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 agentmods add skills/latestaiagents/agent-skills/error-pattern-analyzernpx skills add latestaiagents/agent-skills --skill error-pattern-analyzergit clone --depth 1 https://github.com/latestaiagents/agent-skillsWrote 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/latestaiagents/agent-skills/error-pattern-analyzer)<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/error-pattern-analyzer"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/error-pattern-analyzer.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 | $0.00051 | $0.02422 |
| Opus 5 | $0.00026 | $0.01211 |
| Sonnet 5 | $0.00010 | $0.00484 |
| Haiku 4.5 | $0.00005 | $0.00242 |
Grade A, and why
error-pattern-analyzer 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 3d 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 — 382 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Error Pattern Analyzer
Identify recurring error patterns and systemic issues in your codebase.
When to Use
- Same errors appearing repeatedly
- Investigating production incidents
- Prioritizing bug fixes
- Finding root causes
- Analyzing error trends
Error Classification
By Frequency
| Category | Frequency | Priority |
|---|---|---|
| Critical | >100/hour | P0 - Immediate |
| High | 10-100/hour | P1 - Same day |
| Medium | 1-10/hour | P2 - This week |
| Low | <1/hour | P3 - Backlog |
By Impact
interface ErrorImpact {
affectedUsers: number;
revenue: 'blocking' | 'degraded' | 'none';
dataIntegrity: 'at_risk' | 'safe';
cascading: boolean; // Does it cause other failures?
}
Pattern Detection Workflow
Step 1: Collect Error Data
interface ErrorRecord {
timestamp: Date;
errorType: string;
message: string;
stackTrace: string;
context: {
userId?: string;
endpoint?: string;
input?: unknown;
environment: string;
};
metadata: Record<string, unknown>;
}
// Aggregate errors over time window
async function collectErrors(
timeRange: { start: Date; end: Date }
): Promise<ErrorRecord[]> {
return errorStore.query({
timestamp: { $gte: timeRange.start, $lte: timeRange.end }
});
}
Step 2: Group by Similarity
function groupErrors(errors: ErrorRecord[]): ErrorGroup[] {
const groups = new Map<string, ErrorRecord[]>();
for (const error of errors) {
// Create fingerprint from error type + normalized message
const fingerprint = createFingerprint(error);
const existing = groups.get(fingerprint) || [];
existing.push(error);
groups.set(fingerprint, existing);
}
return Array.from(groups.entries()).map(([fp, errs]) => ({
fingerprint: fp,
count: errs.length,
firstSeen: errs[0].timestamp,
lastSeen: errs[errs.length - 1].timestamp,
sample: errs[0],
affectedUsers: new Set(errs.map(e => e.context.userId)).size
}));
}
function createFingerprint(error: ErrorRecord): string {
// Normalize message (remove variable parts)
const normalizedMessage = error.message
.replace(/\b[0-9a-f]{8,}\b/gi, '<ID>') // UUIDs, hashes
.replace(/\d{4}-\d{2}-\d{2}/g, '<DATE>') // Dates
.replace(/\d+/g, '<N>'); // Numbers
// Use first meaningful stack frame
const keyFrame = extractKeyFrame(error.stackTrace);
return `${error.errorType}:${normalizedMessage}:${keyFrame}`;
}
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.
- 3d ago First seen · 382 lines · 51 tokens per session scan A 73678d77ffe0
error-pattern-analyzer is a skill published in the GitHub repository latestaiagents/agent-skills (5 stars, last pushed 4mo ago), licensed MIT. It adds 51 tokens to every session and 2,422 once invoked, about $0.0003 per session on Opus 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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