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multi-agent-system-pattern: Skill for Cursor

.cursor/skills/agentic-engineering/SKILL.md

agentic-engineering is a skill for Cursor from vpeetla-ai/multi-agent-system-pattern. It costs 46 tokens per session (323 once invoked), scanned A, original, MIT.

A disciplined way to build software with an AI coding agent: understand the task first, make the smallest necessary changes, and check the result with tests.

In plain words
What is it for?
Use it for implementation tasks where code quality matters, especially when changing agent workflows, routing, or behavior in an existing repository.
Why use it?
It reduces unnecessary edits, speculative redesigns, and claims that work is finished without verification. It also highlights risky changes that need extra review or human approval.

Skill for Cursor

Written for Cursor: installed under .cursor/.

This is vpeetla-ai/multi-agent-system-pattern's own configuration. It tells Cursor how to work on multi-agent-system-pattern itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything multi-agent-system-pattern configures →

not rated 2repo 2mo ago A scan 46 tokens original MIT
View source ↗ vpeetla-ai/multi-agent-system-pattern multi-agent-system-pattern.vercel.app
Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/vpeetla-ai/multi-agent-system-pattern/main/.cursor/skills/agentic-engineering/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/vpeetla-ai/multi-agent-system-pattern

Made for: Cursor.

Wrote 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.

agentmods badge for agentic-engineering

README.md
[![agentmods](https://agentmods.dev/badge/skills/vpeetla-ai/multi-agent-system-pattern/agentic-engineering/github.svg)](https://agentmods.dev/skills/vpeetla-ai/multi-agent-system-pattern/agentic-engineering)
Your own site
<a href="https://agentmods.dev/skills/vpeetla-ai/multi-agent-system-pattern/agentic-engineering"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/multi-agent-system-pattern/agentic-engineering/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.

agentmods 80×15 button for agentic-engineering

Your own site · 80×15
<a href="https://agentmods.dev/skills/vpeetla-ai/multi-agent-system-pattern/agentic-engineering"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/multi-agent-system-pattern/agentic-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 323 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.00323
Opus 5.5 $0.00018 $0.00129
Sonnet 5.5 $0.00009 $0.00065
Haiku 4.5 $0.00005 $0.00032

Measured 2mo ago against content hash eacbd34bf3d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agentic-engineering 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 2mo 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.cursor/skills/agentic-engineering/SKILL.md · 40 lines

What it actually says

Agentic Engineering

Not vibe coding — preserve professional quality while moving faster.

Before writing code

  1. State assumptions and success criteria (tests, API response, UI behavior)
  2. Identify smallest change that satisfies the request
  3. Read surrounding files — match naming, types, error handling

While coding

  • Simplicity first — no speculative abstractions or "while I'm here" refactors
  • Surgical diffs — touch only files required for the task
  • Match conventions — see target repo's pyproject.toml, eslint, existing patterns

Before claiming done

  1. Run relevant tests (pytest -q, npm test, typecheck)
  2. For agent graphs: verify routing + at least one happy-path trace
  3. Summarize what changed and what was not changed (scope boundary)

Red flags — stop and ask

  • Request touches governance + orchestration in one PR (split layers)
  • Side effect without gateway/HITL (publish, push, notify)
  • No test strategy for new behavior

Reference

Karpathy: From Vibe Coding to Agentic Engineering

Changes

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.

  1. 2mo ago First seen · 40 lines · 46 tokens per session scan A eacbd34bf3d7

Subscribe to this mod's changes

agentic-engineering is a skill published in the GitHub repository vpeetla-ai/multi-agent-system-pattern (2 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 323 once invoked, about $0.0002 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.

Multi-AgentPlanningPythonTestingai-agentslanggraphtutorial
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