chatcli: Skill for Claude Code

.agent/skills/systematic-debugging/SKILL.md

systematic-debugging is a skill for Claude Code from diillson/chatcli. It costs 25 tokens per session (610 once invoked), scanned A, a copy of systematic-debugging, Apache-2.0.

A four-phase method for debugging difficult software problems: reproduce the issue, isolate its source, understand the root cause, then fix and verify it. It uses written evidence and questions to guide the investigation.

In plain words
What is it for?
It is for investigating complex bugs, documenting reproduction steps, narrowing down recent changes, using root-cause questions such as the five whys, and checking fixes against regressions.
Why use it?
It reduces guesswork and helps prevent fixes that only hide the symptoms. The verification phase checks that the bug is gone and related behavior still works.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

This is diillson/chatcli's own configuration. It tells Claude Code how to work on chatcli itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything chatcli configures →

Reuse

Borrowing it

Nothing to install: this file belongs to diillson/chatcli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/diillson/chatcli/main/.agent/skills/systematic-debugging/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/diillson/chatcli

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/diillson/chatcli/systematic-debugging/github.svg)](https://agentmods.dev/skills/diillson/chatcli/systematic-debugging)
Your own site
<a href="https://agentmods.dev/skills/diillson/chatcli/systematic-debugging"><img src="https://agentmods.dev/badge/skills/diillson/chatcli/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/diillson/chatcli/systematic-debugging"><img src="https://agentmods.dev/badge/skills/diillson/chatcli/systematic-debugging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 610 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 89% copy Near-identical to another mod 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 $0.00025 $0.00610
Opus 5.5 $0.00010 $0.00244
Sonnet 5.5 $0.00005 $0.00122
Haiku 4.5 $0.00003 $0.00061

Measured 1mo ago against content hash 53b60eed01a4, 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.

Origin

This is a copy

89% identical to systematic-debugging — 2 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.

.agent/skills/systematic-debugging/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Systematic Debugging

Source: obra/superpowers

Overview

This skill provides a structured approach to debugging that prevents random guessing and ensures problems are properly understood before solving.

4-Phase Debugging Process

Phase 1: Reproduce

Before fixing, reliably reproduce the issue.

## Reproduction Steps
1. [Exact step to reproduce]
2. [Next step]
3. [Expected vs actual result]

## Reproduction Rate
- [ ] Always (100%)
- [ ] Often (50-90%)
- [ ] Sometimes (10-50%)
- [ ] Rare (<10%)

Phase 2: Isolate

Narrow down the source.

## Isolation Questions
- When did this start happening?
- What changed recently?
- Does it happen in all environments?
- Can we reproduce with minimal code?
- What's the smallest change that triggers it?

Phase 3: Understand

Find the root cause, not just symptoms.

## Root Cause Analysis
### The 5 Whys
1. Why: [First observation]
2. Why: [Deeper reason]
3. Why: [Still deeper]
4. Why: [Getting closer]
5. Why: [Root cause]

Phase 4: Fix & Verify

Fix and verify it's truly fixed.

## Fix Verification
- [ ] Bug no longer reproduces
- [ ] Related functionality still works
- [ ] No new issues introduced
- [ ] Test added to prevent regression

Debugging Checklist

## Before Starting
- [ ] Can reproduce consistently
- [ ] Have minimal reproduction case
- [ ] Understand expected behavior

## During Investigation
- [ ] Check recent changes (git log)
- [ ] Check logs for errors
- [ ] Add logging if needed
- [ ] Use debugger/breakpoints

## After Fix
- [ ] Root cause documented
- [ ] Fix verified
- [ ] Regression test added
- [ ] Similar code checked

Common Debugging Commands

# Recent changes
git log --oneline -20
git diff HEAD~5

# Search for pattern
grep -r "errorPattern" --include="*.ts"

# Check logs
pm2 logs app-name --err --lines 100

Anti-Patterns

❌ Random changes - "Maybe if I change this..." ❌ Ignoring evidence - "That can't be the cause" ❌ Assuming - "It must be X" without proof ❌ Not reproducing first - Fixing blindly ❌ Stopping at symptoms - Not finding root cause

Read the full file on GitHub · 110 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 · 110 lines · 25 tokens per session scan A 53b60eed01a4

Subscribe to this mod's changes

systematic-debugging is a skill published in the GitHub repository diillson/chatcli (93 stars, last pushed today), licensed Apache-2.0. It adds 25 tokens to every session and 610 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to systematic-debugging, differing in 2 lines, and is treated as a copy.

Related

Other skills, from other repositories

error-recovery

A guide to detecting and recovering from failures in long-running AI agents. It covers API outages, bad tool calls, broken conversation state, stalled streams, repeated loops, retries, fallback models, and circuit breakers that stop repeated failure.

bojieli/ai-agent-book · 111 tokens

coding-agent-harness

A guide to building the surrounding system that lets an AI agent safely work on code. This system provides tools, rules, tests, feedback, permissions, and ways to undo changes.

bojieli/ai-agent-book · 106 tokens

04-audit

Audit a codebase read-only across seven quality pillars into one ranked report. Use when the user wants to assess, health-check, or audit a codebase or one pillar. Not for fixing findings, reviewing a change, or checking a feature works.

ai-driven-dev/framework · 54 tokens

07-refactor

Improve code across four axes (cleanup, performance, security, architecture) by scanning and fixing, or applying a pushed audit report. Use when the user wants to refactor, optimize, harden, or remove code. Not for read-only diagnosis or adding tests.

ai-driven-dev/framework · 57 tokens

03-assert

Assert the work behaves by iterating the project's coding assertions until they pass, plus optional architecture and frontend facets. Use to validate an implementation. Not for reviewing or writing tests.

ai-driven-dev/framework · 39 tokens

08-debug

Reproduce and fix a known bug, or find an unknown root cause by hypothesis validation. Use when the user wants to fix a bug, find why something breaks, or reopen a stuck investigation. Not for building a feature or reviewing a diff.

ai-driven-dev/framework · 52 tokens