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 agentmods add skills/yimwoo/codex-agenteam/runnpx skills add yimwoo/codex-agenteam --skill rungit clone --depth 1 https://github.com/yimwoo/codex-agenteamWrote 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/yimwoo/codex-agenteam/run)<a href="https://agentmods.dev/skills/yimwoo/codex-agenteam/run"><img src="https://agentmods.dev/badge/skills/yimwoo/codex-agenteam/run.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.08486 |
| Opus 5 | $0.00013 | $0.04243 |
| Sonnet 5 | $0.00005 | $0.01697 |
| Haiku 4.5 | $0.00003 | $0.00849 |
Grade A, and why
run 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 6d 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 — 887 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgenTeam Run
Orchestrate a full team pipeline for a task. This is the main entry point for collaborative AI-assisted development. You are the lead; AgenTeam dispatches your specialists.
Process
1. Auto-Init Guard
Check for .agenteam/config.yaml, .agenteam.team/config.yaml, or legacy
agenteam.yaml in the project root. If all are missing:
- Create config dir:
mkdir -p .agenteam - Copy the template:
cp <plugin-dir>/templates/agenteam.yaml.template .agenteam/config.yaml - Set the team name to the project directory name
- Generate agents:
python3 <runtime>/agenteam_rt.py generate - Tell the user: "AgenTeam auto-initialized with default roles. Edit
.agenteam/config.yamlto customize." - Then continue with the requested run in the same turn. Auto-init is a prerequisite, not the end of the workflow.
2. Accept Task
Get the task description from the user. If not provided, ask: "What task should the team work on?"
2b. Select Profile
If the project config defines pipeline profiles, select one before init:
- Read
pipeline.profilesfrom config (check ifpipelinekey is a dict with aprofilessub-key). If no profiles defined, skip this step. - If the user already specified
--profile <name>in their request, use it directly and skip classification. - If profiles are defined:
- Read each profile's
hintslist (advisory examples of task shape) - Select the best-fit profile using judgment over the task description and hints. Do not keyword-match — use hints as examples of the kind of task each profile is designed for.
- Announce: "Using profile quick (one-line fix). Override with
--profile standardif needed." - Do not pause for confirmation unless confidence is low or the profile materially shortens the pipeline (e.g., skipping 5 of 7 stages).
- Read each profile's
- If uncertain which profile fits, default to
full(all stages). Misclassification fails safe. - Pass
--profile <name>to the init command in step 3.3:python3 <runtime>/agenteam_rt.py init --task "<task>" --profile <name>
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.
- 6d ago First seen · 887 lines · 25 tokens per session scan A 74c3c5d2f0c4
run is a skill published in the GitHub repository yimwoo/codex-agenteam (13 stars, last pushed 2mo ago), licensed MIT. It adds 25 tokens to every session and 8,486 once invoked, about $0.0001 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.
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