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.
npx agentmods add skills/spideynolove/claude-dotfiles/rlm-debuggingnpx skills add spideynolove/claude-dotfiles --skill rlm-debugginggit clone --depth 1 https://github.com/spideynolove/claude-dotfilesWrote 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/spideynolove/claude-dotfiles/rlm-debugging)<a href="https://agentmods.dev/skills/spideynolove/claude-dotfiles/rlm-debugging"><img src="https://agentmods.dev/badge/skills/spideynolove/claude-dotfiles/rlm-debugging.svg" alt="Measured on agentmods" 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 | $0.00070 | $0.03307 |
| Opus 5 | $0.00035 | $0.01654 |
| Sonnet 5 | $0.00014 | $0.00661 |
| Haiku 4.5 | $0.00007 | $0.00331 |
Grade A, and why
rlm-debugging 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 5d 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.
This is a copy
86% identical to recursive-debugging — 68 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 478 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RLM Systematic Debugging (Phase 1.5)
Overview
When a requirement involves fixing a bug or investigating unexpected behavior, ad-hoc fixes waste time and create new bugs. Systematic debugging finds the root cause before any fix is attempted.
Core Principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
The Iron Law for RLM Debugging:
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
Trigger examples
Tests are failing after the last change; debug itFix crash on empty inputInvestigate why the API returns wrong dataDo a root cause analysis before making changes
When to Use
Mandatory Phase 1.5 when:
- Requirement is a bug fix
- Test failures need investigation
- Unexpected behavior reported
- Performance problems
- Integration issues
Use ESPECIALLY when:
- Under time pressure (emergencies make guessing tempting)
- "Just one quick fix" seems obvious
- Previous fix attempts failed
- You don't fully understand the issue
Don't skip when:
- Issue seems simple (simple bugs have root causes too)
- You're in a hurry (rushing guarantees rework)
- Manager wants it fixed NOW (systematic is faster than thrashing)
Phase 1.5 Insertion
Phase 1.5 is inserted between Phase 1 (AS-IS) and Phase 2 (TO-BE Plan) when debugging is required:
Phase 0: 00-requirements.md
->
Phase 1: 01-as-is.md (captures current behavior)
->
Phase 1.5: 01.5-root-cause.md <- NEW (this skill)
->
Phase 2: 02-to-be-plan.md (includes fix plan based on root cause)
The Four Phases of Systematic Debugging
digraph debugging_phases {
rankdir=TB;
phase1 [label="Step 1:\nRoot Cause Investigation", shape=box, style=filled, fillcolor="#ffcccc"];
phase2 [label="Step 2:\nPattern Analysis", shape=box, style=filled, fillcolor="#ffffcc"];
phase3 [label="Step 3:\nHypothesis & Testing", shape=box, style=filled, fillcolor="#ccffcc"];
phase4 [label="Step 4:\nFix Implementation", shape=box, style=filled, fillcolor="#ccccff"];
phase1 -> phase2 -> phase3 -> phase4;
// Feedback loops
phase3 -> phase1 [label="hypothesis\nfailed", style=dashed];
phase4 -> phase1 [label="fix\nfailed", style=dashed];
}
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.
- 5d ago First seen · 478 lines · 70 tokens per session scan A be5864724ac3
rlm-debugging is a skill published in the GitHub repository spideynolove/claude-dotfiles (2 stars, last pushed 3mo ago), licensed MIT. It adds 70 tokens to every session and 3,307 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to recursive-debugging, differing in 68 lines, and is treated as a copy.
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