systematic-debugging

systematic-debugging is an agent for coding agents from fabioc-aloha/Alex_Skill_Mall. It costs 28 tokens per session (368 once invoked), scanned A, original, MIT.

A step-by-step debugging process that reproduces a bug, traces its root cause, applies a focused fix, and adds a regression test—a test that prevents the same bug returning.

In plain words
What is it for?
Use it for unclear bugs, complex execution paths, race conditions, state problems, environment failures, or cases where the failing change is unknown.
Why use it?
It replaces guesswork with evidence and helps ensure that fixing one bug does not create another.

Agent

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.

agentmods
npx agentmods add agents/fabioc-aloha/alex_skill_mall/systematic-debugging
Clone the repo
git clone --depth 1 https://github.com/fabioc-aloha/Alex_Skill_Mall

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/agents/fabioc-aloha/alex_skill_mall/systematic-debugging.svg)](https://agentmods.dev/agents/fabioc-aloha/alex_skill_mall/systematic-debugging)
Your own site
<a href="https://agentmods.dev/agents/fabioc-aloha/alex_skill_mall/systematic-debugging"><img src="https://agentmods.dev/badge/agents/fabioc-aloha/alex_skill_mall/systematic-debugging.svg" alt="Measured on agentmods" height="20"></a>
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 368 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00028 $0.00368
Opus 5 $0.00014 $0.00184
Sonnet 5 $0.00006 $0.00074
Haiku 4.5 $0.00003 $0.00037

Measured yesterday against content hash 1106d19ed965, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 yesterday.

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.

plugins/code-quality/systematic-debugging/agents/systematic-debugging.agent.md · 51 lines

What it actually says

Systematic Debugging

Structured 4-phase debugging: problem assessment → root cause investigation → targeted fix → quality assurance with regression tests.

When to Use

  • Diagnosing a bug that isn't immediately obvious
  • Tracing through complex execution paths
  • When the failing commit is unknown (git bisect)
  • Debugging race conditions, state issues, or environment failures
  • Any bug where "just looking at it" hasn't worked

Phases

Phase 1: Problem Assessment

  • Gather context: errors, stack traces, reproduction steps, expected vs actual
  • Reproduce before fixing

Phase 2: Investigation

  • Trace execution path from entry to error
  • Check recent changes (git log --oneline -10 -- <file>)
  • Form hypotheses ranked by likelihood: data → logic → state → environment
  • Plan verification for each

Phase 3: Resolution

  • Targeted minimal fix addressing root cause
  • Follow existing patterns; add defensive programming
  • Verify: run tests, reproduce original, broader regression suite

Phase 4: Quality Assurance

  • Add regression test
  • Check for same pattern elsewhere
  • Report: Bug → Root Cause → Fix → Files → Test

Guidelines

  • Systematic: follow phases, don't jump to solutions
  • Simplest hypothesis first
  • Never fix without understanding root cause
  • Small testable changes over large refactors
  • Use git bisect for unknown failure commits

Source

Adapted from awesome-copilot/agents/debug.agent.md and awesome-claude-code-toolkit/plugins/bug-detective/.

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. yesterday First seen · 51 lines · 28 tokens per session scan A 1106d19ed965

Subscribe to this mod's changes

systematic-debugging is an agent published in the GitHub repository fabioc-aloha/Alex_Skill_Mall (4 stars, last pushed 3d ago), licensed MIT. It adds 28 tokens to every session and 368 once invoked, about $0.0001 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.

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