/**
* Centralized Configuration Schemas
* Single source of truth for all optimization/feature config Zod schemas
* [REFACTOR: ZOD-UNIFY] Phase 3: Config schema centralization
* [FIX: SCHEMA-06] Enhanced error messages for all enum fields
* [FIX: SCHEMA-07] Centralized enumErrorMap from utils
*/
import { z } from 'zod';
import { enumErrorMap } from '../utils/zod-helpers.js';
// =============================================================================
// Verification Mode Schema
// =============================================================================
// [FIX: SCHEMA-06] Verification mode enum with helpful error message
const VerificationModeValues = ['standard', 'fast-track', 'single-pass'] as const;
const VerificationModeEnum = z.enum(VerificationModeValues, { errorMap: enumErrorMap('mode', VerificationModeValues) });
export const VerificationModeSchema = z.object({
mode: VerificationModeEnum.default('standard').describe(
'Verification mode: "standard" (full Verifier↔Critic loop), "fast-track" (early convergence for clean code), "single-pass" (Verifier only)'
),
allowEarlyConvergence: z.boolean().optional().describe('Allow convergence before minimum rounds'),
skipCriticForCleanCode: z.boolean().optional().describe('Skip Critic review if no issues found'),
requireSelfReview: z.boolean().optional().describe('Require Verifier self-review in single-pass mode'),
minRounds: z.number().optional().describe('Override default minimum rounds'),
stableRoundsRequired: z.number().optional().describe('Override stable rounds requirement')
}).optional();
export type VerificationModeInput = z.infer<typeof VerificationModeSchema>;
// =============================================================================
// Differential Analysis Schema
// =============================================================================
export const DifferentialConfigSchema = z.object({
enabled: z.boolean().default(false).describe('Enable differential analysis to verify only changed code'),
baseRef: z.string().optional().describe('Base reference for diff: "last-verified", commit hash, branch name, or HEAD~N'),
includeAffectedDependencies: z.boolean().optional().default(true).describe('Include files that import changed files'),
maxAffectedDepth: z.number().optional().default(2).describe('Maximum depth for dependency tracing'),
skipUnchangedTests: z.boolean().optional().default(false).describe('Skip test files that havent changed'),
fallbackToFullIfNoBaseline: z.boolean().optional().default(true).describe('Fall back to full verification if no baseline exists'),
includeLineContext: z.boolean().optional().default(false).describe('Include line-level diff context for focused review')
}).optional();
export type DifferentialConfigInput = z.infer<typeof DifferentialConfigSchema>;
// =============================================================================
// Cache Schema
// =============================================================================
// [FIX: SCHEMA-06] Cache confidence enum with helpful error message
const CacheConfidenceValues = ['HIGH', 'MEDIUM', 'LOW'] as const;
const CacheConfidenceEnum = z.enum(CacheConfidenceValues, { errorMap: enumErrorMap('minConfidence', CacheConfidenceValues) });
export const CacheConfigSchema = z.object({
enabled: z.boolean().default(false).describe('Enable response caching for repeated verifications'),
ttlSeconds: z.number().optional().default(86400).describe('Time-to-live for cache entries in seconds (default: 24 hours)'),
minConfidence: CacheConfidenceEnum.optional().default('MEDIUM').describe('Minimum confidence level to use cached results: "HIGH", "MEDIUM", or "LOW"'),
cacheIssues: z.boolean().optional().default(true).describe('Cache results that contain issues'),
cacheCleanResults: z.boolean().optional().default(true).describe('Cache results with no issues'),
// Extended fields from cache/types.ts
maxEntries: z.number().optional().describe('Maximum number of cache entries'),
storagePath: z.string().optional().describe('Custom storage path for cache')
}).optional();
export type CacheConfigInput = z.infer<typeof CacheConfigSchema>;
// =============================================================================
// Chunking Schema
// =============================================================================
export const ChunkingConfigSchema = z.object({
enabled: z.boolean().default(false).describe('Enable selective context (function-level chunking)'),
maxTokensPerChunk: z.number().optional().default(2000).describe('Maximum tokens per chunk'),
includeRelated: z.boolean().optional().default(true).describe('Include related symbols in chunks'),
maxRelatedDepth: z.number().optional().default(1).describe('Maximum depth for related symbol inclusion'),
minSymbolTokensToChunk: z.number().optional().default(50).describe('Minimum symbol size to chunk separately'),
// Extended fields from chunking/types.ts
priorityCategories: z.array(z.string()).optional().describe('Categories to prioritize in chunking'),
alwaysIncludeTypes: z.array(z.string()).optional().describe('Symbol types to always include')
}).optional();
export type ChunkingConfigInput = z.infer<typeof ChunkingConfigSchema>;
// =============================================================================
// Pipeline Schema
// =============================================================================
// [FIX: SCHEMA-06] Verification tier enum with helpful error message
const VerificationTierValues = ['screen', 'focused', 'exhaustive'] as const;
export const VerificationTierSchema = z.enum(VerificationTierValues, { errorMap: enumErrorMap('tier', VerificationTierValues) });
export type VerificationTierInput = z.infer<typeof VerificationTierSchema>;
export const PipelineConfigSchema = z.object({
enabled: z.boolean().default(false).describe('Enable tiered verification pipeline'),
startTier: VerificationTierSchema.optional().default('screen').describe('Starting verification tier'),
autoEscalate: z.boolean().optional().default(true).describe('Automatically escalate based on findings'),
maxTotalTokens: z.number().optional().default(50000).describe('Maximum total tokens across all tiers'),
exhaustivePatterns: z.array(z.string()).optional().describe('File patterns that always get exhaustive verification')
}).optional();
export type PipelineConfigInput = z.infer<typeof PipelineConfigSchema>;
// =============================================================================
// Safeguards Schema
// =============================================================================
// [FIX: SCHEMA-06] Sampling strategy enum with helpful error message
const SamplingStrategyValues = ['UNIFORM', 'RISK_WEIGHTED', 'CHANGE_WEIGHTED', 'DEPENDENCY_WEIGHTED'] as const;
export const SamplingStrategySchema = z.enum(SamplingStrategyValues, { errorMap: enumErrorMap('strategy', SamplingStrategyValues) });
export type SamplingStrategy = z.infer<typeof SamplingStrategySchema>;
export const PeriodicConfigSchema = z.object({
enabled: z.boolean().default(true).describe('Enable periodic full verification'),
incrementalThreshold: z.number().optional().default(5).describe('Number of incremental verifications before forcing full scan'),
maxHoursSinceFull: z.number().optional().default(24).describe('Maximum hours since last full verification'),
confidenceFloor: z.number().optional().default(0.6).describe('Minimum confidence to avoid full verification'),
alwaysFullPatterns: z.array(z.string()).optional().describe('File patterns that always require full verification')
}).optional();
export type PeriodicConfig = z.infer<typeof PeriodicConfigSchema>;
export const ConfidenceConfigSchema = z.object({
minimumAcceptable: z.number().optional().default(0.7).describe('Minimum acceptable confidence score')
}).optional();
export type ConfidenceConfig = z.infer<typeof ConfidenceConfigSchema>;
export const SamplingConfigSchema = z.object({
enabled: z.boolean().default(true).describe('Enable random sampling of skipped files'),
rate: z.number().optional().default(10).describe('Sampling rate percentage (0-100)'),
minSamples: z.number().optional().default(2).describe('Minimum number of files to sample'),
strategy: SamplingStrategySchema.optional().default('RISK_WEIGHTED').describe('Sampling strategy')
}).optional();
export type SamplingConfig = z.infer<typeof SamplingConfigSchema>;
export const SafeguardsConfigSchema = z.object({
enabled: z.boolean().default(true).describe('Enable quality safeguards'),
periodic: PeriodicConfigSchema,
confidence: ConfidenceConfigSchema,
sampling: SamplingConfigSchema
}).optional();
export type SafeguardsConfigInput = z.infer<typeof SafeguardsConfigSchema>;
// =============================================================================
// Dynamic Roles Schema
// =============================================================================
export const DynamicRoleSamplingParamsSchema = z.object({
maxTokens: z.number().optional().default(4000).describe('Maximum tokens for role generation'),
temperature: z.number().optional().default(0.3).describe('Temperature for role generation (lower = more deterministic)')
}).optional();
export const DynamicRoleConfigSchema = z.object({
enabled: z.boolean().default(false).describe('Enable dynamic role generation based on requirements'),
cacheEnabled: z.boolean().optional().default(true).describe('Cache generated roles for similar requirements'),
maxCacheSize: z.number().optional().default(100).describe('Maximum number of cached role definitions'),
fallbackToStatic: z.boolean().optional().default(true).describe('Fall back to static roles if generation fails'),
samplingParams: DynamicRoleSamplingParamsSchema
}).optional();
export type DynamicRoleConfigInput = z.infer<typeof DynamicRoleConfigSchema>;
// =============================================================================
// LLM Evaluation Schema
// =============================================================================
export const LLMEvalConfigSchema = z.object({
enabled: z.boolean().default(false).describe('Enable LLM-based evaluation (vs pattern matching only)'),
convergenceEval: z.boolean().optional().default(true).describe('Use LLM for convergence quality assessment'),
severityEval: z.boolean().optional().default(true).describe('Use LLM for severity classification'),
edgeCaseEval: z.boolean().optional().default(true).describe('Use LLM to verify edge case analysis quality'),
falsePositiveEval: z.boolean().optional().default(true).describe('Use LLM to detect false positive issues'),
temperature: z.number().optional().default(0.3).describe('Temperature for evaluations (lower = more deterministic)'),
fallbackToPatterns: z.boolean().optional().default(true).describe('Fall back to pattern matching if LLM fails')
}).optional();
export type LLMEvalConfigInput = z.infer<typeof LLMEvalConfigSchema>;
