mirror of
https://github.com/AgentSeal/codeburn.git
synced 2026-07-10 01:29:41 +00:00
feat(cursor): add tools and bash-command breakdown from agentKv
Cursor logs the agent's tool calls (Read, Grep, Glob, Shell, ...) in agentKv
blobs. Join them to conversations via the turn requestId (carried on the bubble's
$.requestId and inherited positionally by the turn's agentKv rows) and attach each
conversation's tool list and Shell commands to the call that carries its input.
Measured on a real DB: Cursor now reports tools {Read, Grep, Glob, Shell,
SemanticSearch} and the executed shell commands, which were previously empty.
Removes the now-superseded parseAgentKv content-char estimate.
This commit is contained in:
AgentSeal
parent
03cae01e31
commit
867f709b29
1 changed files with 82 additions and 147 deletions
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@ -1,4 +1,4 @@
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import { existsSync, statSync, readdirSync, readFileSync } from 'fs'
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import { existsSync, readdirSync, readFileSync } from 'fs'
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import { join } from 'path'
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import { homedir } from 'os'
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@ -66,17 +66,6 @@ type AgentKvRow = {
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content_length: number
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}
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type AgentKvContent = {
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type?: string
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text?: string
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providerOptions?: {
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cursor?: {
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modelName?: string
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requestId?: string
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}
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}
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}
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const CHARS_PER_TOKEN = 4
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function getCursorDbPath(): string {
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@ -497,11 +486,73 @@ function loadComposerInputTokens(db: SqliteDatabase): Map<string, number> {
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return map
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}
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type AgentTools = { tools: string[]; bash: string[] }
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// Cursor logs the agent's tool calls (Read, Grep, Shell, ...) in agentKv blobs
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// keyed by requestId. Bubbles carry the same requestId plus the composerId, so
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// joining the two attributes each conversation's tools and Shell commands.
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const BUBBLE_REQUESTID_QUERY = `
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SELECT key as bubble_key, json_extract(value, '$.requestId') as request_id
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FROM cursorDiskKV
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WHERE key LIKE 'bubbleId:%' AND json_extract(value, '$.requestId') IS NOT NULL
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`
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function loadAgentToolsByComposer(db: SqliteDatabase): Map<string, AgentTools> {
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const byComposer = new Map<string, AgentTools>()
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const requestToComposer = new Map<string, string>()
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try {
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const rows = db.query<{ bubble_key: string; request_id: string | null }>(BUBBLE_REQUESTID_QUERY)
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for (const r of rows) {
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const composer = parseComposerIdFromKey(r.bubble_key)
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if (composer && r.request_id) requestToComposer.set(r.request_id, composer)
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}
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} catch {
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return byComposer
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}
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let rows: AgentKvRow[]
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try {
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rows = db.query<AgentKvRow>(AGENTKV_QUERY)
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} catch {
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return byComposer
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}
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// Only the turn-opening (user) agentKv row carries the requestId; the
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// assistant rows that follow inherit it, so track it positionally.
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let currentRequestId: string | null = null
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for (const row of rows) {
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if (row.request_id) currentRequestId = row.request_id
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if (row.role !== 'assistant' || !row.content || !currentRequestId) continue
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const composer = requestToComposer.get(currentRequestId)
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if (!composer) continue
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let content: unknown
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try {
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content = JSON.parse(blobToText(row.content))
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} catch {
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continue
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}
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if (!Array.isArray(content)) continue
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const bucket = byComposer.get(composer) ?? { tools: [], bash: [] }
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for (const block of content as Array<{ type?: string; toolName?: string; args?: { command?: string } }>) {
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if (!block || block.type !== 'tool-call' || !block.toolName) continue
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bucket.tools.push(block.toolName)
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if (block.toolName === 'Shell') {
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const command = block.args?.command?.trim()
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if (command) bucket.bash.push(command)
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}
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}
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byComposer.set(composer, bucket)
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}
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return byComposer
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}
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function parseBubbles(
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db: SqliteDatabase,
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seenKeys: Set<string>,
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timeFloor: string,
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composerInput: Map<string, number>,
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agentTools: Map<string, AgentTools>,
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): { calls: ParsedProviderCall[] } {
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const results: ParsedProviderCall[] = []
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let skipped = 0
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@ -569,6 +620,9 @@ function parseBubbles(
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let inputTokens = row.input_tokens ?? 0
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let outputTokens = row.output_tokens ?? 0
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// The conversation's tools/bash attach to the single call that carries its
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// real input (its first turn), so they are counted exactly once.
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let creditedHere = false
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// Current Cursor leaves tokenCount at {0,0}. Use the conversation's real
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// context size (promptTokenBreakdown) for input, credited once per
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@ -579,8 +633,13 @@ function parseBubbles(
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if (row.bubble_type === 1) {
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const real = composerInput.get(conversationId)
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if (real != null) {
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inputTokens = creditedComposers.has(conversationId) ? 0 : real
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creditedComposers.add(conversationId)
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if (creditedComposers.has(conversationId)) {
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inputTokens = 0
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} else {
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inputTokens = real
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creditedComposers.add(conversationId)
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creditedHere = true
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}
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} else {
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inputTokens = Math.ceil(textLen / CHARS_PER_TOKEN)
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}
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@ -612,7 +671,12 @@ function parseBubbles(
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const languages = extractLanguages(blobToText(row.code_blocks))
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const hasCode = languages.length > 0
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const cursorTools: string[] = hasCode ? ['cursor:edit', ...languages.map(l => `lang:${l}`)] : []
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const agentTurn = creditedHere ? agentTools.get(conversationId) : undefined
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const cursorTools: string[] = [
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...(hasCode ? ['cursor:edit', ...languages.map(l => `lang:${l}`)] : []),
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...(agentTurn?.tools ?? []),
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]
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const bashCommands = agentTurn?.bash ?? []
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results.push({
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provider: 'cursor',
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@ -626,7 +690,7 @@ function parseBubbles(
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webSearchRequests: 0,
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costUSD,
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tools: cursorTools,
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bashCommands: [],
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bashCommands,
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timestamp,
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speed: 'standard',
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deduplicationKey: dedupKey,
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@ -645,136 +709,6 @@ function parseBubbles(
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return { calls: results }
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}
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function extractModelFromContent(content: AgentKvContent[]): string | null {
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for (const c of content) {
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if (c.providerOptions?.cursor?.modelName) {
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return c.providerOptions.cursor.modelName
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}
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}
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return null
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}
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function extractTextLength(content: AgentKvContent[]): number {
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let total = 0
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for (const c of content) {
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if (c.text) total += c.text.length
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}
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return total
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}
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function parseAgentKv(db: SqliteDatabase, seenKeys: Set<string>, dbPath: string): { calls: ParsedProviderCall[] } {
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const results: ParsedProviderCall[] = []
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// Cursor's agentKv schema does not record per-message timestamps. Use the
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// SQLite file's mtime as a bounded "last write" timestamp for all calls;
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// it's at least honest (no future time, no always-now). Users running
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// codeburn against an idle Cursor install will see agentKv calls land at
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// the actual last activity time rather than today's date.
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let agentKvTimestamp: string
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try {
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agentKvTimestamp = new Date(statSync(dbPath).mtimeMs).toISOString()
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} catch {
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agentKvTimestamp = new Date().toISOString()
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}
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let rows: AgentKvRow[]
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try {
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rows = db.query<AgentKvRow>(AGENTKV_QUERY)
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} catch {
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return { calls: results }
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}
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const sessions: Map<string, { inputChars: number; outputChars: number; model: string | null; userText: string }> = new Map()
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let currentRequestId = 'unknown'
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let turnIndex = 0
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for (const row of rows) {
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if (!row.role || !row.content) continue
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const contentText = blobToText(row.content)
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let content: AgentKvContent[]
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let plainTextLength = 0
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try {
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const parsed = JSON.parse(contentText)
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if (Array.isArray(parsed)) {
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content = parsed
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} else {
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content = []
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plainTextLength = contentText.length
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}
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} catch {
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content = []
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plainTextLength = contentText.length
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}
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const requestId = row.request_id ?? currentRequestId
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if (requestId !== currentRequestId) {
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currentRequestId = requestId
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turnIndex = 0
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}
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const textLength = plainTextLength || extractTextLength(content)
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const model = extractModelFromContent(content)
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if (row.role === 'user') {
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const existing = sessions.get(requestId) ?? { inputChars: 0, outputChars: 0, model: null, userText: '' }
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existing.inputChars += textLength
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if (!existing.userText) {
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const text = content[0]?.text ?? contentText
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const queryMatch = text.match(/<user_query>([\s\S]*?)<\/user_query>/)
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existing.userText = queryMatch ? queryMatch[1].trim().slice(0, 500) : text.slice(0, 500)
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}
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sessions.set(requestId, existing)
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} else if (row.role === 'assistant') {
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const existing = sessions.get(requestId) ?? { inputChars: 0, outputChars: 0, model: null, userText: '' }
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existing.outputChars += textLength
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if (model) existing.model = model
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sessions.set(requestId, existing)
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} else if (row.role === 'tool' || row.role === 'system') {
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const existing = sessions.get(requestId) ?? { inputChars: 0, outputChars: 0, model: null, userText: '' }
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existing.inputChars += textLength
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sessions.set(requestId, existing)
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}
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}
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for (const [requestId, session] of sessions) {
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if (session.inputChars === 0 && session.outputChars === 0) continue
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const inputTokens = Math.ceil(session.inputChars / CHARS_PER_TOKEN)
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const outputTokens = Math.ceil(session.outputChars / CHARS_PER_TOKEN)
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const dedupKey = `cursor:agentKv:${requestId}`
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if (seenKeys.has(dedupKey)) continue
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seenKeys.add(dedupKey)
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const pricingModel = resolveModel(session.model)
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const displayModel = modelForDisplay(session.model)
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const costUSD = calculateCost(pricingModel, inputTokens, outputTokens, 0, 0, 0)
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results.push({
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provider: 'cursor',
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model: displayModel,
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inputTokens,
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outputTokens,
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cacheCreationInputTokens: 0,
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cacheReadInputTokens: 0,
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cachedInputTokens: 0,
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reasoningTokens: 0,
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webSearchRequests: 0,
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costUSD,
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tools: [],
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bashCommands: [],
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timestamp: agentKvTimestamp,
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speed: 'standard',
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deduplicationKey: dedupKey,
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userMessage: session.userText,
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sessionId: requestId,
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})
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}
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return { calls: results }
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}
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function createParser(
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source: SessionSource,
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seenKeys: Set<string>,
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@ -845,7 +779,8 @@ function createParser(
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// which double-counted against the bubble stream. parseAgentKv is
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// kept for the tools/bash breakdown in a follow-up.
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const composerInput = loadComposerInputTokens(db)
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const { calls: bubbleCalls } = parseBubbles(db, localSeen, timeFloor, composerInput)
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const agentTools = loadAgentToolsByComposer(db)
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const { calls: bubbleCalls } = parseBubbles(db, localSeen, timeFloor, composerInput, agentTools)
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allCalls = bubbleCalls
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await writeCachedResults(dbPath, allCalls, timeFloor)
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} finally {
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