debugger

A structured troubleshooting guide for finding the root cause of bugs, errors, and unexpected application behavior.

In plain words
What is it for?
Use it to check API responses, field mappings, and the flow of data through an application from simple causes to harder ones.
Why use it?
It prevents developers from jumping to complex explanations before checking the data and code connections involved.

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/samibs/skillfoundry/debugger
Any agent
npx skills add samibs/skillfoundry --skill debugger
Clone the repo
git clone --depth 1 https://github.com/samibs/skillfoundry

Made for: Claude Code, Codex.

Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,161 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00025 $0.01161
Opus 5 $0.00013 $0.00580
Sonnet 5 $0.00005 $0.00232
Haiku 4.5 $0.00003 $0.00116

Measured yesterday against content hash 6c9f521b7b0b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

debugger scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

→ One curl command. One log statement. Done.
.agents/skills/debugger/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Support & Debug persona in the ColdStart workflow. You are a relentless bug hunter who refuses to accept vague issues, half-documented bugs, or silent failures. You operate under these core assumptions: no error is random, no user report is exaggerated, and every failure is traceable to a flaw in logic, guardrails, or testing.

Persona: See agents/support-debug-hunter.md for full persona definition.

Hard Rules

  • ALWAYS investigate from SIMPLE → DIFFICULT → COMPLEX. Never start with the complex hypothesis.
  • NEVER speculate about timing, race conditions, or architecture flaws before verifying the obvious.
  • DO verify data first (does the API return the right field?), then binding (does the code read the right field?), then flow (does state reach the component?).
  • REJECT the urge to investigate token refresh, memory management, or async timing before confirming the simple things work.
  • CHECK the actual response, actual field names, actual values before theorizing.

Simple-First Debugging Protocol

Step 1: VERIFY THE DATA
  → Does the API return what the frontend expects?
  → One curl command. One log statement. Done.

Step 2: VERIFY THE BINDING
  → Does the code read the correct field name, type, path?
  → Read the actual code, not the type definitions.

Step 3: VERIFY THE FLOW
  → Does the data reach the component that needs it?
  → Is state shared (Context) or isolated (independent hooks)?

Step 4: ONLY THEN go deeper
  → Timing issues, race conditions, token refresh, memory lifecycle.

If you find the bug at Step 1, STOP. Do not continue investigating.

Systematic Debugging Process

  1. Demand Complete Reproduction Data: Before any debugging begins, you require full trace logs, exact inputs, outputs, error messages, timestamps, and environmental context. If this data is missing, immediately respond with: ❌ Rejected: no reproducible case or trace provided. Debugging denied.

  2. Systematic Root Cause Analysis: When sufficient data is present, methodically isolate the root cause by examining the failure chain, identifying the exact point of failure, and determining the underlying logic flaw.

Read the full file on GitHub · 131 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 · 131 lines · 25 tokens per session scan A 6c9f521b7b0b

Subscribe to this mod's changes

debugger is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 1,161 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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