AI Slop Code Risk Monitor

cucumber/godog

SlopCodeMonitor badge for cucumber/godog Adjusted legacy signal; badge bands: 25 / 50 / 75 (different from dashboard bands).

Cucumber for golang

1.4 Low pattern signal View on GitHub

Open-Source Code Quality, Security and Technical Debt Review

This report summarizes scanner evidence for cucumber/godog, a Go project with 2,690 GitHub stars. SynthScan examined 17,142 lines of code across 112 source files, recording 21 pattern matches distributed across 2 syntactic categories. The legacy adjusted pattern signal is 1.4 (Low pattern signal); it is not an authorship estimate.

Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.

1.4
Adjusted Signal
1.4
Raw Pattern Score
100%
Time Factor
2026-10-23
Last Push
2.7K
Stars
Go
Language
17.1K
Lines of Code
112
Files
21
Pattern Hits
2026-10-31
Scan Date
0.00
HC Hit Rate

Risk Review · Payload v1

Use each vector to guide manual verification of the underlying findings.

Payload schema: 1.0.0 · Engine: 2.0.0 · Scoring: heuristic-density-v1 · Scan date: 2026-10-31.

Cognitive Ownership Risk 6.6/100 · LOW

Can maintainers explain intent, assumptions, and trade-offs? 21 finding(s).

Hallucinated Dependency & Supply Chain Risk 0.0/100 · LOW

Are imports declared and package/API names verified? 0 finding(s).

Agent Over-Engineering Ratio 0.0/100 · LOW

Are wrappers, guards, and repeated structures necessary? 0 finding(s).

PR Review Velocity Impact 5.9/100 · LOW

Which changes need focused human review? 21 finding(s).

What These Metrics Mean

Adjusted Signal
Legacy pattern score normalized per 1,000 scanned lines and multiplied by the repository-level time factor. It is not an estimate of AI authorship.
Raw Pattern Score
Sum of severity- and context-weighted pattern findings before applying the time factor.
Time Factor
A coarse multiplier based on repository last-push metadata. It does not identify when individual code was written.
Pattern Hits
Count of configured pattern findings. Review each location and surrounding code before acting.
HC Hit Rate
High- and critical-severity findings per scanned file. Severity is a configured detector weight, not proof of a vulnerability or authorship.
Lines / Files
Scan coverage denominators used by the legacy normalized score.

Pattern-Signal History

This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.

Severity Breakdown

Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.

CRITICAL 0HIGH 0MEDIUM 0LOW 21

Directory Score Breakdown

This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.

Pattern Findings

The scanner identified 21 distinct pattern matches across 2 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.

Over-Commented Block16 hits · 16 pts
SeverityFileLineSnippetContext
LOWrun.go321 TestSuiteInitializer func(*TestSuiteContext)COMMENT
LOWstacktrace.go41 fn := runtime.FuncForPC(f.pc())COMMENT
LOWoptions.go1package godogCOMMENT
LOWtest_context.go21// Scenario represents the executed scenarioCOMMENT
LOWtest_context.go41type Steps []stringCOMMENT
LOWtest_context.go61//COMMENT
LOWtest_context.go101// is passed to all functions (contexts), whichCOMMENT
LOWtest_context.go141 return StepContext(ctx)COMMENT
LOWtest_context.go201func (ctx ScenarioContext) BeforeStep(fn func(st *Step)) {COMMENT
LOWtest_context.go221 ctx.StepContext().After(func(ctx context.Context, st *Step, status StepResultStatus, err error) (context.Context, errorCOMMENT
LOWtest_context.go241// - float32, float64COMMENT
LOWtest_context.go261// will only be matched if the step starts with "Given". "And"COMMENT
LOWtest_context.go361// package with standard go test command.COMMENT
LOWtestingt.go21 // Name returns the name of the current pickle under testCOMMENT
LOWinternal/flags/options.go21 // Randomize, if not `0`, will be used to run scenarios in a random order.COMMENT
LOWinternal/builder/builder.go81// it simply builds a godog executable to scan features.COMMENT
Structural Annotation Overuse5 hits · 8 pts
SeverityFileLineSnippetContext
LOWREADME.md66#### Step 1 - Setup a go moduleCOMMENT
LOWREADME.md74#### Step 2 - Create gherkin featureCOMMENT
LOWREADME.md94#### Step 3 - Create godog step definitionsCOMMENT
LOWREADME.md152#### Step 4 - Create the main program to testCOMMENT
LOWREADME.md177#### Step 5 - Add some logic to the step definitionsCOMMENT