Agent Skills › dotnet/skills › crap-score

crap-score

GitHub

计算 .NET 代码的 CRAP 分数,结合圈复杂度与测试覆盖率识别高风险方法,辅助确定测试优先级和重构需求。

plugins/dotnet-test/skills/crap-score/SKILL.md dotnet/skills

Trigger Scenarios

查询特定方法、类或文件的 CRAP 分数 评估代码复杂度和覆盖率的综合风险 根据 CRAP 分数优先安排测试工作

Install

npx skills add dotnet/skills --skill crap-score -g -y
More Options

Non-standard path

npx skills add https://github.com/dotnet/skills/tree/main/plugins/dotnet-test/skills/crap-score -g -y

Use without installing

npx skills use dotnet/skills@crap-score

指定 Agent (Claude Code)

npx skills add dotnet/skills --skill crap-score -a claude-code -g -y

安装 repo 全部 skill

npx skills add dotnet/skills --all -g -y

预览 repo 内 skill

npx skills add dotnet/skills --list

SKILL.md

Frontmatter
{
    "name": "crap-score",
    "license": "MIT",
    "description": "Calculates CRAP (Change Risk Anti-Patterns) for a named .NET method, class, or file. USE FOR: explicit CRAP calculation or coverage-and-complexity risk within that named target, including which tests to prioritize. DO NOT USE FOR: project-wide coverage\/CRAP, plateaus, or project-wide blockers\/priorities (coverage-analysis); behavioral\/pseudo-mutation gaps (test-gap-analysis); writing tests; test runs without CRAP context.\n"
}

CRAP Score Analysis

Calculate CRAP (Change Risk Anti-Patterns) scores for .NET methods to identify code that is both complex and undertested.

Background

The CRAP score combines cyclomatic complexity and code coverage into a single metric:

$$\text{CRAP}(m) = \text{comp}(m)^2 \times (1 - \text{cov}(m))^3 + \text{comp}(m)$$

Where:

  • $\text{comp}(m)$ = cyclomatic complexity of method $m$
  • $\text{cov}(m)$ = code coverage ratio (0.0 to 1.0) of method $m$
CRAP Score Risk Level Interpretation
< 5 Low Simple and well-tested
5 to < 15 Moderate Acceptable for most code
15 to 30 High Needs more tests or simplification
> 30 Critical Refactor and add coverage urgently

A method with 100% coverage has CRAP = complexity (the minimum). A method with 0% coverage has CRAP = complexity^2 + complexity.

When to Use

  • User wants to assess which methods are risky due to low coverage and high complexity
  • User asks for CRAP score of specific methods, classes, or files
  • User wants to prioritize what to test next within a named method, class, or file based on coverage-and-complexity risk
  • User wants to evaluate test quality beyond simple coverage percentages

When Not to Use

  • User just wants to run tests (use run-tests skill)
  • User wants to write new tests (use code-testing-agent)
  • User only wants a coverage percentage without complexity analysis
  • User wants project-wide coverage/CRAP analysis or priorities (use coverage-analysis)

Inputs

Input Required Description
Target scope Yes Method name, class name, or file path to analyze
Test project path No Path to the test project. Defaults to discovering test projects in the solution.
Source project path No Path to the source project under analysis

Workflow

Step 1: Collect code coverage data

If the user supplies a valid Cobertura report that contains the requested target, use it directly and do not rerun tests. If the supplied report is malformed, empty, internally contradictory, or missing the target, treat it as failed input: regenerate it with a repository-compatible command when possible, or request a valid report when collection is unavailable. Otherwise invoke run-tests to classify the repository's test platform and confirm the compatible command shape, then require a command that emits Cobertura:

Coverage provider Cobertura command
coverlet.collector with VSTest dotnet test <test.csproj> --collect:"XPlat Code Coverage" --results-directory <results-dir>
Microsoft.Testing.Extensions.CodeCoverage with .NET 9 bridged MTP dotnet test <test.csproj> -- --coverage --coverage-output-format cobertura --coverage-output <output-path>
Microsoft.Testing.Extensions.CodeCoverage with .NET 10+ native MTP dotnet test --project <test.csproj> --coverage --coverage-output-format cobertura --coverage-output <output-path>

Use an equivalent repository-owned command when the project defines one. Search the results directory recursively when the collector creates a GUID subfolder. Do not substitute a generic binary .coverage command when no converter is available.

Do not stop at the first restore, compilation, test, or collector failure. Classify the failing layer, inspect every report the command emitted, and exhaust non-persistent retries before asking for input. Safe retries include command-line MSBuild properties that leave source and manifests unchanged and an already-installed or repository-provided alternative collector. A trivial source error is a collection blocker, not the final analysis, when a reversible command-line setting can compile the same source. Never call an empty Cobertura file a successful fallback.

For classic non-SDK projects (ToolsVersion, explicit compile items, or packages.config), use only a repository-provided coverage command that emits Cobertura. If none exists, request Cobertura XML and stop; do not migrate the project or inject an SDK-style provider. CRAP scores always require real coverage data.

Never estimate coverage

Guessed coverage produces wrong CRAP scores, which is worse than no answer. For a classic project with no repository coverage command or existing report, stop here and request Cobertura.

Do not add coverage packages, change project manifests, or install global tools unless the user explicitly authorized dependency/tooling changes. If the repository lacks a usable provider or converter, report that exact prerequisite and the compatible command shape identified through run-tests, then stop. If an existing binary .coverage report is present, convert it only with an already-installed or repository-provided converter; otherwise request authorization or a Cobertura export. If tests execute with failures but still emit valid coverage, continue with that data and note the failures. Report complexity on its own if useful, but never publish a CRAP number derived from assumed coverage.

Before using a report, verify that it parses, contains at least one class and method, and contains the requested target. An empty report or a report that omits the target is failed collection or filtering, not 0% coverage. Regenerate coverage when possible; otherwise stop without publishing a CRAP score.

If the user supplies an existing report, state that it was not regenerated. Do not describe its data as current unless its provenance is established by running the repository's coverage command in this analysis.

Step 2: Compute cyclomatic complexity

Prefer a machine-produced per-method complexity from a repository-provided code metrics report or from the Cobertura method's complexity attribute when that report maps to the current source. Microsoft.CodeAnalysis.Metrics can generate method-level CyclomaticComplexity data through msbuild /t:Metrics, but do not add the package or modify the project without user approval.

If no machine-produced metric exists, analyze the current target source and label the result as a manual complexity count. Count the following decision points (each adds 1 to the base complexity of 1):

Construct Example
if if (x > 0)
else if else if (y < 0)
case (each) case 1:
for for (int i = 0; ...)
foreach foreach (var item in list)
while while (running)
do...while do { } while (cond)
catch (each) catch (Exception ex)
&& if (a && b)
|| (OR) if (a || b)
?? value ?? fallback
?. obj?.Method()
? : (ternary) x > 0 ? a : b
Pattern match arm x is > 0 and < 10

Base complexity is 1 for every method. Each decision point adds 1.

When counting manually, read the source file, report the construct-by-construct breakdown, and do not use a source comment as evidence. Count every occurrence, including operators nested inside arguments or return expressions; before declaring a conflict, rescan specifically for &&, ||, ??, ?., ternaries, and switch/pattern arms. If a supplied report maps to the current method and a careful recount agrees, use its metric decisively. If a genuine disagreement remains, label both sources; when the user explicitly asked to use that report, calculate the primary CRAP result from its machine-produced metric and present the manual count as a caveat rather than withholding the requested result.

Step 3: Extract per-method coverage from Cobertura XML

Parse the Cobertura XML to find each method's line-rate attribute under the target <class> element. If line-rate is not available at method level, compute it from the <lines> elements:

$$\text{cov}(m) = \frac{\text{lines with hits} > 0}{\text{total lines}}$$

Method names in Cobertura may differ from source (async methods, lambdas). Match by line ranges when names don't align.

When both line-rate and <lines> exist, recompute the hit ratio and compare them. Allow only normal report rounding (one percentage point); if they differ more, the report contradicts itself. Regenerate it or report the conflict and stop without calculating CRAP. Never silently choose whichever value produces the expected score.

Step 4: Calculate CRAP scores

For each method in scope, apply the formula:

$$\text{CRAP}(m) = \text{comp}(m)^2 \times (1 - \text{cov}(m))^3 + \text{comp}(m)$$

Use a calculator or script for the arithmetic and show the substituted complexity and coverage. Do not calculate the formula mentally. Answer a named method directly; analyze unrelated methods only when the requested scope is a class or file. Once the requested result is established, do not append hypothetical refactor scores or coverage targets unless the user asked for them. Any numeric example must also come from the calculator or script.

Step 5: Present results

Present a sorted table (highest CRAP first):

| Method                          | Complexity | Coverage | CRAP Score | Risk     |
|---------------------------------|------------|----------|------------|----------|
| OrderService.ProcessOrder       | 10         | 45%      | 26.6       | High     |
| OrderService.ValidateItems      | 8          | 90%      | 8.1        | Moderate |
| OrderService.CalculateTotal     | 3          | 100%     | 3.0        | Low      |

Include:

  • Summary: total methods analyzed, how many in each risk category
  • Top offenders: methods with CRAP > 30, with specific recommendations
  • Quick wins: methods with high complexity but where small coverage improvements would drop the score significantly

Step 6: Provide actionable recommendations

For high-CRAP methods, suggest one or both:

  1. Add tests -- identify uncovered branches and suggest specific test cases
  2. Reduce complexity -- suggest extract-method refactoring for deeply nested logic

Calculate the coverage needed to bring a method below a CRAP threshold of 15:

$$\text{cov}_{\text{needed}} = 1 - \left(\frac{15 - \text{comp}}{\text{comp}^2}\right)^{1/3}$$

This formula only applies when comp < 15. When comp >= 15, the minimum possible CRAP score (at 100% coverage) is comp itself, which already meets or exceeds the threshold. In that case, coverage alone cannot bring the CRAP score below the threshold -- the method must be refactored to reduce its cyclomatic complexity first.

Report this as: "To bring ProcessOrder (complexity 10) below CRAP 15, increase coverage from 45% to more than 63.2% (at least 64% when reporting whole percentages)." For methods where complexity alone exceeds the threshold, report: "ComplexMethod (complexity 18) cannot reach CRAP < 15 through testing alone -- reduce complexity by extracting sub-methods."

Validation

  • Verify that coverage data was collected successfully (Cobertura XML exists and contains data)
  • Confirm the target method is present; absence is not evidence of 0% coverage
  • Confirm every coverage figure came from that XML — no estimated, assumed, or source-comment-derived values
  • Cross-check method line-rate against its line-hit ratio when both exist
  • Cross-check that method names in coverage data match the source code
  • Confirm CRAP scores with calculator or script output
  • Ensure a 100%-covered method's CRAP equals its complexity exactly

Common Pitfalls

  • Estimating coverage when collection fails: never do it — the resulting CRAP scores are wrong in the direction that matters. Use the repository-compatible Cobertura path confirmed through run-tests, then report the blocker instead.
  • Treating an empty report or missing method as 0% coverage: this is failed collection, filtering, or method mapping; do not manufacture a score.
  • Trusting contradictory Cobertura fields: compare line-rate with the line-hit ratio and stop if they disagree beyond rounding.
  • Trusting a stale complexity comment in the source: compute cyclomatic complexity from the current code; a // complexity: 7 comment left by a previous author is not evidence.
  • Mental CRAP arithmetic: use a calculator or script and show the substituted inputs.
  • Changing tooling to bypass a collector error: report the failed repository-compatible command and missing prerequisite; do not install a global collector or edit manifests without explicit authorization.
  • Stale coverage data: regenerate when the user asks for current results or the source/binaries changed; otherwise disclose that a supplied report was not regenerated.
  • Method name mismatches: Cobertura XML may use mangled/compiler-generated names for async methods, lambdas, or local functions. Match by line ranges when names don't align.
  • Generated code: Exclude auto-generated files (e.g., *.Designer.cs, *.g.cs) from analysis unless explicitly requested.

Version History

  • a55fbf4 Current 2026-09-27 19:26

    优化 GPT-5 提示词,改进路由逻辑以正确响应 CRAP 请求,并增强无效覆盖率报告的自动再生能力。

  • 949995c 2026-09-09 02:04

    增强CRAP评分可靠性:拒绝不完整的覆盖证据,优先使用测量的复杂度,并修正分数预期。

  • a3cb4a2 2026-08-27 16:17
  • 7953ba8 2026-08-14 01:14

    支持经典.NET测试项目(非SDK风格),包括packages.config依赖和显式编译项的处理。

  • ad0cfe8 2026-08-01 21:34
  • ce75c35 2026-07-06 00:32

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