error-detective
Diagnose Errors Across Logs and Code
Distributed errors are difficult to trace across noisy logs, stack traces, deployments, and service boundaries. This skill organizes evidence into timelines, correlations, root-cause hypotheses, fixes, and recurrence monitoring.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "error-detective" from https://skillstore.io/skills/sickn33-error-detective.md and its manifest at https://skillstore.io/api/skills/sickn33-error-detective/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "error-detective". A checkout service shows timeout spikes five minutes after a payment deployment.
Expected outcome:
Timeline: Timeouts begin five minutes after the payment deployment and first appear in checkout calls to payment. Leading hypothesis: the deployment increased payment latency, exhausting checkout connections. Next steps: compare latency before and after deployment, inspect connection pool saturation, and test rollback impact.
Using "error-detective". A Python stack trace ends with a missing dictionary key after a configuration update.
Expected outcome:
Likely failure point: the configuration reader assumes the key always exists. Evidence: the exception follows a configuration change. Verify the deployed configuration, add validation, and monitor missing-key errors.
Using "error-detective". Several services report authentication failures, but only one region shows a sharp increase.
Expected outcome:
Pattern: failures are regional rather than system-wide. Leading hypothesis: the affected region has stale credentials or configuration. Compare secret versions, deployment state, and identity-provider responses across regions.
Security Audit
SafeThe only static finding is a false positive: Markdown backticks identify a referenced file and do not execute a shell command. No prompt injection, data exfiltration intent, or other semantic security issue was found in SKILL.md.
Risk Factors
⚙️ External commands (1)
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<iframe src="https://skillstore.io/embed/skills/sickn33-error-detective.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
sickn33. (2026). error-detective security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-error-detective/audits/5BibTeX citation
@techreport{sickn33-sickn33-error-detective-2026,
author = {sickn33},
title = {error-detective security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-error-detective/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "error-detective security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-error-detective/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-error-detective:audit:5"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
sickn33-error-detective
2026-08-21
autumnsgrove-error-detective
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Investigate Production Incidents
Correlate service errors with deployments and time windows to identify likely causes and recovery actions.
Debug Application Failures
Analyze stack traces and nearby code to prioritize likely defect locations and verification steps.
Improve Error Monitoring
Turn recurring symptoms into extraction patterns, monitoring queries, and alerts that detect future failures.
Try These Prompts
Review these logs: [logs]. Identify recurring errors, summarize their frequency and timing, and list the three most likely causes.
Analyze this stack trace and related code: [stack trace and code]. Identify the likely failure point, explain the evidence, and propose verification steps.
Correlate these service logs and deployment events across [time window]. Build a timeline, identify cascading failures, and rank root-cause hypotheses by evidence.
Investigate [incident] using the provided logs, traces, metrics, code changes, and topology. Recommend immediate mitigation, durable fixes, and recurrence detection queries.
Best Practices
- Provide timestamps, service names, deployment events, and full stack traces when available.
- Separate observed evidence from hypotheses and assign each hypothesis a verification step.
- Validate proposed fixes in a safe environment and add monitoring for recurrence.
Avoid
- Do not infer a root cause from one error line without surrounding context.
- Do not expose secrets, tokens, personal data, or unrestricted production logs.
- Do not treat correlation as proof without testing alternative explanations.