Borrowing it
Nothing to install: this file belongs to vpeetla-ai/multi-agent-system-pattern. 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/vpeetla-ai/multi-agent-system-pattern/main/.cursor/skills/setup-vpeetla-skills/SKILL.mdgit clone --depth 1 https://github.com/vpeetla-ai/multi-agent-system-patternWrote 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/vpeetla-ai/multi-agent-system-pattern/setup-vpeetla-skills)<a href="https://agentmods.dev/skills/vpeetla-ai/multi-agent-system-pattern/setup-vpeetla-skills"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/multi-agent-system-pattern/setup-vpeetla-skills/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/vpeetla-ai/multi-agent-system-pattern/setup-vpeetla-skills"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/multi-agent-system-pattern/setup-vpeetla-skills.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 | $0.00058 | $0.00356 |
| Opus 5 | $0.00029 | $0.00178 |
| Sonnet 5 | $0.00012 | $0.00071 |
| Haiku 4.5 | $0.00006 | $0.00036 |
Grade A, and why
setup-vpeetla-skills 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 10d 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:
- setup-vpeetla-skills — 100% identical, 0 lines differ
What it actually says
Setup vpeetla-ai Skills
Run once per repository.
Checklist
- Confirm repo is in vpeetla-ai org
- Install skills:
./scripts/install.sh --cursor --project .from vpeetla-ai-skills - Copy
CONTEXT.mdif missing (or symlink from skills repo) - Add
AGENTS.md(Codex) — merge, do not overwrite custom sections - Identify stack layer (see governed-ai-stack skill)
Ask the user
- Issue tracker: GitHub Issues / Linear / local
docs/issues/ - Triage labels: e.g.
agent-task,hitl-required,loopforge - Docs path:
docs/(default) oradr/
Write .vpeetla-skills.json in repo root
{
"issue_tracker": "github",
"docs_path": "docs",
"stack_layer": "self-improvement",
"gateway_required": false
}
Verify
-
pytest -qornpm testpasses (if applicable) - README has honest implementation status table
-
docs/ECOSYSTEM.mdor link to ai-architecture-portfolio exists for platform repos
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.
- 10d ago First seen · 43 lines · 58 tokens per session scan A 944bd3875645
setup-vpeetla-skills is a skill published in the GitHub repository vpeetla-ai/multi-agent-system-pattern (2 stars, last pushed 5d ago), licensed MIT. It adds 58 tokens to every session and 356 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 2026-08-31.
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food-advisor
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