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 skills add opensquad-ai/opensquad --skill agent_managementgit clone --depth 1 https://github.com/opensquad-ai/opensquadWrote 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.
[](https://agentmods.dev/skills/opensquad-ai/opensquad/agent_management)<a href="https://agentmods.dev/skills/opensquad-ai/opensquad/agent_management"><img src="https://agentmods.dev/badge/skills/opensquad-ai/opensquad/agent_management/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.
<a href="https://agentmods.dev/skills/opensquad-ai/opensquad/agent_management"><img src="https://agentmods.dev/badge/skills/opensquad-ai/opensquad/agent_management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.07307 |
| Opus 5.5 | $0.00000 | $0.02923 |
| Sonnet 5.5 | $0.00000 | $0.01461 |
| Haiku 4.5 | $0.00000 | $0.00731 |
Grade A, and why
agent_management scanned grade A with 1 finding 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- Each Agent is an independent process (`subprocess.Popen`) How it starts
The opening of the file, as written. The whole thing — 1,126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Management Complete Guide
Overview
This Skill provides a complete management guide for OpenSquad Agents, covering the full workflow of creation, configuration, deployment, and troubleshooting.
Key Contents:
- Quick Agent creation (live in 5 minutes)
- Configuration file reference (model, role, tools)
- Architecture internals (process isolation, IM accounts)
- Troubleshooting and best practices
Note If the user does not specify a name when creating an agent, you may decide based on the task content. The account email can also be named in relation to the actual business. The password used when registering the account is the group password configured for the agent — remember it. You may configure a role card for the agent based on business needs.
Important — account registration is a separate step: agent_factory.create_agent only creates the directory structure and config file. It does not automatically register a chat account. You must call chat_account.register_account (Step 1) before creating the agent. The five-step flow below reflects the correct order. (As a fallback, if the agent process starts and the account does not yet exist, bridge.login() will attempt auto-registration at runtime — but you should not rely on this; always register the account explicitly first.)
Part 1: Quick Start
1. Five Steps to Create an Agent
Step 1: Register a ChatPro Account
Each Agent needs an independent account to log into the group chat system.
chat_account.register_account(
email="mybot@ai", # Account email, unique per Agent
password="Bot@2026", # Login password
name="My Assistant" # Display name
)
Step 2: Create or Join a Group
Create a new group:
chat_account.create_group(
email="mybot@ai", # Operating account email
password="Bot@2026", # Password
group_name="AI Workspace" # Group name
)
# Returns group_id, used when configuring config.json
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 1,126 lines · 0 tokens per session scan A 2a389576224e
agent_management is a skill published in the GitHub repository opensquad-ai/opensquad (6 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 7,307 tokens. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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