Borrowing it
Nothing to install: this file belongs to getappz/agentflare. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/getappz/agentflare/master/.claude/skills/systematic-debugging/SKILL.mdgit clone --depth 1 https://github.com/getappz/agentflareWrote 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/getappz/agentflare/systematic-debugging)<a href="https://agentmods.dev/skills/getappz/agentflare/systematic-debugging"><img src="https://agentmods.dev/badge/skills/getappz/agentflare/systematic-debugging/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/getappz/agentflare/systematic-debugging"><img src="https://agentmods.dev/badge/skills/getappz/agentflare/systematic-debugging.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 | $0.00070 | $0.01135 |
| Opus 5.5 | $0.00028 | $0.00454 |
| Sonnet 5.5 | $0.00014 | $0.00227 |
| Haiku 4.5 | $0.00007 | $0.00113 |
Grade A, and why
systematic-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 2mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
The Iron Law
NO FIX WITHOUT ROOT-CAUSE INVESTIGATION FIRST
A fix proposed before Phase 1 is complete is a guess, not a fix. Guesses that happen to work are indistinguishable from guesses that don't until the bug resurfaces somewhere else.
When to use
Any technical issue: a failing test, a production bug, unexpected output, a performance regression, a build failure, an integration that doesn't behave as documented.
Especially when under time pressure, when "just one quick change" seems obvious, or when a previous fix attempt didn't work — those are exactly the conditions where guessing feels fastest and costs the most.
Don't skip because the bug looks simple. Simple bugs have root causes too, and finding one usually takes minutes, not hours.
Phase 1: Root-cause investigation
Before touching any code:
- Read the actual error. Full stack trace, not the first line. Note exact file paths, line numbers, and error codes — they often name the fix directly.
- Reproduce it. Confirm exact, repeatable steps. If it won't reproduce reliably, that's information — gather more data (logging, a tighter repro case) rather than guessing at a fix for a moving target.
- Check recent changes.
git log/git diffon the affected paths, recent dependency bumps, config or environment drift. Most bugs are introduced by something that changed, not something that was always broken. - Trace the data flow backward. Find where the bad value or bad state actually originates, not just where it's first observed. Follow it through each call/component boundary until you reach the source, and fix there — not at the symptom.
Phase 2: Pattern analysis
If a working example exists (a similar endpoint, a sibling test, a reference implementation), read it completely before comparing — skimming guarantees you miss the difference that matters:
- Locate the closest working analog in the same codebase.
- Read it in full, not just the parts that look relevant.
- List every difference from the broken code, however small. Don't discard one because "that can't matter" — verify it doesn't.
- Note what the working version depends on (config, environment, call order) that the broken version might be missing.
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.
- 2mo ago First seen · 110 lines · 70 tokens per session scan A 3ee1632cf55a
systematic-debugging is a skill published in the GitHub repository getappz/agentflare (2 stars, last pushed today), licensed Apache-2.0. It adds 70 tokens to every session and 1,135 once invoked, about $0.0003 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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