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-claude --skill deploy-teamgit clone --depth 1 https://github.com/Rockielab/rockie-claudeWrote 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-claude/deploy-team)<a href="https://agentmods.dev/skills/rockielab/rockie-claude/deploy-team"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-claude/deploy-team/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-claude/deploy-team"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-claude/deploy-team.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 | $0.00116 | $0.00964 |
| Opus 5.5 | $0.00046 | $0.00386 |
| Sonnet 5.5 | $0.00023 | $0.00193 |
| Haiku 4.5 | $0.00012 | $0.00096 |
Grade A, and why
deploy-team 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- deploy-team — 95% identical, 14 lines differ
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/deploy-team — configurable agent teams via Claude CLI
Spawns N claude CLI processes in parallel, each with a distinct role prompt,
shared access to a thread, and (optionally) shared context files. Returns a
concatenated report the main agent reads and synthesizes.
When to use a team vs a single subagent
- Single subagent (via native Agent tool): focused, single-responsibility work with a known output shape. Example: "research agent: find 3 recent papers on X and summarize."
- Team (
/deploy-team): multi-perspective work where agents should see each other's findings and challenge them. Example: "gauntlet a new experiment idea — brainstorm, research, attack, validate."
Invocation
python3 .claude/skills/deploy-team/runtime/orchestrator.py \
--template gauntlet \
--topic "should we run the quadratic readout PC control next?" \
[--context matrix-thinking/KILL_LIST.md EXPERIMENT_LOG.md] \
[--max-minutes 15]
Or with a custom config instead of a template:
python3 .claude/skills/deploy-team/runtime/orchestrator.py \
--config path/to/custom-team.json \
--topic "..."
Templates
- gauntlet — 4 agents: brainstormer, researcher, attacker, validator. For: new ideas. The attacker tries to kill; validator checks survivors.
- pre-launch-audit — 3 agents: security, correctness, simplicity. For: reviewing experiment scripts / new code before GPU time.
- post-run-analysis — 3 agents: positive, adversarial, contextualizer. For: interpreting a completed run from multiple angles.
- blog-coherence — 2 agents: style, factual-alignment. For: verifying a new finding doesn't contradict existing site content.
Custom templates live in .claude/skills/deploy-team/templates/*.json.
Run artifacts
Each run creates .team-runs/<run-id>/:
config.json— resolved config (template + topic + context)thread.md— shared append-only thread (agents post findings for peers)context/— symlinked context files agents can readagents/<name>/prompt.txt— the exact prompt sentoutput.md— agent's final written findingsevents.jsonl— raw stream-json events (debug)
REPORT.md— combined report generated by the orchestrator
What ships with it
4 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 · 90 lines · 116 tokens per session scan A 232e6ed456c9
deploy-team is a skill published in the GitHub repository Rockielab/rockie-claude (23 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 116 tokens to every session and 964 once invoked, about $0.0005 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.
Other skills, from other repositories
auto-run
Autonomous personalized research loop. Use when the user wants to research a topic autonomously, run a research loop, start adaptive research, or use presets like technique-scout or cross-domain. Triggers on: 'auto run', 'research loop', 'autonomous research', 'run research', 'start research', 'adaptive research'.
autoresearch
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports…
excel-workbook
A basic Excel workbook tool for creating, inspecting, editing, and checking .xlsx files. It supports worksheets, cells, simple formulas, dates, and basic formatting, but not macros, charts, pivot tables, or external workbook links.
git-commit
A guided Git commit workflow that examines changes and creates a commit message using the Conventional Commits format, a shared style for labeling changes such as features, fixes, tests, or documentation.
pi-sync
Daily upstream-sync job for the pi Go port — fetch upstream pi, triage every change since the recorded pin, port what's in scope, verify idiomatic + parity via independent reviews, update the ledger, and push. Use for "sync with upstream", "porting job", or as the scheduled daily run.
pi-triage
Decide whether an upstream pi change needs porting to the Go port. Use when assessing upstream commits/PRs ("should we port X?"), or as the triage stage of /pi-sync. Outputs a WHY/WHAT/SCOPE verdict per change.