397777089e
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
219 lines
7.8 KiB
JavaScript
219 lines
7.8 KiB
JavaScript
// Pure logic for the Brain Dashboard. Browser-safe ES module (no node: APIs)
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// so it loads both in the browser and under Vitest's node environment.
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export function normalizeEpisode(raw) {
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const v2 = raw.schema_version === 2;
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const pr = raw.primary_rationale || {};
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const events = Array.isArray(raw.events) ? raw.events : [];
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const tools = {};
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for (const ev of events) {
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if (ev.kind === 'tool_summary' && ev.counts) {
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for (const [k, n] of Object.entries(ev.counts)) tools[k] = (tools[k] || 0) + n;
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}
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}
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const started = raw.timestamps?.started_at || null;
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const ended = raw.timestamps?.ended_at || null;
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return {
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schemaVersion: v2 ? 2 : 1,
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taskId: raw.task_id || null,
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taskRef: raw.task_ref || raw.task_id || null,
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startedAt: started,
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endedAt: ended,
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durationMs: started && ended ? Date.parse(ended) - Date.parse(started) : null,
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pathType: raw.path_type || null,
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outcome: raw.outcome || 'unknown',
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promptSignal: v2 ? raw.prompt_signal || null : null,
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decisionProvenance: v2 ? raw.decision_provenance || null : null,
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environment: v2 ? raw.environment || null : null,
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taskSize: v2 ? raw.task_size || null : null,
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taskClassification: pr.task_classification || null,
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nodeChosen: pr.node_chosen || null,
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hardFloor: pr.hard_floor || { invoked: false, rules: [] },
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skills: events.filter((e) => e.kind === 'skill_invoked').map((e) => e.skill),
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tools,
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errorCount: events.filter((e) => e.kind === 'error').length,
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retryCount: events.filter((e) => e.kind === 'retry').length,
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interruptCount: events.filter((e) => e.kind === 'interrupt').length,
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events,
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raw,
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};
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}
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// episode skill name → automation-graph node id (see tools/observer-known-nodes.txt
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// for the routable vocabulary; only skills that have a graph node are listed).
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export const SKILL_TO_NODE = {
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brainstorming: 'sk_brainstorm',
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'writing-plans': 'sk_wplans',
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'executing-plans': 'sk_eplans',
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'subagent-driven-development': 'sk_subagent',
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'test-driven-development': 'sk_tdd',
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'systematic-debugging': 'sk_debug',
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'verification-before-completion': 'sk_verify',
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'requesting-code-review': 'sk_coderev',
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'using-git-worktrees': 'sk_worktree',
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'finishing-a-development-branch': 'sk_pr',
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'writing-skills': 'sk_wskills',
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'discovery-interview': 'discovery_interview',
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'audit-portal': 'sk_audit_portal',
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regression: 'sk_regression',
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'process-modeling': 'process_modeling',
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'process-analysis': 'process_analysis',
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ccpm: 'ccpm',
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'security-review': 'sk_security_review',
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'claude-md-management': 'claude_md_mgmt',
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};
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// mcp__<server>__<tool> → automation-graph node id.
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export const MCP_SERVER_TO_NODE = {
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github: 'mcp_gh',
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playwright: 'mcp_pw',
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'laravel-boost': 'mcp_boost',
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redis: 'mcp_redis',
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sentry: 'mcp_sentry',
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semgrep: 'mcp_semgrep',
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openapi: 'mcp_openapi',
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magic: 'mcp_21st',
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'universal-icons': 'mcp_icons',
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};
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// "superpowers:systematic-debugging" → "systematic-debugging"
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function skillBase(name) {
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const s = String(name || '');
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return s.includes(':') ? s.split(':').pop() : s;
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}
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// Returns { nodeIds: string[], signals: number, attributed: number }.
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// A "signal" is an episode datum that names a routable node (a skill id or an
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// mcp__ tool). Builtin Claude tools are not signals.
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export function attributeNodes(episode) {
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const ids = new Set();
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let signals = 0;
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let attributed = 0;
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const consider = (nodeId) => {
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signals++;
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if (nodeId) {
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ids.add(nodeId);
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attributed++;
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}
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};
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if (episode.nodeChosen && episode.nodeChosen !== 'direct') {
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consider(SKILL_TO_NODE[skillBase(episode.nodeChosen)]);
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}
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for (const s of episode.skills) consider(SKILL_TO_NODE[skillBase(s)]);
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for (const toolName of Object.keys(episode.tools)) {
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const m = /^mcp__(.+?)__/.exec(toolName);
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if (m) consider(MCP_SERVER_TO_NODE[m[1]]);
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}
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return { nodeIds: [...ids], signals, attributed };
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}
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// Groups episodes by taskRef. Each group's episodes are sorted newest-first;
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// groups are ordered by their newest episode, newest group first.
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export function groupBySession(episodes) {
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const byRef = new Map();
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for (const e of episodes) {
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const key = e.taskRef || e.taskId || 'unknown';
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if (!byRef.has(key)) byRef.set(key, []);
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byRef.get(key).push(e);
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}
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const groups = [...byRef.entries()].map(([taskRef, eps]) => {
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eps.sort((a, b) => String(b.startedAt).localeCompare(String(a.startedAt)));
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return { taskRef, episodes: eps, newest: eps[0]?.startedAt || '' };
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});
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groups.sort((a, b) => String(b.newest).localeCompare(String(a.newest)));
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return groups;
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}
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// filter: { classification?, outcome?, pathType?, withErrors?, dateFrom?, dateTo? }
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export function filterEpisodes(episodes, filter = {}) {
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return episodes.filter((e) => {
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if (filter.classification && e.taskClassification !== filter.classification) return false;
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if (filter.outcome && e.outcome !== filter.outcome) return false;
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if (filter.pathType && e.pathType !== filter.pathType) return false;
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if (filter.withErrors && e.errorCount === 0 && e.retryCount === 0) return false;
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if (filter.dateFrom && String(e.startedAt) < filter.dateFrom) return false;
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if (filter.dateTo && String(e.startedAt) > filter.dateTo) return false;
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return true;
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});
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}
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// Three honest layers (spec §6):
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// design — the dashed conflict edges (fact, from topology)
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// friction — node id → count of errored/retried episodes attributed to it
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// correlation — errored episodes that span both ends of a design-conflict edge
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export function inferConflicts(episodes, edges) {
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const design = edges.filter((e) => e.dashes === true);
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const friction = {};
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const correlation = [];
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for (const e of episodes) {
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if (e.errorCount === 0 && e.retryCount === 0) continue;
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const ids = attributeNodes(e).nodeIds;
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for (const id of ids) friction[id] = (friction[id] || 0) + 1;
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if (e.errorCount > 0) {
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for (const edge of design) {
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if (ids.includes(edge.from) && ids.includes(edge.to)) {
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correlation.push({ episode: e.taskId, pair: [edge.from, edge.to], conflict: edge.title || '' });
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}
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}
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}
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}
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return { design, friction, correlation };
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}
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// Aggregates a list of episodes into dashboard metrics.
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export function aggregate(episodes) {
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const nodeHeat = {};
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const pathType = {};
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const outcome = {};
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const classification = {};
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const economy = {};
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let totalErrors = 0;
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let totalRetries = 0;
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let redirects = 0;
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for (const e of episodes) {
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for (const id of attributeNodes(e).nodeIds) nodeHeat[id] = (nodeHeat[id] || 0) + 1;
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if (e.pathType) pathType[e.pathType] = (pathType[e.pathType] || 0) + 1;
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outcome[e.outcome] = (outcome[e.outcome] || 0) + 1;
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if (e.taskClassification) classification[e.taskClassification] = (classification[e.taskClassification] || 0) + 1;
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const lvl = e.environment ? e.environment.economy_level : null;
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const key = lvl == null ? 'n/a' : String(lvl);
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economy[key] = (economy[key] || 0) + 1;
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totalErrors += e.errorCount;
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totalRetries += e.retryCount;
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if (e.decisionProvenance && e.decisionProvenance.kind === 'user_directed_method') redirects++;
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}
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return {
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nodeHeat,
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pathType,
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outcome,
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classification,
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economy,
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totalErrors,
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totalRetries,
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redirectRate: episodes.length ? redirects / episodes.length : 0,
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count: episodes.length,
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};
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}
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export function parseEpisodes(text) {
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const episodes = [];
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let skipped = 0;
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for (const line of String(text).split('\n')) {
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const trimmed = line.trim();
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if (!trimmed) continue;
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let raw;
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try {
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raw = JSON.parse(trimmed);
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} catch {
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skipped++;
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continue;
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}
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if (!raw || typeof raw !== 'object' || raw.observer_error) {
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skipped++;
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continue;
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}
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episodes.push(normalizeEpisode(raw));
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}
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return { episodes, skipped };
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}
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