debugging-patterns

A set of debugging methods for finding the underlying cause of a software problem. It uses logs, error details, code history, and known error patterns as evidence.

In plain words
What is it for?
Investigating errors, comparing changes with git history, checking for issues such as race conditions or configuration mistakes, and judging confidence in a diagnosis.
Why use it?
It helps avoid guessing at fixes when a build, test, or program fails unexpectedly.

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/a5c-ai/babysitter/debugging-patterns
Any agent
npx skills add a5c-ai/babysitter --skill debugging-patterns
Clone the repo
git clone --depth 1 https://github.com/a5c-ai/babysitter

Made for: Claude Code, Codex.

Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 305 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 $0.00027 $0.00305
Opus 5 $0.00014 $0.00152
Sonnet 5 $0.00005 $0.00061
Haiku 4.5 $0.00003 $0.00030

Measured 2d ago against content hash c8751c88ff32, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

debugging-patterns 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 2d 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.

library/methodologies/cc10x/skills/debugging-patterns/SKILL.md · 42 lines

What it actually says

Pattern-Based Diagnosis

  • Check patterns.md for known gotchas matching the error
  • Cross-reference with common patterns: null pointer, race condition, resource leak, config error
  • Rate root cause confidence (>=80% to proceed with fix)

Evidence Collection

  • Stack traces with full call chain
  • Error messages with context
  • Exit codes from reproduction attempts
  • Git blame/log for change correlation
  • Environment differences (if applicable)

When to Use

  • During DEBUG workflow investigation phase
  • When BUILD tests fail unexpectedly
  • When reviewing error handling gaps

Agents Used

  • bug-investigator (primary consumer)
  • silent-failure-hunter (pattern reference)
Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 42 lines · 27 tokens per session scan A c8751c88ff32

Subscribe to this mod's changes

debugging-patterns is a skill published in the GitHub repository a5c-ai/babysitter (1,757 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 305 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 2026-08-30.

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