First detector of the 'is the config OPTIMAL?' axis (vs the existing 'correct?' scanners). New orchestrated scanner family CA-OPT (count 14->15), the deterministic half of the hybrid optimization lens. CA-OPT-001 (low, Missed opportunity): a multi-step procedure in CLAUDE.md (>=6 consecutive numbered steps) that belongs in a skill. Reads recommendation + provenance from the best-practices register (BP-MECH-003). Conservative by design; the negative corpus proves null false-positives. Prose-judgment cases (lifecycle->hook, 'never'->permission) are deferred to the Chunk 2b opus analyzer. Wiring mirrors OST: orchestrator entry, humanizer (OPT->'Missed opportunity' + family), scoring (OPT->'CLAUDE.md', existing area -> no new posture row -> byte-stable), strip-helper (OST,OPT), SC-5 regenerated under hermetic HOME (additive OPT entry only). 10 new tests; suite 1045->1055, self-audit A/A, readmeCheck passed (all verified with a clean HOME). Note: the pre-existing TOK test reads the real ~/.claude (non-hermetic) -> run the suite with a clean HOME for deterministic results. Tracked as a separate follow-up. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
406 lines
16 KiB
JavaScript
406 lines
16 KiB
JavaScript
/**
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* Scoring, maturity, and posture assessment for config-audit.
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* Zero external dependencies.
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*/
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import { gradeFromPassRate, WEIGHTS } from './severity.mjs';
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import { humanizeFinding } from './humanizer.mjs';
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/**
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* One-line plain-language context per overall grade. Used when a scorecard
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* is rendered with `options.humanized: true`.
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*/
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const GRADE_CONTEXT = {
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A: 'Healthy setup, only minor polish needed',
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B: 'Good shape — a few items to address',
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C: 'Some attention needed',
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D: 'Several issues — prioritize the urgent ones',
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F: 'Important issues need attention',
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};
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// --- Tier weights for utilization calculation ---
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const TIER_WEIGHTS = { t1: 3, t2: 2, t3: 1, t4: 1 };
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const TIER_COUNTS = { t1: 5, t2: 7, t3: 8, t4: 5 };
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const TOTAL_DIMENSIONS = 25;
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const MAX_WEIGHTED = Object.entries(TIER_COUNTS).reduce(
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(sum, [tier, count]) => sum + count * TIER_WEIGHTS[tier],
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0,
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); // 5*3 + 7*2 + 8*1 + 5*1 = 42
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/**
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* Calculate weighted utilization from GAP scanner findings.
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* @param {object[]} gapFindings - Array of GAP scanner findings (each has .category = t1|t2|t3|t4)
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* @param {number} [totalDimensions=25]
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* @returns {{ score: number, overhang: number }}
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*/
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export function calculateUtilization(gapFindings, totalDimensions = TOTAL_DIMENSIONS) {
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// Count gaps per tier
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const gapsByTier = { t1: 0, t2: 0, t3: 0, t4: 0 };
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for (const f of gapFindings) {
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const tier = f.category;
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if (tier in gapsByTier) gapsByTier[tier]++;
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}
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// Present (non-gap) weight
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let presentWeight = 0;
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for (const [tier, totalCount] of Object.entries(TIER_COUNTS)) {
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const presentCount = totalCount - gapsByTier[tier];
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presentWeight += presentCount * TIER_WEIGHTS[tier];
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}
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const score = Math.round((presentWeight / MAX_WEIGHTED) * 100);
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return { score, overhang: 100 - score };
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}
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// --- Maturity levels ---
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const MATURITY_LEVELS = [
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{ level: 0, name: 'Bare', description: 'No CLAUDE.md, default everything' },
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{ level: 1, name: 'Configured', description: 'CLAUDE.md + basic settings' },
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{ level: 2, name: 'Structured', description: 'Rules, skills, hooks' },
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{ level: 3, name: 'Automated', description: 'MCP, custom agents, diverse hooks' },
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{ level: 4, name: 'Governed', description: 'Plugins, managed settings, full monitoring' },
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];
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/**
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* Determine config maturity level (threshold-based: highest level where ALL requirements met).
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* @param {object[]} gapFindings - GAP scanner findings
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* @param {{ files: Array<{ type: string, absPath?: string, scope?: string }> }} discovery
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* @returns {{ level: number, name: string, description: string }}
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*/
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export function determineMaturityLevel(gapFindings, discovery) {
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const gapIds = new Set(gapFindings.map(f => {
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// Extract the gap check id from the title — match against known titles
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return findGapId(f);
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}));
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const has = (id) => !gapIds.has(id); // feature is present if NOT in gaps
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// Level 1: CLAUDE.md present
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if (!has('t1_1')) return MATURITY_LEVELS[0];
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// Level 2: Level 1 + permissions + hooks + (modular OR path-rules)
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const level2 = has('t1_2') && has('t1_3') && (has('t2_2') || has('t2_3'));
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if (!level2) return MATURITY_LEVELS[1];
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// Level 3: Level 2 + MCP + hook diversity + custom subagents
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const level3 = has('t1_5') && has('t2_5') && has('t2_6');
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if (!level3) return MATURITY_LEVELS[2];
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// Level 4: Level 3 + project MCP in git + custom plugin
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const level4 = has('t4_1') && has('t4_2');
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if (!level4) return MATURITY_LEVELS[3];
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return MATURITY_LEVELS[4];
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}
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/**
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* Map a GAP finding to its gap check ID based on known title→id mapping.
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* @param {object} finding
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* @returns {string}
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*/
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function findGapId(finding) {
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return TITLE_TO_ID[finding.title] || 'unknown';
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}
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/** Title→ID mapping for all 25 gap checks */
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const TITLE_TO_ID = {
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'No CLAUDE.md file': 't1_1',
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'No permissions configured': 't1_2',
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'No hooks configured': 't1_3',
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'No custom skills or commands': 't1_4',
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'No MCP servers configured': 't1_5',
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'Settings only at one scope': 't2_1',
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'CLAUDE.md not modular': 't2_2',
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'No path-scoped rules': 't2_3',
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'Auto-memory explicitly disabled': 't2_4',
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'Low hook diversity': 't2_5',
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'No custom subagents': 't2_6',
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'No model configuration': 't2_7',
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'No status line configured': 't3_1',
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'No custom keybindings': 't3_2',
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'Using default output style': 't3_3',
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'No worktree workflow': 't3_4',
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'No advanced skill frontmatter': 't3_5',
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'No subagent isolation': 't3_6',
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'No dynamic skill context': 't3_7',
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'No autoMode classifier': 't3_8',
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'No project .mcp.json in git': 't4_1',
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'No custom plugin': 't4_2',
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'Agent teams not enabled': 't4_3',
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'No managed settings': 't4_4',
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'No LSP plugins': 't4_5',
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};
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// --- Segments ---
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const SEGMENTS = [
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{ min: 81, segment: 'Top Performer', description: 'Exceptional configuration — leveraging most of Claude Code\'s capabilities' },
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{ min: 65, segment: 'Strong', description: 'Well-configured — using advanced features effectively' },
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{ min: 45, segment: 'Competent', description: 'Solid foundation — room to leverage more features' },
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{ min: 25, segment: 'Developing', description: 'Basic setup — significant features untapped' },
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{ min: 0, segment: 'Beginner', description: 'Minimal configuration — most capabilities unused' },
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];
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/**
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* Determine segment from utilization score.
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* @param {number} score - 0-100
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* @param {number} [_maturityLevel] - unused, kept for API compatibility
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* @returns {{ segment: string, description: string }}
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*/
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export function determineSegment(score, _maturityLevel) {
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for (const s of SEGMENTS) {
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if (score >= s.min) return { segment: s.segment, description: s.description };
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}
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return SEGMENTS[SEGMENTS.length - 1];
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}
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// --- Area scoring ---
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const SCANNER_AREA_MAP = {
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CML: 'CLAUDE.md',
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SET: 'Settings',
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HKV: 'Hooks',
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RUL: 'Rules',
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MCP: 'MCP',
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IMP: 'Imports',
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CNF: 'Conflicts',
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GAP: 'Feature Coverage',
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TOK: 'Token Efficiency',
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CPS: 'Token Efficiency',
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SKL: 'Token Efficiency',
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DIS: 'Settings',
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COL: 'Plugin Hygiene',
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OST: 'Settings',
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OPT: 'CLAUDE.md',
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};
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/**
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* Slugify an area name into a stable id.
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* Example: "Token Efficiency" → "token_efficiency", "CLAUDE.md" → "claude_md".
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*/
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function slugify(name) {
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return String(name).toLowerCase().replace(/[^a-z0-9]+/g, '_').replace(/^_+|_+$/g, '');
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}
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/**
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* Compute raw severity-weighted penalty from scanner counts.
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* Critical/high findings dominate; lows barely move the needle.
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* @param {{ critical?: number, high?: number, medium?: number, low?: number, info?: number }} counts
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* @returns {number}
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*/
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function severityPenalty(counts) {
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let penalty = 0;
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for (const [sev, weight] of Object.entries(WEIGHTS)) {
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penalty += (counts[sev] || 0) * weight;
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}
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return penalty;
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}
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/**
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* Score per config area from scanner results (v5: severity-weighted).
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* @param {object[]} scannerResults - Array of scanner result objects from envelope.scanners
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* @returns {{ areas: Array<{ id: string, name: string, grade: string, score: number, findingCount: number }>, overallGrade: string, scoringVersion: string }}
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*/
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export function scoreByArea(scannerResults) {
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// Group scanner results by area name so multiple scanners that share an area
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// (e.g. TOK + CPS both → "Token Efficiency") produce one combined row.
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const grouped = new Map();
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for (const result of scannerResults) {
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const name = SCANNER_AREA_MAP[result.scanner] || result.scanner;
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if (!grouped.has(name)) grouped.set(name, []);
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grouped.get(name).push(result);
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}
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const areas = [];
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for (const [name, results] of grouped) {
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const findings = results.flatMap(r => r.findings || []);
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const findingCount = findings.length;
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let score;
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if (results.some(r => r.scanner === 'GAP')) {
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// GAP scoring uses utilization, not severity penalty
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const util = calculateUtilization(findings);
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score = util.score;
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} else {
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// v5 severity-weighted: penalty proportional to a per-area budget.
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// Combine counts across all scanners contributing to this area.
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const counts = { critical: 0, high: 0, medium: 0, low: 0, info: 0 };
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for (const r of results) {
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for (const k of Object.keys(counts)) {
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counts[k] += (r.counts && r.counts[k]) || 0;
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}
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}
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const penalty = severityPenalty(counts);
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const maxBudget = Math.max(10, findingCount * 4);
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const passRate = Math.max(0, 100 - (penalty / maxBudget) * 100);
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score = Math.round(passRate);
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}
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const grade = gradeFromPassRate(score);
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areas.push({ id: slugify(name), name, grade, score, findingCount });
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}
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// Overall grade: quality areas only (exclude GAP — feature coverage is informational, not a quality issue)
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const qualityAreas = areas.filter(a => a.name !== 'Feature Coverage');
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const totalScore = qualityAreas.reduce((sum, a) => sum + a.score, 0);
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const avgScore = qualityAreas.length > 0 ? Math.round(totalScore / qualityAreas.length) : 0;
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const overallGrade = gradeFromPassRate(avgScore);
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return { areas, overallGrade, scoringVersion: 'v5' };
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}
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/**
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* Derive top 3 actions from GAP findings (T1 first, then T2).
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* @param {object[]} gapFindings
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* @param {object} [options]
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* @param {boolean} [options.humanized=false] - When true, return humanized
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* recommendations (looked up via humanizer translations).
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* @returns {string[]}
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*/
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export function topActions(gapFindings, options = {}) {
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const tierOrder = ['t1', 't2', 't3', 't4'];
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const sorted = [...gapFindings].sort(
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(a, b) => tierOrder.indexOf(a.category) - tierOrder.indexOf(b.category),
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);
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const top3 = sorted.slice(0, 3);
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if (options.humanized) {
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return top3.map(f => humanizeFinding(f).recommendation);
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}
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return top3.map(f => f.recommendation);
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}
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/**
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* Generate a terminal-friendly scorecard string (v2 format — kept for backward compat).
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* @param {{ areas: Array<{ name: string, grade: string, score: number }>, overallGrade: string }} areaScores
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* @param {{ score: number, overhang: number }} utilization
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* @param {{ level: number, name: string }} maturity
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* @param {{ segment: string }} segment
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* @param {string[]} actions
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* @returns {string}
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* @deprecated Use generateHealthScorecard for v3+ terminal output
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*/
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export function generateScorecard(areaScores, utilization, maturity, segment, actions) {
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// Bug fix: exclude GAP from displayed avgScore (was inconsistent with overallGrade)
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const qualityAreas = areaScores.areas.filter(a => a.name !== 'Feature Coverage');
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const avgScore = qualityAreas.length > 0
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? Math.round(qualityAreas.reduce((s, a) => s + a.score, 0) / qualityAreas.length)
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: 0;
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const lines = [];
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lines.push('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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lines.push(' Config-Audit Posture Score');
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lines.push('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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lines.push('');
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lines.push(` Overall: ${areaScores.overallGrade} (${avgScore}/100) Maturity: Level ${maturity.level} (${maturity.name})`);
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lines.push(` Segment: ${segment.segment} Utilization: ${utilization.score}%`);
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lines.push('');
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lines.push(' Area Scores');
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lines.push(' ───────────');
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// Format areas in 2-column layout
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const areas = areaScores.areas;
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for (let i = 0; i < areas.length; i += 2) {
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const left = areas[i];
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const right = areas[i + 1];
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const leftStr = ` ${left.name} ${'.'.repeat(Math.max(1, 20 - left.name.length))} ${left.grade} (${left.score})`;
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if (right) {
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const rightStr = `${right.name} ${'.'.repeat(Math.max(1, 20 - right.name.length))} ${right.grade} (${right.score})`;
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lines.push(`${leftStr.padEnd(35)}${rightStr}`);
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} else {
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lines.push(leftStr);
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}
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}
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if (actions.length > 0) {
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lines.push('');
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lines.push(' Top 3 Actions');
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lines.push(' ─────────────');
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for (let i = 0; i < actions.length; i++) {
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lines.push(` ${i + 1}. ${actions[i]}`);
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}
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}
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lines.push('');
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lines.push('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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return lines.join('\n');
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}
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/**
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* Generate a v3 health-focused terminal scorecard.
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* Shows only the quality areas (currently 8) — no utilization, maturity, or segment.
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* @param {{ areas: Array<{ name: string, grade: string, score: number }>, overallGrade: string }} areaScores
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* @param {number} opportunityCount - Number of GAP findings (shown as opportunity count)
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* @param {object} [options]
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* @param {boolean} [options.humanized=false] - When true, render with plain-language
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* grade context and friendlier opportunity phrasing. When false (default),
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* render the v5.0.0 verbatim scorecard (backwards-compatible).
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* @returns {string}
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*/
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export function generateHealthScorecard(areaScores, opportunityCount, options = {}) {
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const qualityAreas = areaScores.areas.filter(a => a.name !== 'Feature Coverage');
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const avgScore = qualityAreas.length > 0
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? Math.round(qualityAreas.reduce((s, a) => s + a.score, 0) / qualityAreas.length)
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: 0;
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const humanized = options.humanized === true;
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const lines = [];
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lines.push('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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lines.push(humanized ? ' Configuration health' : ' Config-Audit Health Score');
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lines.push('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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lines.push('');
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if (humanized) {
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const context = GRADE_CONTEXT[areaScores.overallGrade] || '';
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const headline = context
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? ` Health: ${areaScores.overallGrade} (${avgScore}/100) — ${context}`
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: ` Health: ${areaScores.overallGrade} (${avgScore}/100)`;
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lines.push(headline);
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lines.push(` ${qualityAreas.length} areas reviewed`);
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} else {
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lines.push(` Health: ${areaScores.overallGrade} (${avgScore}/100) ${qualityAreas.length} areas scanned`);
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}
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lines.push('');
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lines.push(humanized ? ' Area scores' : ' Area Scores');
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lines.push(' ───────────');
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// Format areas in 2-column layout (quality areas only).
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// In humanized mode, area names are wrapped in backticks so SC-3 can treat
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// them as code references (technical identifiers like CLAUDE.md, MCP, Hooks
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// are tier3 jargon outside backtick spans). Padding compensates for the
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// two extra characters so column alignment matches the v5.0.0 layout.
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const padBase = humanized ? 22 : 20;
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const padCol = humanized ? 37 : 35;
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const labelOf = (a) => (humanized ? `\`${a.name}\`` : a.name);
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for (let i = 0; i < qualityAreas.length; i += 2) {
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const left = qualityAreas[i];
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const right = qualityAreas[i + 1];
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const leftLabel = labelOf(left);
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const leftStr = ` ${leftLabel} ${'.'.repeat(Math.max(1, padBase - leftLabel.length))} ${left.grade} (${left.score})`;
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if (right) {
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const rightLabel = labelOf(right);
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const rightStr = `${rightLabel} ${'.'.repeat(Math.max(1, padBase - rightLabel.length))} ${right.grade} (${right.score})`;
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lines.push(`${leftStr.padEnd(padCol)}${rightStr}`);
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} else {
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lines.push(leftStr);
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}
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}
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if (opportunityCount > 0) {
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lines.push('');
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if (humanized) {
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const noun = opportunityCount === 1 ? 'way' : 'ways';
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lines.push(` ${opportunityCount} ${noun} you could get more out of Claude Code — see /config-audit feature-gap`);
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} else {
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lines.push(` ${opportunityCount} ${opportunityCount === 1 ? 'opportunity' : 'opportunities'} available — run /config-audit feature-gap for recommendations`);
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}
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}
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lines.push('');
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lines.push('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
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return lines.join('\n');
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}
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export { TITLE_TO_ID, TIER_WEIGHTS, TIER_COUNTS, MAX_WEIGHTED, MATURITY_LEVELS, SEGMENTS };
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