AGENT SKILL

file-test-bug

File a GitHub issue for local integration test failures. TRIGGERS: file test bug, report test failure, create bug for test, integration test failed, test failure issue, junit failure

使用场景测试与质量
License 许可
MIT
最近更新
2026-11-12
Stars
★ 263
Forks
225

01 前言 Front Matter

name
file-test-bug
license
MIT
metadata
{ "author": "Microsoft", "version": "1.0.0" }
description
File a GitHub issue for local integration test failures. TRIGGERS: file test bug, report test failure, create bug for test, integration test failed, test failure issue, junit failure

03 SKILL.md 正文

File Test Bug

Creates a GitHub issue in microsoft/github-copilot-for-azure for integration test failures.

Input

  • Skill name (required): e.g., azure-ai, appinsights-instrumentation
  • Test run (optional): Timestamp of test run. Defaults to most recent with logs for the skill.

Steps

  1. Ask user for skill name if not provided
  2. Parse tests/reports/junit.xml for failures matching the skill
  3. Find test run directory (specified or most recent with matching logs)
  4. Read agent-metadata.md from tests/reports/test-run-<timestamp>/<skillname>-<testname>/
  5. For each failure, read the actual line of code from the test file using the location (file:line) from junit.xml
  6. REQUIRED - Write diagnosis BEFORE creating issue:
    • Analyze the agent-metadata.md to understand what the agent did
    • Compare agent behavior to what the test expected (from the assertion)
    • Identify the root cause (skill issue, test issue, or model behavior)
    • Write 2-3 sentences per failed test explaining WHY it failed
    • Suggest potential fixes (update skill, update test, or update fixtures)
  7. Create issue via github-mcp-server-create_issue:
owner: microsoft
repo: github-copilot-for-azure
title: Integration test failure in <skill-name>
labels: ["bug", "integration-test"]
body: |
  ## Failed Tests
  - <test-name>: <error message>
  
  ## Diagnosis
  
  ### Root Cause
  <1-2 sentences explaining WHY the test failed based on agent-metadata.md analysis>
  
  ### Analysis per Test
  - **<test-name>**: <what agent did vs what test expected>
  
  ### Suggested Fix
  <one of: update skill, update test assertions, provide test fixtures>

  ## Details
  ### <test-name>
  **Error:** <failure from junit.xml>
  **Location:** <file:line>
  ```typescript
  <actual line of code from the test file at the specified line number>

<details> <summary>agent-metadata.md</summary>

<full contents of agent-metadata.md file, verbatim>

</details>


## Important

Include the **complete, unmodified contents** of each `agent-metadata.md` file in the issue body. Do NOT summarize or truncate the logs. Wrap each log in a `<details>` block with the test name as the summary.

04 同仓库更多 Skills

microsoft
microsoft/GitHub-Copilot-for-Azure

azure-advisor-cost-optimization

Analyze Azure Advisor Cost/IdleResources findings and prevalidate deletion safety, including Service Groups. WHEN: "find unused Azure resources", "what resources am I paying for but no longer using", "idle-resource savings", "historical idle-resource savings", "are these idle resources safe to delete". Generic Cost, other subcategories, and cross-category requests use azure-advisor.

★ 263
microsoft
microsoft/GitHub-Copilot-for-Azure

foundry-iq

Foundry IQ knowledge bases. WHEN: make local or Blob documents searchable; create/diagnose KBs; triage unsupported connectors or multi-source KB creation/reconfiguration (even with classic-search terms); connect existing KB to agents (including multi-source KBs); create/reuse a Search service; retrieve from an existing knowledge base with citations; no brand words needed. Read its procedure before query/target questions. NOT: other KB providers, repository-file search, classic Azure AI Search index/query/app work with no Foundry IQ KB or connector request, generic agent creation.

Skill与智能体开发
★ 263
microsoft
microsoft/GitHub-Copilot-for-Azure

python-appservice-deploy

Deploy Python (Flask/Django/FastAPI) code to Azure App Service Linux. WHEN: "Flask App Service", "Django App Service", "FastAPI App Service", "deploy Python to App Service". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform/Bicep/IaC, full infra — use azure-prepare.

运维与部署
★ 263
microsoft
microsoft/GitHub-Copilot-for-Azure

preset

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

运维与部署Skill与智能体开发
★ 263
microsoft
microsoft/GitHub-Copilot-for-Azure

customize

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).

Skill与智能体开发
★ 263
microsoft
microsoft/GitHub-Copilot-for-Azure

capacity

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

★ 263