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debug-error
Systematically debug and resolve errors using structured hypothesis-driven investigation
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Systematically debug and resolve errors using structured hypothesis-driven investigation
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
PR-focused code review with structured checklist, severity ratings, and actionable feedback
Use when a code review finding needs proof — write a focused test in JavaScript or Go that either confirms the issue is real or exposes it as over-engineering hyperbole. Trigger after code-review or code-review-skill findings are presented and evidence is requested.
Use when reviewing Dependabot alerts, npm audit findings, govulncheck output, or CVE reports on a JavaScript/Node.js or Go project — especially when triaging multiple alerts across direct and transitive dependencies to assess real-world risk and produce a remediation plan.
Produce data-driven software delivery estimates by analyzing historical JIRA tickets, git activity, and engineer track records, then matching the new work against the most similar past tickets. Use this skill whenever the user asks "how long will this take", wants to estimate a piece of work, scope an epic, plan a sprint, or estimate delivery for JIRA stories or a Figma design. Also use whenever the user wants developer-to-work assignment recommendations based on history, wants to optimize an estimate by adding or reallocating engineers, or asks "what's the fastest way to ship this" or "who should work on this". Especially trigger when the user provides JIRA ticket IDs, JIRA story links, or Figma designs together with any indication of a team that will execute the work.
Use when auditing an existing test suite for quality and coverage gaps, evaluating Playwright migration readiness, scoring automation against a world-class e-commerce standard, or guiding the creation of new tests. Applicable to Selenium, WebdriverIO, and Playwright suites.
AI-powered observability with Grafana MCP — translates natural language to metrics, logs, and trace queries to diagnose issues like a senior SRE
| name | debug-error |
| description | Systematically debug and resolve errors using structured hypothesis-driven investigation |
Systematically debug and resolve errors using structured, hypothesis-driven investigation.
Follow this methodology to debug: $ARGUMENTS
git log -10 --oneline -- <file> and git diff on relevant files.Based on the evidence, form ranked hypotheses about the root cause. Common causes to consider:
package.json, requirements.txt, lock files).