Repository Analysis

virattt/dexter

An autonomous agent for deep financial research

3.2 Likely human-written View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of virattt/dexter, a TypeScript project with 27,370 GitHub stars. SynthScan v2.0 examined 41,132 lines of code across 234 source files, recording 73 pattern matches distributed across 4 syntactic categories. The overall adjusted score of 3.2 places this repository in the Likely human-written band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

3.2
Adjusted Score
3.2
Raw Score
100%
Time Factor
2026-07-14
Last Push
27.4K
Stars
TypeScript
Language
41.1K
Lines of Code
234
Files
73
Pattern Hits
2026-07-14
Scan Date
0.00
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 0MEDIUM 19LOW 54

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 73 distinct pattern matches across 4 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Decorative Section Separators19 hits · 57 pts
SeverityFileLineSnippetContext
MEDIUMsrc/tools/search/x-search.ts209// ─── Tool definition ─────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts33// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts35// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts104// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts106// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts152// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts154// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts180// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/permissions/rules.ts182// ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts48 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts50 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts118 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts120 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts183 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts185 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts231 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts233 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts260 // ──────────────────────────────────────────────────────────────────────────COMMENT
MEDIUMsrc/components/question-prompt.ts262 // ──────────────────────────────────────────────────────────────────────────COMMENT
Structural Annotation Overuse24 hits · 39 pts
SeverityFileLineSnippetContext
LOWsrc/tools/finance/read-filings.ts173 // Step 1: Plan ticker + filing types using structured outputCOMMENT
LOWsrc/tools/finance/read-filings.ts246 // Step 2: Select and read filing content with canonical item namesCOMMENT
LOWsrc/tools/finance/screen-stocks.ts123 // Step 1: Fetch screener metrics (cached after first call)COMMENT
LOWsrc/tools/finance/screen-stocks.ts138 // Step 2: LLM structured output — translate natural language → filtersCOMMENT
LOWsrc/tools/finance/screen-stocks.ts158 // Step 3: POST to screener APICOMMENT
LOWsrc/agent/agent.ts573 // Step 1: Memory flushCOMMENT
LOWsrc/agent/agent.ts599 // Step 2: CompactionCOMMENT
LOWsrc/agent/agent.ts652 // Step 3: Fallback — truncate oldest roundsCOMMENT
LOWsrc/skills/write-memo/SKILL.md25## Step 1: Frame the TradeCOMMENT
LOWsrc/skills/write-memo/SKILL.md37## Step 2: Gather Data (Parallel)COMMENT
LOWsrc/skills/write-memo/SKILL.md72## Step 3: Build ScenariosCOMMENT
LOWsrc/skills/write-memo/SKILL.md90## Step 4: Optional DCF AnchorCOMMENT
LOWsrc/skills/write-memo/SKILL.md94## Step 5: Draft Memo ContentCOMMENT
LOWsrc/skills/write-memo/SKILL.md142## Step 6: Self-Critique Pass (Mandatory)COMMENT
LOWsrc/skills/write-memo/SKILL.md154## Step 7: Render HTMLCOMMENT
LOWsrc/skills/write-memo/SKILL.md167## Step 8: Report to ChatCOMMENT
LOWsrc/skills/dcf/SKILL.md23## Step 1: Gather Financial DataCOMMENT
LOWsrc/skills/dcf/SKILL.md62## Step 2: Calculate FCF Growth RateCOMMENT
LOWsrc/skills/dcf/SKILL.md72## Step 3: Estimate Discount Rate (WACC)COMMENT
LOWsrc/skills/dcf/SKILL.md87## Step 4: Project Future Cash FlowsCOMMENT
LOWsrc/skills/dcf/SKILL.md93## Step 5: Calculate Present ValueCOMMENT
LOWsrc/skills/dcf/SKILL.md97## Step 6: Sensitivity AnalysisCOMMENT
LOWsrc/skills/dcf/SKILL.md101## Step 7: Validate ResultsCOMMENT
LOWsrc/skills/dcf/SKILL.md116## Step 8: Output FormatCOMMENT
Hyper-Verbose Identifiers22 hits · 24 pts
SeverityFileLineSnippetContext
LOWsrc/tools/registry.ts263export function buildCompactToolDescriptions(model: string): string {CODE
LOWsrc/tools/fetch/utils.ts153export async function getWithPermittedRedirects(CODE
LOWsrc/tools/finance/formatters.ts148export function formatHistoricalKeyRatios(data: unknown, args?: Rec): string {CODE
LOWsrc/tools/finance/formatters.ts251export function formatBeneficialOwnership(data: unknown): string {CODE
LOWsrc/tools/finance/formatters.ts264export function formatInstitutionalHoldings(data: unknown, args?: Rec): string {CODE
LOWsrc/memory/temporal-decay.ts28export function calculateTemporalDecayMultiplier(params: {CODE
LOWsrc/utils/model.ts55export function getDefaultModelForProvider(providerId: string): string | undefined {CODE
LOWsrc/utils/tokens.ts39export function getEffectiveContextWindow(model: string): number {CODE
LOWsrc/utils/env.ts16export function checkApiKeyExistsForProvider(providerId: string): boolean {CODE
LOWsrc/utils/env.ts112export function getSearchProviderDisplayName(providerId: SearchProviderId): string {CODE
LOWsrc/utils/env.ts116export function getApiKeyNameForSearchProvider(providerId: SearchProviderId): string {CODE
LOWsrc/utils/env.ts120export function checkApiKeyForSearchProvider(providerId: SearchProviderId): boolean {CODE
LOWsrc/utils/env.ts124export function saveApiKeyForSearchProvider(providerId: SearchProviderId, apiKey: string): boolean {CODE
LOWsrc/agent/compact.ts154export function buildCompactSummaryMessage(summary: string): string {CODE
LOWsrc/components/select-list.ts57export function createSearchProviderSelector(CODE
LOWsrc/components/select-list.ts117export function createApiKeyConfirmSelector(onConfirm: (wantsToSet: boolean) => void) {CODE
LOWsrc/model/llm.ts276function annotateSystemMessageForCaching(messages: BaseMessage[]): BaseMessage[] {CODE
LOWsrc/skills/registry.ts107export function buildSkillMetadataSection(): string {CODE
LOWsrc/gateway/access-control.ts95export async function checkInboundAccessControl(params: {CODE
LOWsrc/gateway/group/history-buffer.ts44export function getAndClearGroupHistory(groupId: string): GroupHistoryEntry[] {CODE
LOWsrc/gateway/group/history-buffer.ts54export function formatGroupHistoryContext(params: {CODE
LOWsrc/gateway/channels/whatsapp/auth-store.ts40export function maybeRestoreCredsFromBackup(authDir: string): void {CODE
Verbosity Indicators8 hits · 12 pts
SeverityFileLineSnippetContext
LOWsrc/tools/finance/read-filings.ts173 // Step 1: Plan ticker + filing types using structured outputCOMMENT
LOWsrc/tools/finance/read-filings.ts246 // Step 2: Select and read filing content with canonical item namesCOMMENT
LOWsrc/tools/finance/screen-stocks.ts123 // Step 1: Fetch screener metrics (cached after first call)COMMENT
LOWsrc/tools/finance/screen-stocks.ts138 // Step 2: LLM structured output — translate natural language → filtersCOMMENT
LOWsrc/tools/finance/screen-stocks.ts158 // Step 3: POST to screener APICOMMENT
LOWsrc/agent/agent.ts573 // Step 1: Memory flushCOMMENT
LOWsrc/agent/agent.ts599 // Step 2: CompactionCOMMENT
LOWsrc/agent/agent.ts652 // Step 3: Fallback — truncate oldest roundsCOMMENT