debugging

A step-by-step method for debugging software by finding the original cause of an error before changing code.

In plain words
What is it for?
Investigating failing tests or commands, tracing incorrect values through a codebase, comparing working and broken implementations, and verifying a fix.
Why use it?
It reduces guesswork and repeated fixes by using error details, reproduction steps, data tracing, working examples, and focused tests.

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/dineshdb/pie/debugging
Any agent
npx skills add dineshdb/pie --skill debugging
Clone the repo
git clone --depth 1 https://github.com/dineshdb/pie

Made for: Claude Code, Codex.

Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 496 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 $0.00015 $0.00496
Opus 5 $0.00008 $0.00248
Sonnet 5 $0.00003 $0.00099
Haiku 4.5 $0.00002 $0.00050

Measured yesterday against content hash 9175187dd1a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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.

.pie/skills/debugging/SKILL.md · 71 lines

What it actually says

Debugging

Iron Law: NO FIXES WITHOUT ROOT CAUSE INVESTIGATION.

Phase 1: Root Cause

Before any fix:

  1. Read error completely — stack traces, line numbers, error codes
  2. Reproduce consistently — exact steps to trigger
  3. Check recent changesgit diff, new deps, config changes
  4. Trace data flow — where does the bad value originate?

Multi-component tracing:

# Trace a value through the stack
grep -rn "VARIABLE_NAME" src/
git log --oneline -10  # recent changes
git diff HEAD~3 -- src/module/  # what changed recently

Stack trace when lost:

import traceback; traceback.print_stack()
# or in Rust: println!("{:?}", std::backtrace::Backtrace::capture());

Phase 2: Pattern Analysis

  1. Find working examples in codebase: grep -rn "working_pattern" src/
  2. Read reference implementation completely
  3. Identify ALL differences between working and broken
  4. Understand dependencies and assumptions

Phase 3: Hypothesis

  1. State: "I think X is root cause because Y"
  2. Make SMALLEST possible change
  3. Test ONE variable at a time
  4. If 3+ fixes failed → question architecture

Phase 4: Implement + Defense-in-Depth

  1. Create failing test case
  2. Implement single fix (no "while I'm here" changes)
  3. Verify fix works using verification skill
  4. Add validation at every layer:
Layer Purpose
Entry Reject invalid input at boundary
Business Logic Ensure data makes sense for operation
Environment Prevent dangerous operations in context
Debug Capture context for forensics

Red Flags — STOP

  • "Quick fix for now"
  • "Just try changing X"
  • "Add multiple changes at once"
  • "I don't fully understand but this might work"
  • One more fix (when 2+ already failed)

All mean: Return to Phase 1. If 3+ failed → question architecture.

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 · 71 lines · 15 tokens per session scan A 9175187dd1a1

Subscribe to this mod's changes

debugging is a skill published in the GitHub repository dineshdb/pie (2 stars, last pushed 3mo ago), licensed MIT. It adds 15 tokens to every session and 496 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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