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 oil-oil/codex-team-mode --skill team-modegit clone --depth 1 https://github.com/oil-oil/codex-team-modeWrote 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/oil-oil/codex-team-mode/team-mode)<a href="https://agentmods.dev/skills/oil-oil/codex-team-mode/team-mode"><img src="https://agentmods.dev/badge/skills/oil-oil/codex-team-mode/team-mode/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/oil-oil/codex-team-mode/team-mode"><img src="https://agentmods.dev/badge/skills/oil-oil/codex-team-mode/team-mode.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00080 | $0.01030 |
| Opus 5.5 | $0.00032 | $0.00412 |
| Sonnet 5.5 | $0.00016 | $0.00206 |
| Haiku 4.5 | $0.00008 | $0.00103 |
Grade A, and why
team-mode 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.
How it starts
The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team Mode
The main agent decomposes the user's task, decides what to delegate, and accepts the result. A task's size alone does not require subagents. On activation, send one brief commentary update in the user's language prefixed with 👾 (in Chinese: 👾 已开启小队模式。).
When to dispatch
Delegate a defined part of the task when a child can make useful progress through implementation, codebase discovery, review, or expert work. The main agent owns how the parts fit together, unresolved product decisions, and final acceptance. There is no target number of agents or required sequence.
Choose the smallest count that covers the independent work. One child is the default for one bounded question or review lens. Add children only when each can work and report independently, with a distinct question, scope, or lens. A large diff alone is not a reason to fan out.
Consider coordination and usage overhead. Respect the host's active-agent limit; if parallel dispatch is unavailable, continue sequentially or inline without silently dropping coverage.
Explorer— use for substantial codebase discovery at the start of a task. Handle small lookups and general research directly. Read Explore for this route.Executor— use when the intended result and file ownership are clear enough for independent implementation. Give each target one owner.Reviewer— use when the user asks for review or a completed result has a meaningful risk of unnoticed defects. Review the assigned result without steering toward a suspected answer; save a Markdown report when a lasting record helps.ExpertAdvisor— use for a complex architecture or high-impact decision, a problem unresolved after repeated attempts, or modeling or complex computer automation the main agent cannot handle well. Ask for an independent plan or assign the expert a concrete outcome to produce.
When the user asks to simplify code, or before committing a code change, follow Simplify for scoped cleanup and final review. The main agent decides which findings to apply and accepts the final result.
What ships with it
9 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 Changed · -90 lines b7298622cefb
- 1mo ago Changed · +19 lines · +1 tokens per session da54f7537ce4
- 1mo ago Changed · +3 tokens per session fd216d09c006
- 1mo ago First seen · 121 lines · 76 tokens per session scan A 5a1f10c8801c
team-mode is a skill published in the GitHub repository oil-oil/codex-team-mode (227 stars, last pushed 24d ago), licensed MIT. It adds 80 tokens to every session and 1,030 once invoked, about $0.0003 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.
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