systematic-debugging

systematic-debugging is a skill for Claude Code from bobmatnyc/claude-mpm-skills. It costs 61 tokens per session (1,162 once invoked), scanned A, original, MIT.

A step-by-step method for investigating software bugs by reproducing them, isolating the failing part, finding the underlying cause, fixing it, and checking the result.

In plain words
What is it for?
Use it when handling errors, crashes, failing tests, unexpected behavior, or unclear problems in an application.
Why use it?
It prevents guesswork and helps distinguish the original cause of a failure from the place where the error becomes visible.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it when handling errors, crashes, failing tests, unexpected behavior, or unclear problems in an application.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bobmatnyc/claude-mpm-skills/systematic-debugging
Install

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.

Any agent
npx skills add bobmatnyc/claude-mpm-skills --skill systematic-debugging
Clone the repo
git clone --depth 1 https://github.com/bobmatnyc/claude-mpm-skills

Made for: Claude Code.

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 systematic-debugging

README.md
[![agentmods](https://agentmods.dev/badge/skills/bobmatnyc/claude-mpm-skills/systematic-debugging/github.svg)](https://agentmods.dev/skills/bobmatnyc/claude-mpm-skills/systematic-debugging)
Your own site
<a href="https://agentmods.dev/skills/bobmatnyc/claude-mpm-skills/systematic-debugging"><img src="https://agentmods.dev/badge/skills/bobmatnyc/claude-mpm-skills/systematic-debugging/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 systematic-debugging

Your own site · 80×15
<a href="https://agentmods.dev/skills/bobmatnyc/claude-mpm-skills/systematic-debugging"><img src="https://agentmods.dev/badge/skills/bobmatnyc/claude-mpm-skills/systematic-debugging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,162 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00061 $0.01162
Opus 5 $0.00030 $0.00581
Sonnet 5 $0.00012 $0.00232
Haiku 4.5 $0.00006 $0.00116

Measured 9d ago against content hash 88c1d2d7c6a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

systematic-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 9d 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.

universal/debugging/systematic-debugging/SKILL.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Systematic Debugging

When to Use

  • A bug, error, exception, or crash needs investigation
  • Something is "not working" and the cause is unclear
  • A test is failing and the reason isn't obvious
  • Unexpected behavior needs troubleshooting in any language or framework

Core Workflow

Follow these five phases sequentially. Do not skip ahead to fixing before completing isolation and tracing.

Phase 1: Reproduce

Establish a reliable way to trigger the bug before doing anything else.

  1. Read the full error message, stack trace, and logs — note exact text, line numbers, and error codes
  2. Create a minimal reproduction case that triggers the issue consistently
  3. Record the exact steps, inputs, and environment that cause the failure

Checkpoint: Can you trigger the bug on demand? If intermittent, gather more data before proceeding.

Phase 2: Isolate

Narrow down where the failure originates.

  1. Use binary search to find the failing component — disable or stub out halves of the system
  2. Check recent changes with git log --oneline -20 and git diff against the last known good state
  3. Add targeted logging or use a debugger to observe state at key boundaries
# Find which commit introduced the bug
git bisect start
git bisect bad HEAD
git bisect good <last-known-good-commit>
# Git will checkout midpoints — test each one and mark good/bad

Checkpoint: The bug is traced to a specific function, module, or data flow.

Phase 3: Trace to Root Cause

Understand why the failure happens — not just where.

  1. Read the code path completely from entry point through the failure site
  2. Check assumptions: what does each function expect vs. what it actually receives?
  3. Trace data flow backward — where does the bad value originate?
  4. Verify with evidence: add assertions or print statements to confirm your hypothesis
# Example: verify assumptions about incoming data
def process_order(order):
    assert order.status == "pending", f"Expected pending, got {order.status}"
    assert order.items, "Order has no items"
    # ... rest of processing

Read the full file on GitHub · 118 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 118 lines · 61 tokens per session scan A 88c1d2d7c6a5

Subscribe to this mod's changes

systematic-debugging is a skill published in the GitHub repository bobmatnyc/claude-mpm-skills (75 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 1,162 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 2026-09-03.

Related

Other skills, from other repositories

systematic-debugging

4-phase root cause debugging: understand bugs before fixing.

NousResearch/hermes-agent · 16 tokens

langsmith-observability

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

davila7/claude-code-templates · 45 tokens

experimental-code-coverage-local-debugger

Runs code coverage locally via Universal Test Runner (UTR) or helper scripts, mimicking LUCI trybots. Activate when CQ tryjobs fail or underreport coverage, to test local GN/recipe repairs before uploading, or to debug hermetic crashes.

chromium/chromium · 59 tokens

adversarial-reviewer

Adversarial code review that assumes bugs exist and hunts for them. Use when asked to review code, find bugs, audit for correctness, stress-test a PR, or when someone says "tear this apart" or "what's wrong with this". Give no benefit of the doubt — every line is guilty until proven innocent.

emdash-cms/emdash · 71 tokens

cli-e2e

Write, modify, or debug Docker-based Composio CLI end-to-end tests under ts/e2e-tests/cli, including binary invocation, fixture isolation, output assertions, and package manifests. Use for CLI E2E test suites only; use cli-command for CLI source implementation.

ComposioHQ/composio · 62 tokens

work

Deliver one maintainer-approved EmDash issue, choosing the bug-fix path for a defect and the direct implementation path for an enhancement or task.

emdash-cms/emdash · 31 tokens