systematic-debugging

systematic-debugging is a skill for Claude Code from itallstartedwithaidea/agent-skills. It costs 24 tokens per session (1,353 once invoked), scanned A, original, MIT.

A four-phase method for finding the underlying cause of a software bug: reproduce it, rank possible causes, test them with small measurements, and apply a targeted fix.

In plain words
What is it for?
It helps investigate failing or intermittent tests, stack traces, user-reported bugs, and problems that appear after recent changes.
Why use it?
It replaces changing several things at once with evidence-based investigation, making it clearer why the bug occurred and whether the fix works.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Claude Code; built for cline.

Part of the software-dev-skills plugin — 8 skills shipped together , and of all-skills

Good fit It helps investigate failing or intermittent tests, stack traces, user-reported bugs, and problems that appear after recent changes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/itallstartedwithaidea/agent-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 itallstartedwithaidea/agent-skills --skill systematic-debugging
Clone the repo
git clone --depth 1 https://github.com/itallstartedwithaidea/agent-skills

Made for: Claude Code.

Or install software-dev-skills, the plugin that ships this one along with the rest of its 8 skills.

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/itallstartedwithaidea/agent-skills/systematic-debugging/github.svg)](https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/systematic-debugging)
Your own site
<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/systematic-debugging"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-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/itallstartedwithaidea/agent-skills/systematic-debugging"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/systematic-debugging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,353 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 $0.00024 $0.01353
Opus 5.5 $0.00010 $0.00541
Sonnet 5.5 $0.00005 $0.00271
Haiku 4.5 $0.00002 $0.00135

Measured 1mo ago against content hash b26f5b5c4f17, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 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.

skills/software-dev/systematic-debugging/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Systematic Debugging

Part of Agent Skills™ by googleadsagent.ai™

Description

Systematic Debugging replaces trial-and-error fixes with a disciplined four-phase root cause analysis process. The agent reproduces the bug reliably, generates ranked hypotheses, tests each hypothesis with minimal instrumentation, and applies a targeted fix with defense-in-depth hardening. No fix is applied without first understanding why the bug exists.

Agents are prone to "shotgun debugging"—changing multiple things simultaneously and hoping the problem disappears. This skill enforces scientific rigor: one variable at a time, observable evidence at each step, and a clear causal chain from root cause to fix. The agent must articulate the root cause in plain language before writing any corrective code.

After the immediate fix, the agent applies defense-in-depth: adding assertions, input validation, or monitoring that would catch the same class of bug in the future. The debugging session concludes with a post-mortem note documenting the root cause, the fix, and the preventive measures added.

Use When

  • A test fails unexpectedly or intermittently
  • A user reports a bug with a stack trace or reproduction steps
  • Code behaves differently in production than in development
  • An error message is unclear or misleading
  • Multiple potential causes exist and guessing would waste time
  • A previous fix attempt did not resolve the issue

How It Works

graph TD
    A[Bug Report] --> B[Phase 1: Reproduce]
    B --> C{Reproducible?}
    C -->|No| D[Gather More Context]
    D --> B
    C -->|Yes| E[Phase 2: Hypothesize]
    E --> F[Rank Hypotheses by Likelihood]
    F --> G[Phase 3: Test Top Hypothesis]
    G --> H{Root Cause Found?}
    H -->|No| I[Eliminate Hypothesis]
    I --> F
    H -->|Yes| J[Phase 4: Fix + Harden]
    J --> K[Write Regression Test]
    K --> L[Apply Defense-in-Depth]
    L --> M[Document Post-Mortem]

Read the full file on GitHub · 140 lines

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. 1mo ago First seen · 140 lines · 24 tokens per session scan A b26f5b5c4f17

Subscribe to this mod's changes

systematic-debugging is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (44 stars, last pushed 6mo ago), licensed MIT. It adds 24 tokens to every session and 1,353 once invoked, about $0.0001 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.

Related

Other skills, from other repositories

incident-postmortem

Close the learning loop after a rescue or incident — reconstruct the timeline from actionlog, run root-cause analysis (platform / site / measurement / external), produce a structured postmortem document, distill reusable insights via /learn, and propose preventive guardrails. Use after a /rescue, a CPA spike, a…

logly/mureo · 150 tokens

ai-hive-a2a-cancel-handoff-check

A verification workflow for tasks handed from one AI agent to another using A2A, a protocol for agent-to-agent communication. It checks remote status, task identifiers, handoff outputs, and cancellation results.

wubin1836/ai-hive-agent-skills · 166 tokens

ai-hive-agents-api-session-recovery

A design guide for recovering long-running hosted-agent sessions, their execution events, and result files after interruptions.

wubin1836/ai-hive-agent-skills · 143 tokens

ga4-debugging-validation

This skill should be used when the user asks to "debug GA4 tracking", "validate tag implementation", "use DebugView", or mentions "data quality checks", "GA4 audit", or "event tracking not working". Do NOT use for: e-commerce event setup (use ga4-ecommerce-setup), BigQuery data analysis (use ga4-bigquery-export).

Ad-Superpowers/ad-superpowers-plugin · 81 tokens

linkedin-performance-troubleshooter

This skill should be used when the user asks to "fix LinkedIn ad performance", "diagnose high LinkedIn CPL", "fix LinkedIn ads not spending", or mentions "LinkedIn low engagement", "LinkedIn performance drop", or "reduce LinkedIn ad costs". Do NOT use for: LinkedIn bid strategy selection (use…

Ad-Superpowers/ad-superpowers-plugin · 109 tokens

gtm-container-auditor

This skill should be used when the user asks to "audit my GTM container", "find duplicate tags", "clean up Tag Manager", mentions "GTM health check", "unused tags and triggers", or "consent compliance of tags". Do NOT use for: server-side tracking or CAPI implementation (use first-party-data-strategy), attribution…

Ad-Superpowers/ad-superpowers-plugin · 98 tokens