interactive-debugging

A workflow for debugging problems that only become clear while an application is running. It uses temporary instrumentation, reproduction, logs, and verification to investigate timing, state, browser, and event-order issues.

In plain words
What is it for?
Use it to investigate intermittent failures, async timeouts, incorrect state, client behavior, or event-order bugs by collecting runtime data and then removing the temporary debugging setup.
Why use it?
Static code inspection may not reveal what happened during a timeout, race condition, or stale update. Runtime evidence helps confirm the cause before changing the code.

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

Made for: Claude Code, Codex.

Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,323 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 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 $0.00097 $0.01323
Opus 5 $0.00048 $0.00661
Sonnet 5 $0.00019 $0.00265
Haiku 4.5 $0.00010 $0.00132

Measured 2d ago against content hash 8aea6b6e7efe, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

interactive-debugging scanned grade B with 2 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.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/debug_server.js, scripts/debug_server.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

fetch("http://localhost:3333/debug", { method: "POST",

Makes network callslowCapability

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

- Verify it with `curl http://localhost:3333/health`.
skills/interactive-debugging/SKILL.md · 152 lines

How it starts

The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interactive Debugging

Use this skill to run a debug loop: hypothesize, instrument, reproduce, inspect runtime logs, fix, verify, and clean up.

Required Paths

  • Debug server: .debug/debug_server.*
  • Debug log: .debug/debug.log
  • Default endpoint: http://localhost:3333/debug

The bundled servers in this skill's scripts/ directory (next to this SKILL.md, not in the project being debugged) are intentionally thin. They accept POST /debug, append the raw request body to .debug/debug.log with a timestamp, and return ok.

Steps

Step 1: Understand the Bug

  • Read the relevant code before changing anything.
  • State 1-3 concrete hypotheses that runtime data can prove or disprove.
  • Do not jump to a fix before collecting data unless the cause is already proven.

Step 2: Create the Debug Server

  • Create .debug/ in the project under debug.
  • Copy the matching bundled server from this skill's scripts/ directory to .debug/debug_server.js or .debug/debug_server.py in the project.
  • For another language, create the smallest equivalent server at .debug/debug_server.<ext>.
  • Keep the server thin: no schemas, dashboards, persistence, extra routes, or broad utilities.

Step 3: Start the Debug Server

Run it from the project root:

node .debug/debug_server.js 3333
python3 .debug/debug_server.py 3333
  • The server is a long-running foreground process; start it in the background (or another terminal) so it does not block your shell.
  • Use another port only if 3333 is occupied.
  • Verify it with curl http://localhost:3333/health.
  • Clear .debug/debug.log before reproduction if it already exists.

Step 4: Instrument the Code

  • Add the fewest probes needed to test the hypotheses.
  • Wrap every probe or probe block in matching debug region markers:
// #region DEBUG
fetch("http://localhost:3333/debug", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    event: "function-entry",
    traceId,
    value,
  }),
}).catch(() => {});
// #endregion DEBUG

Read the full file on GitHub · 152 lines

Files

What ships with it

5 files 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 · 152 lines · 97 tokens per session scan B 8aea6b6e7efe

Subscribe to this mod's changes

interactive-debugging is a skill published in the GitHub repository denysdovhan/agents (17 stars, last pushed 1mo ago), licensed MIT. It adds 97 tokens to every session and 1,323 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, 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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