systematic-debugging

A step-by-step method for investigating bugs, failed tests, and unexpected software behaviour. TDD means test-driven development, where tests help guide implementation, but this guide focuses on finding the underlying cause first.

In plain words
What is it for?
Use it to read error details, reproduce failures, map affected code, investigate the root cause, and only then propose a fix.
Why use it?
It reduces wasted effort from quick patches that hide the real problem or create new ones.

Skill for Claude CodeCodex

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 skills/dr-code/tessera/systematic-debugging
Any agent
npx skills add dr-code/tessera --skill systematic-debugging
Clone the repo
git clone --depth 1 https://github.com/dr-code/tessera

Made for: Claude Code, Codex.

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 968 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 $0.00021 $0.00968
Opus 5 $0.00010 $0.00484
Sonnet 5 $0.00004 $0.00194
Haiku 4.5 $0.00002 $0.00097

Measured yesterday against content hash 645865319a9b, 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.

skills/systematic-debugging/SKILL.md · 112 lines

How it starts

The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Systematic Debugging

Overview

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Core principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.

Violating the letter of this process is violating the spirit of debugging.

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If you haven't completed Phase 1, you cannot propose fixes.

Tessera: Map Blast Radius First

Before starting Phase 1 — if tessera MCP is configured in this session:

1. graph_continue (mandatory first call)
2. graph_impact(changed_files=["<file where bug was reported>"])

graph_impact shows which other files depend on the broken code. This tells you:

  • How far a fix might ripple
  • Which tests are likely affected
  • Whether this is a leaf-level bug or a core abstraction issue

Surface this impact map before investigating root cause.

The Four Phases

You MUST complete each phase before proceeding to the next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

  1. Read error messages carefully — stack traces, line numbers, error codes
  2. Reproduce consistently — can you trigger it reliably every time?
  3. Check recent changes — git diff, recent commits, new dependencies
  4. Gather evidence in multi-component systems
    • Add diagnostic logging at each component boundary
    • Run once to gather evidence showing WHERE it breaks
    • Then analyze to identify the failing component
  5. Trace data flow — where does the bad value originate? Trace backward through the call stack

Phase 2: Pattern Analysis

  1. Find working examples — use graph_retrieve(query="<working component similar to broken one>") if tessera MCP is configured to find similar code in the codebase
  2. Read the reference — use graph_read to read the working implementation completely, not just skim
  3. Identify differences — list every difference, however small
  4. Understand dependencies — what settings, config, environment does this need?

Read the full file on GitHub · 112 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. yesterday First seen · 112 lines · 21 tokens per session scan A 645865319a9b

Subscribe to this mod's changes

systematic-debugging is a skill published in the GitHub repository dr-code/tessera (1 stars, last pushed 21d ago), licensed MIT. It adds 21 tokens to every session and 968 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 2026-08-31.

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