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multi-agent-system-pattern: Skill for Cursor

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

loop-engineering is a skill for Cursor from vpeetla-ai/multi-agent-system-pattern. It costs 48 tokens per session (307 once invoked), scanned A, original, MIT.

Engineering guidance for loops in self-improving AI systems, including retrieval, memory, evaluation, and tool use.

In plain words
What is it for?
Use it to build agent loops, tune RAG systems—tools that retrieve relevant documents—bridge MCP tools, and maintain procedural memory.
Why use it?
It connects observed failures to changes in search settings, stored lessons, tests, and review scores.

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 48 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/loop-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 loop-engineering

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/vpeetla-ai/multi-agent-system-pattern/loop-engineering"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/multi-agent-system-pattern/loop-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 307 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 $0.00048 $0.00307
Opus 5.5 $0.00019 $0.00123
Sonnet 5.5 $0.00010 $0.00061
Haiku 4.5 $0.00005 $0.00031

Measured 2mo ago against content hash 7f855b529f66, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

loop-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/loop-engineering/SKILL.md · 43 lines

What it actually says

Loop Engineering

ODAEU outer loop

Phase Action
Observe Load RAG config vN, memory hints, corpus context
Decide Plan ReAct steps or orchestrator decomposition
Act MCP tools (read_file, search_docs) or repo patches
Evaluate Recall, faithfulness, pytest, review score
Update Tune RAG (top_k, hybrid_alpha) + write lesson

RAG evolve signals

Failure Tune
low_recall ↑ top_k, ↑ hybrid_alpha
low_faithfulness ↑ rerank_threshold, ↓ hybrid_alpha

Memory

  • Lesson(failure_mode, lesson, rag_version) → JSON store (v1)
  • Hints injected on next run via hints_for_query

MCP bridge

  • Local adapters in mcp/bridge.py; extensible to stdio MCP servers
  • Never give agents raw shell without allowlist

Reference

  • loop-engine-agent-platform/src/loop_engine/harness/
  • loops/support-intelligence.yaml
  • ADR-001 in LoopForge repo
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 · 43 lines · 48 tokens per session scan A 7f855b529f66

Subscribe to this mod's changes

loop-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 48 tokens to every session and 307 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.

Data and AIMemory and contextMulti-AgentPythonai-agentslanggraphtutorial
Related

loop-engineering compared with skills from other repositories

loop-engineering next to 6 skills from other repositories
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loop-engineeringvpeetla-ai/multi-agent-system-patternSkill22mo agoMITA48Cursor
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memmachine-memoryMemMachine/MemMachineSkill3.1kyesterdayApache-2.0A96Codex
stripe-directorystripe/aiSkill2.0kyesterdayMITC212Claude Code
langchainznlgis/opengis-skillsSkill7610d agoMITA93Claude Code, Codex