](https://agentmods.dev/skills/qwenlm/qwen-code/coordinate)
Your own site
<a href="https://agentmods.dev/skills/qwenlm/qwen-code/coordinate"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-code/coordinate/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.

agentmods 80×15 button for coordinate

Your own site · 80×15
<a href="https://agentmods.dev/skills/qwenlm/qwen-code/coordinate"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-code/coordinate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 788 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. Third-party audits
  • Snyk pass 7 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00043 $0.00788
Opus 5.5 $0.00017 $0.00315
Sonnet 5.5 $0.00009 $0.00158
Haiku 4.5 $0.00004 $0.00079

Measured 1mo ago against content hash 0574d33ab74e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

coordinate 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 1mo 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.

packages/core/src/skills/bundled/coordinate/SKILL.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Coordinate Qwen Code Teammates

Act as the team leader. Decompose the goal, keep task ownership clear, reconcile disagreements, and deliver the final result.

Build one bounded team

When team_create is available:

  1. Create one team and one self-contained task per current investigation workstream. Do not queue an implementation task while read-only teammates are idle because tasks are auto-assigned.
  2. Spawn named investigation teammates with read_only: true — one per workstream, and prefer three at most. Never exceed the team's configured cap, which team_create reports; spawning past it fails outright. Do not pass model; use the session-default model unless the selected agent definition explicitly overrides it.
  3. Assign tasks and let teammates collaborate through send_message and the shared task list. Send targeted follow-ups when evidence conflicts, a task needs clarification, or a result is incomplete.
  4. Accept or reject each result based on its evidence. Reassign rejected work instead of silently using it.

Read-only teammates have a positive execution allowlist. They cannot use shell, edit or write files, save memory, create schedules, invoke arbitrary deferred tools, or spawn agents. This is enforced by the runtime, not only by this prompt.

Pin the only writer to a worktree

When the goal requires code changes:

  1. Finish the parallel investigation first.
  2. Call request_shutdown for each investigation teammate. Once shutdown is pending, they are excluded from automatic task assignment.
  3. Call enter_worktree once and keep the returned path.
  4. Create the implementation task, then spawn exactly one named writer with subagent_type: "general-purpose" and working_dir: <path>. Do not set read_only for this teammate.
  5. Give the writer the accepted investigation evidence and require all changes to stay inside the worktree.
  6. Review and verify the worktree result. The leader alone decides whether and how to integrate it into the current branch.
  7. Do not remove the worktree until accepted changes have been integrated or deliberately discarded.

Read the full file on GitHub · 53 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. 1mo ago First seen · 53 lines · 43 tokens per session scan A 0574d33ab74e

Subscribe to this mod's changes

coordinate is a skill published in the GitHub repository QwenLM/qwen-code (28,565 stars, last pushed today), licensed Apache-2.0. It adds 43 tokens to every session and 788 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

sls-dashboard-builder

A tool for creating and modifying importable JSON dashboards for Alibaba Cloud SLS, a service for searching and monitoring logs. It maps checked queries and analysis needs to dashboard charts.

alibaba/loongsuite-pilot · 72 tokens

loongsuite-pilot-insight

A reporting workflow for turning LoongSuite Pilot and AI coding-agent logs into structured reports about events, teams, data quality, development efficiency, and AI use. It defines the meaning of the log fields and the measurements used in dashboards.

alibaba/loongsuite-pilot · 91 tokens

loongsuite-pilot-ops

Skill "loongsuite-pilot-ops" from alibaba/loongsuite-pilot, covering loongsuite-pilot-ops, quick start, todo: add quick start commands and usage.

alibaba/loongsuite-pilot · 15 tokens

proactive-agent

Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack 🦞.

MerkyorLynn/Lynn · 46 tokens

novel-workshop

A workspace for writing novels with an AI assistant, covering outlines, characters, chapters, multiple viewpoints, editing, and book assembly. It treats the author’s files and instructions as the source of truth.

MerkyorLynn/Lynn · 90 tokens

agent-personality

3-layer personality system for AI agents: Yuan (base persona), Ishiki (private self-awareness), Public Ishiki (external behavior rules). Give your agent a consistent character, emotional depth, and safe guest interaction boundaries. Use when: (1) Want agent to have a consistent personality, (2) Agent needs different…

MerkyorLynn/Lynn · 114 tokens