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| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | 2x 2x 2x 2x 2x | import { calculateDependencyHealth, ToolName } from '@aiready/core';
import type { ToolScoringOutput } from '@aiready/core';
import type { DepsReport } from './types';
/**
* Convert dependency health report into a ToolScoringOutput.
*/
export function calculateDepsScore(report: DepsReport): ToolScoringOutput {
const { rawData, summary } = report;
// Recalculate using core math to get risk contribution breakdown
const riskResult = calculateDependencyHealth({
totalPackages: rawData.totalPackages,
outdatedPackages: rawData.outdatedPackages,
deprecatedPackages: rawData.deprecatedPackages,
trainingCutoffSkew: rawData.trainingCutoffSkew,
});
const factors: ToolScoringOutput['factors'] = [
{
name: 'Outdated Packages',
impact: -Math.min(
30,
(rawData.outdatedPackages / Math.max(1, rawData.totalPackages)) *
100 *
0.3
),
description: `${rawData.outdatedPackages} outdated packages`,
},
{
name: 'Deprecated Packages',
impact: -Math.min(
40,
(rawData.deprecatedPackages / Math.max(1, rawData.totalPackages)) *
100 *
0.4
),
description: `${rawData.deprecatedPackages} deprecated packages`,
},
{
name: 'Training Cutoff Skew',
impact: -Math.min(30, rawData.trainingCutoffSkew * 100 * 0.3),
description: `Training cutoff skew of ${rawData.trainingCutoffSkew.toFixed(1)} years`,
},
];
const recommendations: ToolScoringOutput['recommendations'] =
riskResult.recommendations.map((rec) => ({
action: rec,
estimatedImpact: 6,
priority: summary.score < 50 ? 'high' : 'medium',
}));
return {
toolName: ToolName.DependencyHealth,
score: summary.score,
rawMetrics: {
...rawData,
rating: summary.rating,
},
factors,
recommendations,
};
}
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