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 Rockielab/rockie-codex --skill deploy-team-dashboardgit clone --depth 1 https://github.com/Rockielab/rockie-codexWrote 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/rockielab/rockie-codex/deploy-team-dashboard)<a href="https://agentmods.dev/skills/rockielab/rockie-codex/deploy-team-dashboard"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-codex/deploy-team-dashboard/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/rockielab/rockie-codex/deploy-team-dashboard"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-codex/deploy-team-dashboard.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 | $0.00069 | $0.01453 |
| Opus 5 | $0.00034 | $0.00727 |
| Sonnet 5 | $0.00014 | $0.00291 |
| Haiku 4.5 | $0.00007 | $0.00145 |
Grade A, and why
deploy-team-dashboard 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 9d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
deploy-team-dashboard — multi-agent team on a hard problem
The tool is installed at $HOME/.codex/teams/. It operates on the repository where the main agent is currently working (resolved via git rev-parse --show-toplevel), not where the tool itself is installed.
When to summon
Only deploy a team when ALL THREE hold:
- Multi-dimensional problem. The question has several aspects that must be optimized simultaneously and traded off against each other — not one question with one best answer.
- Cross-pollination matters. You want the agents to read each other's findings mid-work and adjust. If they could produce their answers in isolation, use the Agent tool instead.
- Observability is useful. The developer should be able to watch the work unfold and intervene (post to the thread, DM an agent, pause, stop).
If any one is missing, use a specialist subagent via the Agent tool.
When NOT to summon
- One question with one right answer (find all uses of X, fix this bug, audit this function) — use the appropriate subagent
- Time-critical work — teams have 30+ second spin-up
- Fire-and-forget parallel dispatch — the Agent tool already does that
- Anything where you already know the answer and just need it typed — use a specialist
Flow
- Compose a team config (JSON). Shape is authoritative at
$HOME/.codex/teams/schema.json— follow it rather than inventing fields. - Show the config to the developer for approval before spending the compute.
- Invoke from the repo you're working in:
node "$HOME/.codex/teams/orchestrator/index.js" <path/to/config.json> - The orchestrator validates the config, stages any referenced context files, creates a git worktree per agent, starts the dashboard, opens it in Chrome, runs the team, and writes
result.jsonwhen done. - When agents finish (all
AGENT_DONE, deadline hits, orstop_teamfires), readresult.jsonandthread.mdto synthesize findings back to the developer.
Config (authoritative at $HOME/.codex/teams/schema.json)
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.
- 9d ago First seen · 91 lines · 69 tokens per session scan A 9ab6d07ec244
deploy-team-dashboard is a skill published in the GitHub repository Rockielab/rockie-codex (20 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 69 tokens to every session and 1,453 once invoked, about $0.0003 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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