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 ivy00johns/Skill-Madness --skill diagnose-loopgit clone --depth 1 https://github.com/ivy00johns/Skill-MadnessWrote 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/ivy00johns/skill-madness/diagnose-loop)<a href="https://agentmods.dev/skills/ivy00johns/skill-madness/diagnose-loop"><img src="https://agentmods.dev/badge/skills/ivy00johns/skill-madness/diagnose-loop.svg" alt="Measured on agentmods" 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 | $0.00125 | $0.01591 |
| Opus 5 | $0.00063 | $0.00796 |
| Sonnet 5 | $0.00025 | $0.00318 |
| Haiku 4.5 | $0.00013 | $0.00159 |
Grade A, and why
diagnose-loop 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
3. **`curl` / HTTP request that reproduces** — for API and webhook bugs; capture as a shell script so it replays in one line. How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Diagnose Loop
Tradeoff caveat. This skill biases toward thoroughness over speed. For trivial bugs with obvious causes (typos, off-by-one, a missing import the stack trace already points at), skip phases and just fix it. For everything else — flaky tests, performance regressions, "it works on my machine," intermittent failures, anything you've stared at for more than 15 minutes — the discipline is the point. Adapted from mattpocock's
diagnosepattern.
diagnose-loop vs systematic-debugging. The plugin skill
superpowers:systematic-debuggingis the general "form a hypothesis before you touch a fix" discipline for any bug or unexpected behavior. Reach fordiagnose-loop(this skill) specifically when the payoff is in building a fast, deterministic, binary feedback loop first — flaky tests, performance regressions, hard-to-reproduce or intermittent failures. For a straightforward bug where you just need disciplined hypothesizing,superpowers:systematic-debuggingis the lighter fit.
Phase 1 — Build a feedback loop (THE SKILL)
Spend disproportionate effort here. Be aggressive. Be creative. Refuse to give up.
Every later phase mechanically consumes Phase 1's output. A fast deterministic loop turns hypothesizing into a binary search; a slow or noisy loop turns it into guessing. Building the loop is the work — the rest is bookkeeping.
A good loop has three properties: it runs in seconds, it returns a binary pass/fail signal, and it fails for the same reason every time. Optimize for those before doing anything else.
Ten ranked ways to construct a loop
In order of cost — pick the cheapest one that actually reproduces the bug.
- Existing failing test — cheapest possible signal; the harness already exists.
- New failing test that captures the bug — write the assertion, watch it fail, then start.
curl/ HTTP request that reproduces — for API and webhook bugs; capture as a shell script so it replays in one line.- CLI command +
diffagainst known-good output — golden-file testing for any tool that emits text. - Headless browser script (Playwright/Puppeteer) for UI bugs — compose with the
playwrightskill. - Trace/log replay — when the bug only happens in production, dump the request and replay it locally.
- Throwaway harness script in the repo's language — a 20-line file that imports the buggy module and exercises it directly.
- Property-based / fuzz test — when the bug is data-dependent and you don't yet know which input triggers it.
git bisect— when the bug is recent and a known-good commit exists; the loop is the bisect script.- Differential testing against a reference implementation — for parser, compiler, or protocol bugs where "correct" is defined elsewhere.
What ships with it
3 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.
- 8d ago First seen · 87 lines · 125 tokens per session scan A fc9b5acbb2d7
diagnose-loop is a skill published in the GitHub repository ivy00johns/Skill-Madness (11 stars, last pushed today), licensed MIT. It adds 125 tokens to every session and 1,591 once invoked, about $0.0006 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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