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Found 44 Skills
Use when creating, writing, or refining a bug report for a FOLIO project. Produces structured bug tickets with a clear summary, preconditions, numbered steps to reproduce, expected vs. actual results, and supporting evidence (logs, stack traces, screenshots). Also use when asked to file a defect, triage an issue, or prepare a bug for Jira. Optionally interacts with the user to gather missing context and can create the ticket via the Jira MCP integration.
Plans real-user QA deliverables: personas, journey maps, exploratory charters, persona/journey/tour/CFR test cases, regression suites, Figma validation checks, automation intent, and user-impact bug reports. Writes artifacts under <qa-output-path>/qa/ for qa-execution to consume. Use when planning QA before execution, documenting journey-driven test strategy, marking flows that need E2E follow-up, or filing structured bug reports. Do not use for live execution, AI implementation audits, CI gate ownership, or technical integration/security/performance suites; use qa-execution or agent-output-audit instead.
Guides QA engineers through daily testing activities—morning review, test case creation, automation, exploratory testing, bug reporting, and end-of-day wrap-up. Use when planning or executing day-to-day testing or when the user asks about daily testing workflow.
Report a bug in the compound-engineering plugin
Use this skill when the user wants to create a new issue, report a bug, submit a feature request, or discuss a requirement before implementation. "create issue", "report bug", "create-issue", "submit issue", "新建 issue", "提需求", "提 bug". Requires Gitee MCP Server to be configured.
Execute YAML test plan, stop on first failure, output rich debug prompt
Analyze GitHub issue content, assess its priority, identify missing information, and provide clear reproduction steps or triage advice. Trigger when the user asks to triage an issue, analyze a bug report, or asks 'how should I respond to this issue'.
Issue Workflow Stage 1 — Convert the user's problem into a reproducible, traceable {slug}-report.md through conversation. The AI only asks "what you saw, how to reproduce it, what should happen" here, and does not guess the root cause for the user (that's Stage 2's responsibility). Meanwhile, this stage is the only official decision point for choosing between the fast track and standard path: Based on the user's description, first review the relevant code; if the root cause can be identified at a glance and the required changes are minor, directly inform the user to take the fast track. Trigger scenarios: The user says "file an issue", "record this bug", "I found a problem". This is the starting point of the issue workflow with no pre-dependencies.