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 cosmix/loom --skill loom-debugginggit clone --depth 1 https://github.com/cosmix/loomWrote 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/cosmix/loom/loom-debugging)<a href="https://agentmods.dev/skills/cosmix/loom/loom-debugging"><img src="https://agentmods.dev/badge/skills/cosmix/loom/loom-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/cosmix/loom/loom-debugging"><img src="https://agentmods.dev/badge/skills/cosmix/loom/loom-debugging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.03332 |
| Opus 5.5 | $0.00010 | $0.01333 |
| Sonnet 5.5 | $0.00005 | $0.00666 |
| Haiku 4.5 | $0.00002 | $0.00333 |
Grade A, and why
loom-debugging 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
tcpdump -i any port 8080 # wire-level; curl -v for HTTP How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging
Overview
Find the true cause of a defect and prevent its recurrence — across app code, tests, data pipelines, ML, and infra. The failure mode to avoid is symptom-patching: changing code until the symptom disappears without understanding why, which moves the bug rather than fixing it.
The Root-Cause Loop
Run this loop; don't skip steps. Most wasted time comes from hypothesizing before reproducing, or fixing before localizing.
- Reproduce — deterministically. If you can't reproduce it, you can't verify a fix. Capture exact inputs, env, versions, and the full error/stack. For intermittent bugs, first make it more frequent (loop it, add load, shrink timeouts) before anything else.
- Minimize — shrink to the smallest input/code that still fails. Delete half, re-run, repeat (delta-debugging). A 5-line repro localizes faster than a 5000-line one and often reveals the cause outright.
- Localize — bound where it happens before asking why. Bisect in space (comment out / binary-search modules) and in time (
git bisect). Read the stack trace top frame first, then the first frame in your code. - Hypothesize — state a specific, falsifiable cause ("X is null because Y returns None when Z"). Vague hypotheses ("something with async") aren't testable.
- Test the hypothesis — one variable at a time; change something that should confirm/refute it. If the experiment can't distinguish two causes, design a better one.
- Fix — the root cause, minimally. Verify the repro now passes AND that you understand why the fix works (else you may have masked it).
- Prevent — add a regression test that fails without the fix. No regression test = the bug is not done. Then generalize: are there sibling instances of the same class elsewhere?
Core Discipline
- Reproduce before fixing. Never "fix" what you can't observe failing.
- Read the error fully — message, type, and every stack frame. The answer is often literally in it (wrong frame, unexpected value, swallowed cause).
- Check recent changes. Most new failures are recently introduced →
git log,git bisect. - Question your assumptions. The bug lives in what you're sure is correct. Verify it (print it, assert it) rather than believing it.
- Preserve evidence. Save the failing input, logs, core dump, and seed before you start mutating code.
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 Changed · -33 tokens per session c71aea981c2a
- 1mo ago First seen · 232 lines · 57 tokens per session scan A 75b2248e8b1e
loom-debugging is a skill published in the GitHub repository cosmix/loom (62 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 3,332 once invoked, about $0.0001 per session on Opus 5.5. 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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