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Found 170 Skills
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Write a structured incident postmortem or post-incident review. Use when asked to write a postmortem, incident report, P1/P2 review, outage report, or RCA (root cause analysis). Generates a blameless postmortem with timeline, root cause, contributing factors, impact summary, and action items.
[Fix & Debug] ⚡⚡ Fix a GitHub issue with systematic debugging
Diagnose pytest or CI failures, identify root cause, and implement the minimal fix. Use when tests fail or CI reports errors.
Structured multi-step reasoning via Sequential Thinking MCP. Use for complex debugging, architectural trade-offs, or root cause analysis.
Copilot agent that assists with bug investigation, root cause analysis, and fix generation for efficient debugging and issue resolution Trigger terms: bug fix, debug, troubleshoot, root cause analysis, error investigation, fix bug, resolve issue, error analysis, stack trace Use when: User requests involve bug hunter tasks.
Collaboration workflow for GitHub Issue handling. Used when users receive an issue that needs analysis and response. Through the four-step process of "Diagnosis → Qualification → Decision → Response", produce accurate root cause analysis and appropriate user responses from an issue, avoiding misjudgment of problem types or unprofessional responses.
Debugging and Root Cause Localization for AscendC Operator Precision Issues. Used when operator precision tests fail (such as allclose failure, result deviation, all-zero/NaN output, etc.). Process: Error Distribution Analysis → Code Error-Prone Point Review → Experimental Isolation → printf/DumpTensor Instrumentation → Fix Verification. Keywords: precision debugging, precision issue, result inconsistency, error localization, allclose failure, output deviation, NaN, all-zero, precision debug.
Systematic Fishbone analysis exploring problem causes across six categories
Use when diagnosing unexpected behavior, failed workflows, bugs, browser or Node.js runtime issues, logs, traces, or when preparing a root-cause hypothesis. 诊断异常、定位 bug、判断修复方向时使用：先建立证据表，区分运行时事实和代码推断，避免多层猜测；证据不足时添加 copy-friendly 浏览器日志或本地 Node.js JSONL 日志。
Compares two `tuist generate` runs to identify cache hit rate changes and root-cause analysis of cache invalidation. Can be invoked with generation IDs, dashboard URLs, or branch names.
Hypothesis-driven debugging with ranked hypotheses, git bisect strategy, instrumentation planning, and minimal reproduction design. Triggers on: "debug this systematically", "root cause analysis", "bisect this bug", "rank hypotheses", "isolate this issue", "minimal reproduction". NOT for general reasoning.