Borrowing it
Nothing to install: this file belongs to Nnnsightnnn/claudekit. 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/Nnnsightnnn/claudekit/main/.claude/skills/ai-error-learner/SKILL.mdgit clone --depth 1 https://github.com/Nnnsightnnn/claudekitWrote 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/nnnsightnnn/claudekit/ai-error-learner)<a href="https://agentmods.dev/skills/nnnsightnnn/claudekit/ai-error-learner"><img src="https://agentmods.dev/badge/skills/nnnsightnnn/claudekit/ai-error-learner/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/nnnsightnnn/claudekit/ai-error-learner"><img src="https://agentmods.dev/badge/skills/nnnsightnnn/claudekit/ai-error-learner.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 | $0.00033 | $0.04913 |
| Opus 5.5 | $0.00013 | $0.01965 |
| Sonnet 5.5 | $0.00007 | $0.00983 |
| Haiku 4.5 | $0.00003 | $0.00491 |
Grade A, and why
AI Error Learner 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- The number is NOT preceded within 30 characters by one of: `HTTP`, `Status`, `Response`, `code`, `curl`, `fetch`, `GET`, `POST`, `PUT`, `DELETE` The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 358 lines · 33 tokens per session scan A 270db2ab8bb6
AI Error Learner is a skill published in the GitHub repository Nnnsightnnn/claudekit (2 stars, last pushed 4mo ago), with no licence file. It adds 33 tokens to every session and 4,913 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 2026-08-31.
Other skills, from other repositories
five-whys
Finds the root cause of a bug, failure or recurring problem by asking "why" until the answer is a cause you can fix. Use when the user asks why something keeps happening, or wants the root cause rather than a quick fix.
check-cache-bugs
Audit Claude Code setup for cache bugs (CC#40524): sentinel, --resume/--continue, attribution header + ArkNill B3/B4/B5.
sandbox-unblock
Diagnostic protocol to run before reporting a sandbox blocker or asking for a configuration change. Eleven checks that eliminate false positives, then a report template the person holding the settings can act on. On one measured day, six of eight reported blockers turned out to be false, all from the same handful of…
investigate
Systematic root-cause debugging: find the cause before writing any fix.
qa
Systematic QA testing of a web application: diff-aware, tiered, with fix-and-verify loop.
optimize
Analyze and suggest performance improvements for code, queries, or systems.