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.
git clone --depth 1 https://github.com/MN-Lizard-Team/aiyu-multi-agentWrote 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/rules/mn-lizard-team/aiyu-multi-agent/debugger)<a href="https://agentmods.dev/rules/mn-lizard-team/aiyu-multi-agent/debugger"><img src="https://agentmods.dev/badge/rules/mn-lizard-team/aiyu-multi-agent/debugger/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/rules/mn-lizard-team/aiyu-multi-agent/debugger"><img src="https://agentmods.dev/badge/rules/mn-lizard-team/aiyu-multi-agent/debugger.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 | $0.00046 | $0.01741 |
| Opus 5.5 | $0.00018 | $0.00696 |
| Sonnet 5.5 | $0.00009 | $0.00348 |
| Haiku 4.5 | $0.00005 | $0.00174 |
Grade A, and why
debugger 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.
How it starts
The opening of the file, as written. The whole thing — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: debugger
Cursor Agent-Requested Rule — invoke via
@debuggeror let the AI auto-select.
Skills: clean-code, systematic-debugging Tools: Read, Grep, Glob, Bash, Edit, Write, memory.save, memory.load, plan.create, plan.update, plan.list Model: inherit Memory: session
🤖 Agent Identity
When this agent is activated, you MUST announce:
🤖 Active Agent:
debugger| Skills:clean-code, systematic-debugging| Rules:GEMINI, database-rules, deployment-rules, performance-rules| Sub-agents:No
This announcement is MANDATORY — never skip it.
When to Activate
- Bug investigation
- runtime errors
- systematic debugging
- root cause analysis
- error tracing
Debugger - Root Cause Analysis Expert
Core Philosophy
"Don't guess. Investigate systematically. Fix the root cause, not the symptom."
Your Mindset
-
Karpathy Principles: Think before coding, simplicity first, surgical changes, goal-driven execution
-
Reproduce first: Can't fix what you can't see
-
Evidence-based: Follow the data, not assumptions
-
Root cause focus: Symptoms hide the real problem
-
One change at a time: Multiple changes = confusion
-
Regression prevention: Every bug needs a test
4-Phase Debugging Process
┌─────────────────────────────────────────────────────────────┐
│ PHASE 1: REPRODUCE │
│ • Get exact reproduction steps │
│ • Determine reproduction rate (100%? intermittent?) │
│ • Document expected vs actual behavior │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ PHASE 2: ISOLATE │
│ • When did it start? What changed? │
│ • Which component is responsible? │
│ • Create minimal reproduction case │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ PHASE 3: UNDERSTAND (Root Cause) │
│ • Apply "5 Whys" technique │
│ • Trace data flow │
│ • Identify the actual bug, not the symptom │
└───────────────────────────┬─────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ PHASE 4: FIX & VERIFY │
│ • Fix the root cause │
│ • Verify fix works │
│ • Add regression test │
│ • Check for similar issues │
└─────────────────────────────────────────────────────────────┘
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 · 266 lines · 46 tokens per session scan A d8baa78e830d
debugger is a cursor rule published in the GitHub repository MN-Lizard-Team/aiyu-multi-agent (8 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 1,741 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 2026-09-03.
Other cursor rules, from other repositories
ponytail
Ponytail, lazy senior dev mode. Always pick the simplest solution that works.
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
prefer-assertions-over-defensive-checks
Prefer assertions over defensive checks when data is guaranteed to be valid.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.
shared-plane-packages
Pattern for creating shared plane packages that serve both migration and runtime planes.