mirror of
https://github.com/AgentSeal/codeburn.git
synced 2026-05-17 03:56:45 +00:00
f92d57d24a
Adds a context-bloat finding to codeburn optimize that flags sessions where effective input/cache tokens (cache-discounted via existing pricing constants) are large and disproportionate to output. Suggests starting fresh with a tightened context. Sessions flagged here are excluded from the cost-outlier finding to avoid double-listing. Growth-from-previous-session callouts are suppressed when the predecessor is more than 7 days back. Three impact tiers (low/medium/high). Supersedes #242 with review fixes from real-data probe. Original implementation by @ozymandiashh.
652 lines
21 KiB
TypeScript
652 lines
21 KiB
TypeScript
import { describe, it, expect } from 'vitest'
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import {
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detectJunkReads,
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detectDuplicateReads,
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detectLowReadEditRatio,
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detectCacheBloat,
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detectBloatedClaudeMd,
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detectContextBloat,
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detectSessionOutliers,
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computeHealth,
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computeTrend,
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type ToolCall,
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type ApiCallMeta,
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type WasteFinding,
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} from '../src/optimize.js'
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import type { ProjectSummary } from '../src/types.js'
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function call(name: string, input: Record<string, unknown>, sessionId = 's1', project = 'p1'): ToolCall {
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return { name, input, sessionId, project }
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}
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function emptyProjects(): ProjectSummary[] {
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return []
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}
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function projectWithSessions(costs: number[], project = 'app'): ProjectSummary {
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const sessions = costs.map((cost, i) => {
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const tokens = Math.round(cost * 1000)
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return {
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sessionId: `s${i + 1}`,
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project,
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firstTimestamp: `2026-05-${String(i + 1).padStart(2, '0')}T10:00:00Z`,
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lastTimestamp: `2026-05-${String(i + 1).padStart(2, '0')}T10:30:00Z`,
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totalCostUSD: cost,
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totalInputTokens: tokens,
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totalOutputTokens: tokens,
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totalCacheReadTokens: 0,
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totalCacheWriteTokens: 0,
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apiCalls: 1,
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turns: [],
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modelBreakdown: {},
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toolBreakdown: {},
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mcpBreakdown: {},
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bashBreakdown: {},
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categoryBreakdown: {} as ProjectSummary['sessions'][number]['categoryBreakdown'],
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skillBreakdown: {},
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}
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})
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return {
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project,
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projectPath: `/tmp/${project}`,
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sessions,
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totalCostUSD: costs.reduce((sum, cost) => sum + cost, 0),
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totalApiCalls: sessions.length,
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}
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}
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type TestSession = ProjectSummary['sessions'][number]
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function contextSession(
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i: number,
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overrides: Partial<TestSession>,
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project = 'app',
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): TestSession {
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return {
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sessionId: `s${i + 1}`,
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project,
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firstTimestamp: `2026-05-${String(i + 1).padStart(2, '0')}T10:00:00Z`,
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lastTimestamp: `2026-05-${String(i + 1).padStart(2, '0')}T10:30:00Z`,
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totalCostUSD: 1,
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totalInputTokens: 0,
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totalOutputTokens: 0,
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totalCacheReadTokens: 0,
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totalCacheWriteTokens: 0,
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apiCalls: 1,
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turns: [],
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modelBreakdown: {},
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toolBreakdown: {},
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mcpBreakdown: {},
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bashBreakdown: {},
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categoryBreakdown: {} as TestSession['categoryBreakdown'],
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skillBreakdown: {},
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...overrides,
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}
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}
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function projectWithContextSessions(sessions: TestSession[], project = 'app'): ProjectSummary {
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return {
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project,
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projectPath: `/tmp/${project}`,
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sessions,
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totalCostUSD: sessions.reduce((sum, session) => sum + session.totalCostUSD, 0),
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totalApiCalls: sessions.reduce((sum, session) => sum + session.apiCalls, 0),
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}
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}
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describe('detectJunkReads', () => {
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it('returns null below minimum threshold', () => {
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const calls = [
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call('Read', { file_path: '/x/node_modules/a.js' }),
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call('Read', { file_path: '/x/node_modules/b.js' }),
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]
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expect(detectJunkReads(calls)).toBeNull()
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})
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it('flags when threshold is met', () => {
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const calls = [
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call('Read', { file_path: '/x/node_modules/a.js' }),
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call('Read', { file_path: '/x/node_modules/b.js' }),
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call('Read', { file_path: '/x/.git/config' }),
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]
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const finding = detectJunkReads(calls)
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expect(finding).not.toBeNull()
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expect(finding!.impact).toBe('low')
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})
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it('scales impact with read count', () => {
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const make = (n: number) => Array.from({ length: n }, (_, i) =>
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call('Read', { file_path: `/x/node_modules/file-${i}.js` })
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)
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expect(detectJunkReads(make(25))!.impact).toBe('high')
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expect(detectJunkReads(make(10))!.impact).toBe('medium')
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})
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it('ignores non-junk paths', () => {
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const calls = [
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call('Read', { file_path: '/x/src/a.ts' }),
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call('Read', { file_path: '/x/src/b.ts' }),
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call('Read', { file_path: '/x/README.md' }),
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]
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expect(detectJunkReads(calls)).toBeNull()
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})
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it('ignores non-read tools', () => {
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const calls = [
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call('Edit', { file_path: '/x/node_modules/a.js' }),
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call('Bash', { command: 'ls node_modules' }),
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call('Grep', { pattern: 'test', path: '/x/node_modules' }),
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]
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expect(detectJunkReads(calls)).toBeNull()
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})
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it('handles missing file_path gracefully', () => {
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const calls = [
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call('Read', {}),
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call('Read', { file_path: null as unknown as string }),
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]
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expect(detectJunkReads(calls)).toBeNull()
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})
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it('suggests CLAUDE.md advice listing detected and common junk dirs', () => {
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const calls = Array.from({ length: 5 }, () => call('Read', { file_path: '/x/node_modules/a.js' }))
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const finding = detectJunkReads(calls)!
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expect(finding.fix.type).toBe('paste')
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if (finding.fix.type === 'paste') {
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expect(finding.fix.text).toContain('node_modules')
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}
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expect(finding.fix.label).toContain('CLAUDE.md')
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})
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})
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describe('detectDuplicateReads', () => {
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it('counts same file read multiple times in same session', () => {
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const calls = [
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...Array.from({ length: 4 }, () => call('Read', { file_path: '/src/a.ts' }, 's1')),
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...Array.from({ length: 4 }, () => call('Read', { file_path: '/src/b.ts' }, 's1')),
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]
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const finding = detectDuplicateReads(calls)
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expect(finding).not.toBeNull()
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})
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it('does not count across sessions', () => {
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const calls = [
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call('Read', { file_path: '/src/a.ts' }, 's1'),
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call('Read', { file_path: '/src/a.ts' }, 's2'),
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call('Read', { file_path: '/src/a.ts' }, 's3'),
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]
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expect(detectDuplicateReads(calls)).toBeNull()
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})
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it('excludes junk directory reads', () => {
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const calls = Array.from({ length: 10 }, () =>
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call('Read', { file_path: '/x/node_modules/foo.js' }, 's1')
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)
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expect(detectDuplicateReads(calls)).toBeNull()
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})
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it('returns null for single reads', () => {
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const calls = [
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call('Read', { file_path: '/src/a.ts' }, 's1'),
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call('Read', { file_path: '/src/b.ts' }, 's1'),
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]
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expect(detectDuplicateReads(calls)).toBeNull()
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})
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})
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describe('detectLowReadEditRatio', () => {
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it('returns null below minimum edit count', () => {
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const calls = [
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call('Edit', {}),
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call('Edit', {}),
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call('Read', {}),
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]
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expect(detectLowReadEditRatio(calls)).toBeNull()
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})
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it('returns null when ratio is healthy', () => {
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const calls = [
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...Array.from({ length: 40 }, () => call('Read', {})),
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...Array.from({ length: 10 }, () => call('Edit', {})),
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]
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expect(detectLowReadEditRatio(calls)).toBeNull()
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})
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it('flags when edits outpace reads', () => {
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const calls = [
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...Array.from({ length: 5 }, () => call('Read', {})),
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...Array.from({ length: 10 }, () => call('Edit', {})),
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]
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const finding = detectLowReadEditRatio(calls)
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expect(finding).not.toBeNull()
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expect(finding!.impact).toBe('high')
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})
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it('counts Grep and Glob as reads for ratio', () => {
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const calls = [
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...Array.from({ length: 40 }, () => call('Grep', {})),
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...Array.from({ length: 10 }, () => call('Edit', {})),
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]
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expect(detectLowReadEditRatio(calls)).toBeNull()
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})
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it('counts Write as edit', () => {
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const calls = [
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...Array.from({ length: 15 }, () => call('Read', {})),
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...Array.from({ length: 10 }, () => call('Write', {})),
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]
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const finding = detectLowReadEditRatio(calls)
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expect(finding).not.toBeNull()
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})
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})
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describe('detectCacheBloat', () => {
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it('returns null below minimum api calls', () => {
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const apiCalls: ApiCallMeta[] = [
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{ cacheCreationTokens: 80000, version: '2.1.100' },
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{ cacheCreationTokens: 80000, version: '2.1.100' },
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]
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expect(detectCacheBloat(apiCalls, emptyProjects())).toBeNull()
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})
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it('returns null when median is close to baseline', () => {
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const apiCalls: ApiCallMeta[] = Array.from({ length: 20 }, () => ({
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cacheCreationTokens: 50000,
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version: '2.1.98',
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}))
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expect(detectCacheBloat(apiCalls, emptyProjects())).toBeNull()
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})
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it('flags when median exceeds 1.4x baseline', () => {
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const apiCalls: ApiCallMeta[] = Array.from({ length: 20 }, () => ({
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cacheCreationTokens: 80000,
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version: '2.1.100',
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}))
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const finding = detectCacheBloat(apiCalls, emptyProjects())
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expect(finding).not.toBeNull()
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})
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})
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describe('detectBloatedClaudeMd', () => {
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it('returns null when no projects have CLAUDE.md', () => {
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const result = detectBloatedClaudeMd(new Set(['/nonexistent/path']))
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expect(result).toBeNull()
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})
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it('returns null for empty project set', () => {
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const result = detectBloatedClaudeMd(new Set())
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expect(result).toBeNull()
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})
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})
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describe('detectContextBloat', () => {
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it('returns null below the input/context token floor', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 74_999,
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totalOutputTokens: 100,
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}),
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])
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expect(detectContextBloat([project])).toBeNull()
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})
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it('returns null when output is proportionate to input/context tokens', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 100_000,
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totalOutputTokens: 5_000,
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}),
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])
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expect(detectContextBloat([project])).toBeNull()
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})
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it('discounts cache reads when estimating context pressure', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 5_000,
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totalCacheReadTokens: 700_000,
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totalOutputTokens: 5_000,
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}),
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])
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expect(detectContextBloat([project])).toBeNull()
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})
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it('weights cache writes when estimating context pressure', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 10_000,
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totalCacheWriteTokens: 80_000,
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totalOutputTokens: 3_000,
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}),
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.explanation).toContain('110.0K effective input/cache')
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expect(finding!.tokensSaved).toBe(65_000)
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})
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it('flags sessions where input/cache tokens swamp output', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 90_000,
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totalCacheReadTokens: 30_000,
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totalOutputTokens: 2_000,
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}),
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.title).toContain('context-heavy session')
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expect(finding!.explanation).toContain('app/s1')
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expect(finding!.explanation).toContain('93.0K effective input/cache')
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expect(finding!.explanation).toContain('46.5:1')
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expect(finding!.impact).toBe('low')
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expect(finding!.tokensSaved).toBe(63_000)
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})
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it('uses medium impact between the low and high tiers', () => {
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const project = projectWithContextSessions(
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Array.from({ length: 4 }, (_, i) => contextSession(i, {
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totalInputTokens: 80_000,
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totalOutputTokens: 1_000,
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})),
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)
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.impact).toBe('medium')
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})
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it('uses high impact at 10 or more candidates regardless of total size', () => {
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const project = projectWithContextSessions(
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Array.from({ length: 10 }, (_, i) => contextSession(i, {
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totalInputTokens: 80_000,
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totalOutputTokens: 1_000,
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})),
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)
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.impact).toBe('high')
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})
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it('includes context growth from the previous session when it is large', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 20_000,
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totalOutputTokens: 1_000,
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}),
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contextSession(1, {
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totalInputTokens: 100_000,
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totalOutputTokens: 2_000,
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}),
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.explanation).toContain('5.0x previous session input')
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})
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it('calculates context growth within each project only', () => {
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const finding = detectContextBloat([
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projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 20_000,
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totalOutputTokens: 1_000,
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}),
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contextSession(1, {
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totalInputTokens: 100_000,
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totalOutputTokens: 2_000,
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}),
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], 'app'),
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projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 100_000,
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totalOutputTokens: 2_000,
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}, 'api'),
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], 'api'),
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])
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expect(finding).not.toBeNull()
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expect(finding!.explanation.match(/previous session input/g)).toHaveLength(1)
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})
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it('summarizes additional candidates after the preview limit', () => {
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const project = projectWithContextSessions(
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Array.from({ length: 6 }, (_, i) => contextSession(i, {
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totalInputTokens: 80_000 + i * 10_000,
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totalOutputTokens: 1_000,
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})),
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)
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.explanation).toContain('app/s6')
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expect(finding!.explanation).toContain('; +1 more')
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expect(finding!.impact).toBe('high')
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})
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it('uses high impact for one very large context-heavy session', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 600_000,
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totalOutputTokens: 10_000,
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}),
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.impact).toBe('high')
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})
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it('handles zero-output sessions without dividing by zero', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 80_000,
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totalOutputTokens: 0,
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}),
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.explanation).toContain('1000+:1')
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expect(finding!.tokensSaved).toBe(80_000)
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})
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it('caps display ratio at 1000+:1 for non-zero-output sessions too', () => {
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const project = projectWithContextSessions([
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contextSession(0, {
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totalInputTokens: 5_000_000,
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totalOutputTokens: 100,
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}),
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.explanation).toContain('1000+:1')
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})
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it('suppresses the growth ratio when the previous session is more than 7 days back', () => {
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const project = projectWithContextSessions([
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{
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...contextSession(0, { totalInputTokens: 20_000, totalOutputTokens: 1_000 }),
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firstTimestamp: '2026-05-01T10:00:00Z',
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lastTimestamp: '2026-05-01T10:30:00Z',
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},
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{
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...contextSession(1, { totalInputTokens: 100_000, totalOutputTokens: 2_000 }),
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firstTimestamp: '2026-05-15T10:00:00Z',
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lastTimestamp: '2026-05-15T10:30:00Z',
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},
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
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expect(finding!.explanation).not.toContain('previous session input')
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})
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it('anchors growth even when the previous session is below the reporting threshold', () => {
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const project = projectWithContextSessions([
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contextSession(0, { totalInputTokens: 20_000, totalOutputTokens: 1_000 }),
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contextSession(1, { totalInputTokens: 100_000, totalOutputTokens: 2_000 }),
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])
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const finding = detectContextBloat([project])
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expect(finding).not.toBeNull()
|
|
// The first session sits below CONTEXT_BLOAT_MIN_INPUT_TOKENS (75K) and
|
|
// is not itself a candidate, but the growth-from-previous comparison for
|
|
// the second session must still anchor against it.
|
|
expect(finding!.explanation).toContain('5.0x previous session input')
|
|
})
|
|
})
|
|
|
|
describe('detectSessionOutliers', () => {
|
|
it('returns null when there are too few sessions for a project baseline', () => {
|
|
expect(detectSessionOutliers([projectWithSessions([0.5, 4])])).toBeNull()
|
|
})
|
|
|
|
it('returns null when no session exceeds twice the project average', () => {
|
|
expect(detectSessionOutliers([projectWithSessions([1, 1.2, 1.4, 1.6])])).toBeNull()
|
|
})
|
|
|
|
it('does not flag the exact 2x boundary', () => {
|
|
expect(detectSessionOutliers([projectWithSessions([1, 1, 2])])).toBeNull()
|
|
})
|
|
|
|
it('flags sessions costing more than twice their project average', () => {
|
|
const finding = detectSessionOutliers([projectWithSessions([1, 1, 1, 10])])
|
|
expect(finding).not.toBeNull()
|
|
expect(finding!.title).toContain('high-cost session outlier')
|
|
expect(finding!.explanation).toContain('app/s4')
|
|
expect(finding!.impact).toBe('medium')
|
|
expect(finding!.tokensSaved).toBeGreaterThan(0)
|
|
})
|
|
|
|
it('ignores tiny absolute-cost outliers', () => {
|
|
expect(detectSessionOutliers([projectWithSessions([0.01, 0.01, 0.01, 0.2])])).toBeNull()
|
|
})
|
|
|
|
it('isolates baselines per project', () => {
|
|
const finding = detectSessionOutliers([
|
|
projectWithSessions([8, 9, 10], 'web'),
|
|
projectWithSessions([1, 1, 1, 12], 'api'),
|
|
])
|
|
|
|
expect(finding).not.toBeNull()
|
|
expect(finding!.explanation).toContain('api/s4')
|
|
expect(finding!.explanation).not.toContain('web/')
|
|
})
|
|
|
|
it('excludes sessions already flagged by detectContextBloat', () => {
|
|
const project = projectWithSessions([1, 1, 1, 10])
|
|
const excluded = new Set(['s4'])
|
|
expect(detectSessionOutliers([project], excluded)).toBeNull()
|
|
})
|
|
|
|
it('still flags cost outliers that are not context-bloat candidates', () => {
|
|
const project = projectWithSessions([1, 1, 1, 10])
|
|
const excluded = new Set(['some-other-session'])
|
|
const finding = detectSessionOutliers([project], excluded)
|
|
expect(finding).not.toBeNull()
|
|
expect(finding!.explanation).toContain('app/s4')
|
|
})
|
|
})
|
|
|
|
describe('computeHealth', () => {
|
|
it('returns A with 100 for no findings', () => {
|
|
const { score, grade } = computeHealth([])
|
|
expect(score).toBe(100)
|
|
expect(grade).toBe('A')
|
|
})
|
|
|
|
function mockFinding(impact: 'high' | 'medium' | 'low'): WasteFinding {
|
|
return {
|
|
title: 't', explanation: 'e', impact, tokensSaved: 1000,
|
|
fix: { type: 'paste', label: 'l', text: 't' },
|
|
}
|
|
}
|
|
|
|
it('one low finding stays at A', () => {
|
|
const { score, grade } = computeHealth([mockFinding('low')])
|
|
expect(score).toBe(97)
|
|
expect(grade).toBe('A')
|
|
})
|
|
|
|
it('two high findings drop to C', () => {
|
|
const { score, grade } = computeHealth([mockFinding('high'), mockFinding('high')])
|
|
expect(score).toBe(70)
|
|
expect(grade).toBe('C')
|
|
})
|
|
|
|
it('caps penalty at 80 to prevent score below 20', () => {
|
|
const findings = Array.from({ length: 20 }, () => mockFinding('high'))
|
|
const { score } = computeHealth(findings)
|
|
expect(score).toBe(20)
|
|
})
|
|
|
|
it('progresses grades predictably', () => {
|
|
expect(computeHealth([mockFinding('low')]).grade).toBe('A')
|
|
expect(computeHealth([mockFinding('medium')]).grade).toBe('A')
|
|
expect(computeHealth([mockFinding('medium'), mockFinding('medium')]).grade).toBe('B')
|
|
expect(computeHealth([mockFinding('high'), mockFinding('high'), mockFinding('high')]).grade).toBe('C')
|
|
expect(computeHealth([mockFinding('high'), mockFinding('high'), mockFinding('high'), mockFinding('high'), mockFinding('high')]).grade).toBe('F')
|
|
})
|
|
})
|
|
|
|
describe('computeTrend', () => {
|
|
const window = 48 * 60 * 60 * 1000
|
|
const baselineWindow = 5 * 24 * 60 * 60 * 1000
|
|
|
|
it('returns active when no recent activity detected', () => {
|
|
const trend = computeTrend({
|
|
recentCount: 0, recentWindowMs: window,
|
|
baselineCount: 100, baselineWindowMs: baselineWindow,
|
|
hasRecentActivity: false,
|
|
})
|
|
expect(trend).toBe('active')
|
|
})
|
|
|
|
it('returns resolved when recent activity exists but zero waste in it', () => {
|
|
const trend = computeTrend({
|
|
recentCount: 0, recentWindowMs: window,
|
|
baselineCount: 100, baselineWindowMs: baselineWindow,
|
|
hasRecentActivity: true,
|
|
})
|
|
expect(trend).toBe('resolved')
|
|
})
|
|
|
|
it('returns improving when recent rate is less than half of baseline rate', () => {
|
|
const trend = computeTrend({
|
|
recentCount: 5, recentWindowMs: window,
|
|
baselineCount: 100, baselineWindowMs: baselineWindow,
|
|
hasRecentActivity: true,
|
|
})
|
|
expect(trend).toBe('improving')
|
|
})
|
|
|
|
it('returns active when recent rate matches baseline rate', () => {
|
|
const recentRate = 100 / baselineWindow
|
|
const recentCount = Math.ceil(recentRate * window)
|
|
const trend = computeTrend({
|
|
recentCount, recentWindowMs: window,
|
|
baselineCount: 100, baselineWindowMs: baselineWindow,
|
|
hasRecentActivity: true,
|
|
})
|
|
expect(trend).toBe('active')
|
|
})
|
|
|
|
it('returns active when baseline is empty (new finding)', () => {
|
|
const trend = computeTrend({
|
|
recentCount: 10, recentWindowMs: window,
|
|
baselineCount: 0, baselineWindowMs: baselineWindow,
|
|
hasRecentActivity: true,
|
|
})
|
|
expect(trend).toBe('active')
|
|
})
|
|
})
|