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Found 38 Skills
Capture Fusion skill workflow failure context and guide a draft-first bug reporting flow with explicit confirmation before any GitHub mutation.
Generate comprehensive test plans, test cases, regression test suites, automation annotations, and bug reports for QA engineers. Includes Figma MCP integration for design validation. Use when planning QA before execution, documenting test strategies, marking which flows require E2E follow-up, or creating structured bug reports. Do not use for executing tests against a live repository or running verification gates — use qa-execution for that.
Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
Expert in quality assurance and testing. Responsible for bug detection, edge case validation, test planning, and automated test creation to ensure software reliability.
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.
Phase 1 of the Issue Workflow - Translate 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 Phase 2's responsibility). This phase is also the only official decision point for determining whether to take the fast track or the standard path: first read the relevant code based on the user's description, and if the root cause can be identified at a glance and the changes required are minor, directly inform the user to take the fast track. Trigger scenarios: The user says "file an issue", "log this bug", "I found a problem". This is the starting point of the issue workflow with no pre-requisites.
Files structured GitHub bug reports for agent-validator when users ask to file, report, or open an issue for a suspected defect
Report a bug in the compound-engineering plugin
Execute YAML test plan, stop on first failure, output rich debug prompt
This skill should be used when a QA engineer wants to test or verify a completed task, run through acceptance criteria, check Gherkin scenarios against the implementation, record pass/fail results, or sign off on a ticket before merge. Triggers on phrases like "verify task
This skill should be used when a developer or QA engineer wants to report a bug, create a bug ticket, document a test failure, log a defect, file an issue found during a QA session, or report something that is broken — for example "report a bug", "create a bug ticket", "I found a defect", "something is broken in task
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.