check-coverage — for Claude Code check-coverage, databao-cli, community, for Claude Code, ide skills, agentic-analytics, analytics, business-intelligence, businessintelligence, context

v1.0.0
GitHub

이 스킬 정보

적합한 상황: Ideal for AI agents that need run make test-cov-check. 현지화된 요약: # Check Coverage Steps Run make test-cov-check If tests pass and coverage = 80%, done. It covers agentic-analytics, analytics, business-intelligence workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

기능

Run make test-cov-check
If tests pass and coverage = 80%, done.
Existing tests broke : fix production code, not tests.
New tests fail : fix the test.
Ambiguous : read test intent. If behavior intentionally changed, update

# Core Topics

for Claude Code agentic-analytics analytics business-intelligence businessintelligence context
JetBrains JetBrains
[19]
[4]
Updated: 4/2/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
30
Canonical Locale
en
Detected Body Locale
en

적합한 상황: Ideal for AI agents that need run make test-cov-check. 현지화된 요약: # Check Coverage Steps Run make test-cov-check If tests pass and coverage = 80%, done. It covers agentic-analytics, analytics, business-intelligence workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

이 스킬을 사용하는 이유

추천 설명: check-coverage helps agents run make test-cov-check. Check Coverage Steps Run make test-cov-check If tests pass and coverage = 80%, done. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

최적의 용도

적합한 상황: Ideal for AI agents that need run make test-cov-check.

↓ 실행 가능한 사용 사례 for check-coverage

사용 사례: Applying Run make test-cov-check
사용 사례: Applying If tests pass and coverage = 80%, done
사용 사례: Applying Existing tests broke : fix production code, not tests

! 보안 및 제한 사항

  • 제한 사항: New code you just wrote (must have tests).
  • 제한 사항: Do NOT: add trivial tests just to raise numbers, add # pragma: no cover
  • 제한 사항: Prioritize: New code you just wrote (must have tests)

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Install Path

Start With Installation And Validation

If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Trusted Recheck

Cross-Check Against Trusted Picks

If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Workflow

Move To Workflow Collections For Team Rollout

When the goal shifts from a single skill to team handoff, approvals, and repeatable execution, move into workflow collections.
Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is check-coverage?

적합한 상황: Ideal for AI agents that need run make test-cov-check. 현지화된 요약: # Check Coverage Steps Run make test-cov-check If tests pass and coverage = 80%, done. It covers agentic-analytics, analytics, business-intelligence workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install check-coverage?

Run the command: npx killer-skills add JetBrains/databao-cli/check-coverage. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for check-coverage?

Key use cases include: 사용 사례: Applying Run make test-cov-check, 사용 사례: Applying If tests pass and coverage = 80%, done, 사용 사례: Applying Existing tests broke : fix production code, not tests.

Which IDEs are compatible with check-coverage?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for check-coverage?

제한 사항: New code you just wrote (must have tests).. 제한 사항: Do NOT: add trivial tests just to raise numbers, add # pragma: no cover. 제한 사항: Prioritize: New code you just wrote (must have tests).

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add JetBrains/databao-cli/check-coverage. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use check-coverage immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

check-coverage

Install check-coverage, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Check Coverage

Steps

1. Run make test-cov-check

If tests pass and coverage >= 80%, done.

2. If tests fail

  • Existing tests broke: fix production code, not tests.
  • New tests fail: fix the test.
  • Ambiguous: read test intent. If behavior intentionally changed, update test and document in commit message.

3. If coverage below 80%

Check "Missing" column. Prioritize:

  1. New code you just wrote (must have tests).
  2. Critical paths (error handling, validation, CLI logic).
  3. Utility functions with clear contracts.

Do NOT: add trivial tests just to raise numbers, add # pragma: no cover without justification, or test third-party/Streamlit internals.

4. Write tests

Add to tests/test_<module>.py. Use project_layout fixture when needed. One behavior per test function.

5. Re-run make test-cov-check

Repeat until threshold met.

6. HTML report (optional)

make test-cov -- opens htmlcov/index.html.

Failure handling

  • Missing pytest-cov: run uv sync --dev.
  • Uncoverable lines (platform-specific, external calls): add # pragma: no cover with reason, note in commit message.

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