Borrowing it
Nothing to install: this file belongs to Coinyak/onchainai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Coinyak/onchainai/main/.agents/skills/multi-agent-coordination/SKILL.mdgit clone --depth 1 https://github.com/Coinyak/onchainaiWrote 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/coinyak/onchainai/multi-agent-coordination)<a href="https://agentmods.dev/skills/coinyak/onchainai/multi-agent-coordination"><img src="https://agentmods.dev/badge/skills/coinyak/onchainai/multi-agent-coordination/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/coinyak/onchainai/multi-agent-coordination"><img src="https://agentmods.dev/badge/skills/coinyak/onchainai/multi-agent-coordination.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 | $0.00066 | $0.00440 |
| Opus 5.5 | $0.00026 | $0.00176 |
| Sonnet 5.5 | $0.00013 | $0.00088 |
| Haiku 4.5 | $0.00007 | $0.00044 |
Grade A, and why
multi-agent-coordination 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.
What it actually says
Multi-Agent Coordination
Read before spawning subagents:
docs/MULTI_AGENT_COORDINATION.md— roster, DAG, verification matrixdocs/MCP_AGENT_WORKFLOW.md— Vercel/Railway/GitHub/onchainai routingdocs/handoff-packet-template.md— required between agents
Quick roster
| Role | Paths |
|---|---|
| Backend Core | src/ (API, crawler, MCP) |
| Frontend Surface | frontend/ |
| Data & Schema | migrations/, sqlx prepare |
| Harness & Deploy | scripts/, .github/, .grok/, .cursor/ |
| Security & Trust | auth, admin, install_safety, x402 |
Coordinator: DAG + merge handoffs + agent-harness-check.sh + user summary.
Spawn checklist
git status --short- Assign exclusive globs; no two writers on same file
- Serialize seams: schema → API contract packet → frontend
- MCP read-only by default; deploy only via
./scripts/deploy-railway.shwhen user asks - Handoff packet on every boundary
MCP (observe, not replace gates)
- vercel — Next deploy/logs (
onchain-ai/onchainai) - railway — API logs, env names, deploy status
- onchainai — live product queries
- github — PR/diff when user names a PR
Never paste secrets from MCP output. Never redeploy via MCP without explicit user approval.
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 · 47 lines · 66 tokens per session scan A 2bdf0963a7b3
multi-agent-coordination is a skill published in the GitHub repository Coinyak/onchainai (1 stars, last pushed 3mo ago), licensed MIT. It adds 66 tokens to every session and 440 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 2026-08-31.
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