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.
git clone --depth 1 https://github.com/Goldziher/ai-rulezWrote 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/commands/goldziher/ai-rulez/explain-error)<a href="https://agentmods.dev/commands/goldziher/ai-rulez/explain-error"><img src="https://agentmods.dev/badge/commands/goldziher/ai-rulez/explain-error/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/commands/goldziher/ai-rulez/explain-error"><img src="https://agentmods.dev/badge/commands/goldziher/ai-rulez/explain-error.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 | $0.00015 | $0.00112 |
| Opus 5.5 | $0.00006 | $0.00045 |
| Sonnet 5.5 | $0.00003 | $0.00022 |
| Haiku 4.5 | $0.00002 | $0.00011 |
Grade A, and why
explain-error 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 today.
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.
What it actually says
Explain error
- Read the last 200 lines of
$ARGUMENTS. - Find the first line containing
ERRORorTraceback. - Explain the error in two sentences and name the most likely cause.
- Propose one next step the user can run.
Done when the explanation and the next step are written. If the file has no error line, say so and stop.
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.
- today First seen · 14 lines · 15 tokens per session scan A c23f6469d28d
explain-error is a command published in the GitHub repository Goldziher/ai-rulez (163 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 112 once invoked, about $0.0001 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 2026-10-17.
Other commands, from other repositories
agent-brain-graph
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local
Command "local" from getsentry/toolkit, covering examples, start the server and tail events (default), run your app with the local server auto-enabled, use a custom port and only show errors and logs (filter out transactions).
poly-check
Lint and check formatting with poly — apply no fixes; summarize findings and drift.
debug-files
Command "debug-files" from getsentry/toolkit, covering examples, inspect a debug information file (auto-detects the format), bundle jvm sources with a debug id, exclude additional directories and output as json.
fix-issues
Pick up one approved task, implement the fix, and close it.
speckit.md-doctor.drift
Re-evaluate since the last run: compute the git/.memsearch/TDD delta, re-score previously graded files in light of what changed, and report which past suggestions were resolved or are now stale/false.