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.
npx skills add JayRHa/AgentSkills --skill debug-detectivegit clone --depth 1 https://github.com/JayRHa/AgentSkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jayrha/agentskills/debug-detective)<a href="https://agentmods.dev/skills/jayrha/agentskills/debug-detective"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/debug-detective/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jayrha/agentskills/debug-detective"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/debug-detective.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00153 | $0.01814 |
| Opus 5.5 | $0.00061 | $0.00726 |
| Sonnet 5.5 | $0.00031 | $0.00363 |
| Haiku 4.5 | $0.00015 | $0.00181 |
Grade A, and why
debug-detective 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Detective
Overview
Debugging fails when it becomes random poking — changing lines, re-running, hoping. This skill enforces a scientific, evidence-first process: you never change code to "see what happens" until you have a falsifiable hypothesis backed by an observation. The goal is to find the root cause, not to make the symptom disappear.
Keywords: debug, root cause, bug, regression, crash, stack trace, flaky test, intermittent, heisenbug, deadlock, memory leak, race condition, bisect, repro, reproduce, isolate, hypothesis, works on my machine.
Core principle: A bug you cannot reproduce is a bug you cannot confirm fixed. Spend your effort earning a reliable reproduction first; everything else gets faster after that.
Workflow
Follow these phases in order. Do not skip ahead — a fix found by skipping is usually a coincidence, not a cure.
1. Capture & Reproduce
- Collect the exact symptom: error message, stack trace, wrong vs. expected output, exit code, screenshot, logs.
- Record the environment: OS, runtime/language version, dependency versions, config, env vars, data, concurrency, time/locale.
- Build a minimal reliable reproduction — the smallest command/input that triggers the bug. Note how often it fails (100%? 1 in 20?).
- If it is intermittent, quantify the rate and try to raise it (loop it, add load, shrink timeouts) before proceeding. See
references/intermittent-bugs.md. - Gate: Do not continue until you can trigger the bug on demand (or have a measured failure rate). Write the repro down.
2. Isolate
- Shrink the surface area. Remove inputs, disable features, stub dependencies until the bug still reproduces with the least machinery. (Delta-debugging mindset.)
- Establish the boundary: which layer/module/function is the last place behavior is correct, and the first place it is wrong?
- Add observation points (logging, breakpoints, assertions,
printof invariants) — observe, don't fix.
3. Hypothesize
- State a single, falsifiable hypothesis: "The crash happens because
usersisNonewhen the cache misses." A good hypothesis predicts an observation you haven't made yet. - Rank candidate hypotheses by likelihood × cheapness-to-test. Test the cheapest discriminating one first.
- For each, write the prediction before you run the experiment. See
references/hypothesis-log.mdfor the format and usetemplates/investigation-log.mdto track them.
What ships with it
7 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.
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.
- 1mo ago First seen · 95 lines · 153 tokens per session scan A d6d3e806d94d
debug-detective is a skill published in the GitHub repository JayRHa/AgentSkills (12 stars, last pushed 2mo ago), licensed MIT. It adds 153 tokens to every session and 1,814 once invoked, about $0.0006 per session on Opus 5.5. 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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