433 lines
16 KiB
TypeScript
433 lines
16 KiB
TypeScript
export const ASSISTANT_MCP_DISCOVERY_PLAN_SCHEMA_VERSION = "assistant_mcp_discovery_plan_v1" as const;
|
|
export const ASSISTANT_MCP_DISCOVERY_EVIDENCE_SCHEMA_VERSION = "assistant_mcp_discovery_evidence_v1" as const;
|
|
|
|
export const ASSISTANT_MCP_DISCOVERY_PRIMITIVES = [
|
|
"search_business_entity",
|
|
"inspect_1c_metadata",
|
|
"resolve_entity_reference",
|
|
"query_movements",
|
|
"query_documents",
|
|
"aggregate_by_axis",
|
|
"drilldown_related_objects",
|
|
"probe_coverage",
|
|
"explain_evidence_basis"
|
|
] as const;
|
|
|
|
export type AssistantMcpDiscoveryPrimitive = (typeof ASSISTANT_MCP_DISCOVERY_PRIMITIVES)[number];
|
|
|
|
export type AssistantMcpDiscoveryPlanStatus = "allowed" | "needs_clarification" | "blocked";
|
|
export type AssistantMcpDiscoveryCoverageStatus = "full" | "partial" | "blocked";
|
|
export type AssistantMcpDiscoveryEvidenceStatus = "confirmed" | "inferred_only" | "insufficient" | "blocked";
|
|
export type AssistantMcpDiscoveryAnswerPermission = "confirmed_answer" | "bounded_inference" | "checked_sources_only";
|
|
|
|
export interface AssistantMcpDiscoveryTurnMeaningRef {
|
|
asked_domain_family?: string | null;
|
|
asked_action_family?: string | null;
|
|
asked_aggregation_axis?: string | null;
|
|
seeded_ranking_need?: string | null;
|
|
explicit_entity_candidates?: string[];
|
|
metadata_ambiguity_entity_sets?: string[];
|
|
metadata_scope_hint?: string | null;
|
|
explicit_organization_scope?: string | null;
|
|
explicit_date_scope?: string | null;
|
|
subject_resolution_optional?: boolean | null;
|
|
meaning_confidence?: number | null;
|
|
unsupported_but_understood_family?: string | null;
|
|
stale_replay_forbidden?: boolean | null;
|
|
}
|
|
|
|
export interface AssistantMcpDiscoveryExecutionBudget {
|
|
max_probe_count: number;
|
|
max_rows_per_probe: number;
|
|
}
|
|
|
|
export interface AssistantMcpDiscoveryPlanContract {
|
|
schema_version: typeof ASSISTANT_MCP_DISCOVERY_PLAN_SCHEMA_VERSION;
|
|
policy_owner: "assistantMcpDiscoveryPolicy";
|
|
plan_status: AssistantMcpDiscoveryPlanStatus;
|
|
semantic_data_need: string | null;
|
|
turn_meaning_ref: AssistantMcpDiscoveryTurnMeaningRef | null;
|
|
allowed_primitives: AssistantMcpDiscoveryPrimitive[];
|
|
rejected_primitives: string[];
|
|
required_axes: string[];
|
|
clarification_gaps: string[];
|
|
execution_budget: AssistantMcpDiscoveryExecutionBudget;
|
|
requires_evidence_gate: true;
|
|
answer_may_use_raw_model_claims: false;
|
|
reason_codes: string[];
|
|
}
|
|
|
|
export interface BuildAssistantMcpDiscoveryPlanInput {
|
|
semanticDataNeed?: string | null;
|
|
turnMeaning?: AssistantMcpDiscoveryTurnMeaningRef | null;
|
|
proposedPrimitives?: string[] | null;
|
|
requiredAxes?: string[] | null;
|
|
clarificationGaps?: string[] | null;
|
|
maxProbeCount?: number | null;
|
|
maxRowsPerProbe?: number | null;
|
|
}
|
|
|
|
export interface AssistantMcpDiscoveryProbeResult {
|
|
primitive_id: string;
|
|
status: "ok" | "error" | "skipped";
|
|
rows_received?: number | null;
|
|
rows_matched?: number | null;
|
|
limitation?: string | null;
|
|
}
|
|
|
|
export interface ResolveAssistantMcpDiscoveryEvidenceInput {
|
|
plan: AssistantMcpDiscoveryPlanContract;
|
|
probeResults?: AssistantMcpDiscoveryProbeResult[] | null;
|
|
confirmedFacts?: string[] | null;
|
|
inferredFacts?: string[] | null;
|
|
unknownFacts?: string[] | null;
|
|
sourceRowsSummary?: string | null;
|
|
queryLimitations?: string[] | null;
|
|
recommendedNextProbe?: string | null;
|
|
}
|
|
|
|
export interface AssistantMcpDiscoveryEvidenceContract {
|
|
schema_version: typeof ASSISTANT_MCP_DISCOVERY_EVIDENCE_SCHEMA_VERSION;
|
|
policy_owner: "assistantMcpDiscoveryPolicy";
|
|
evidence_status: AssistantMcpDiscoveryEvidenceStatus;
|
|
coverage_status: AssistantMcpDiscoveryCoverageStatus;
|
|
answer_permission: AssistantMcpDiscoveryAnswerPermission;
|
|
confirmed_facts: string[];
|
|
inferred_facts: string[];
|
|
unknown_facts: string[];
|
|
source_rows_summary: string | null;
|
|
query_plan: AssistantMcpDiscoveryPlanContract;
|
|
query_limitations: string[];
|
|
confidence_reason: string;
|
|
recommended_next_probe: string | null;
|
|
reason_codes: string[];
|
|
}
|
|
|
|
const DEFAULT_DISCOVERY_BUDGET: AssistantMcpDiscoveryExecutionBudget = {
|
|
max_probe_count: 3,
|
|
max_rows_per_probe: 100
|
|
};
|
|
|
|
const MAX_PROBE_COUNT = 36;
|
|
const MAX_ROWS_PER_PROBE = 500;
|
|
|
|
const ALLOWED_PRIMITIVE_SET = new Set<string>(ASSISTANT_MCP_DISCOVERY_PRIMITIVES);
|
|
|
|
function toNonEmptyString(value: unknown): string | null {
|
|
if (value === null || value === undefined) {
|
|
return null;
|
|
}
|
|
const text = String(value).trim();
|
|
return text.length > 0 ? text : null;
|
|
}
|
|
|
|
function toStringList(value: unknown): string[] {
|
|
if (!Array.isArray(value)) {
|
|
return [];
|
|
}
|
|
const result: string[] = [];
|
|
for (const item of value) {
|
|
const text = toNonEmptyString(item);
|
|
if (text && !result.includes(text)) {
|
|
result.push(text);
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
|
|
function normalizeReasonCode(value: string): string | null {
|
|
const normalized = value
|
|
.trim()
|
|
.replace(/[^\p{L}\p{N}_.:-]+/gu, "_")
|
|
.replace(/^_+|_+$/g, "")
|
|
.toLowerCase();
|
|
return normalized.length > 0 ? normalized.slice(0, 120) : null;
|
|
}
|
|
|
|
function pushReason(target: string[], value: string): void {
|
|
const normalized = normalizeReasonCode(value);
|
|
if (normalized && !target.includes(normalized)) {
|
|
target.push(normalized);
|
|
}
|
|
}
|
|
|
|
function clampInteger(value: number | null | undefined, fallback: number, min: number, max: number): number {
|
|
if (!Number.isFinite(value)) {
|
|
return fallback;
|
|
}
|
|
return Math.min(max, Math.max(min, Math.trunc(Number(value))));
|
|
}
|
|
|
|
function isAllowedPrimitive(value: string): value is AssistantMcpDiscoveryPrimitive {
|
|
return ALLOWED_PRIMITIVE_SET.has(value);
|
|
}
|
|
|
|
function normalizeTurnMeaning(
|
|
value: AssistantMcpDiscoveryTurnMeaningRef | null | undefined
|
|
): AssistantMcpDiscoveryTurnMeaningRef | null {
|
|
if (!value) {
|
|
return null;
|
|
}
|
|
const result: AssistantMcpDiscoveryTurnMeaningRef = {};
|
|
const domain = toNonEmptyString(value.asked_domain_family);
|
|
const action = toNonEmptyString(value.asked_action_family);
|
|
const aggregationAxis = toNonEmptyString(value.asked_aggregation_axis);
|
|
const seededRankingNeed = toNonEmptyString(value.seeded_ranking_need);
|
|
const organization = toNonEmptyString(value.explicit_organization_scope);
|
|
const dateScope = toNonEmptyString(value.explicit_date_scope);
|
|
const unsupported = toNonEmptyString(value.unsupported_but_understood_family);
|
|
const entities = toStringList(value.explicit_entity_candidates);
|
|
const metadataAmbiguityEntitySets = toStringList(value.metadata_ambiguity_entity_sets);
|
|
if (domain) {
|
|
result.asked_domain_family = domain;
|
|
}
|
|
if (action) {
|
|
result.asked_action_family = action;
|
|
}
|
|
if (aggregationAxis) {
|
|
result.asked_aggregation_axis = aggregationAxis;
|
|
}
|
|
if (seededRankingNeed) {
|
|
result.seeded_ranking_need = seededRankingNeed;
|
|
}
|
|
if (entities.length > 0) {
|
|
result.explicit_entity_candidates = entities;
|
|
}
|
|
if (metadataAmbiguityEntitySets.length > 0) {
|
|
result.metadata_ambiguity_entity_sets = metadataAmbiguityEntitySets;
|
|
}
|
|
if (organization) {
|
|
result.explicit_organization_scope = organization;
|
|
}
|
|
if (dateScope) {
|
|
result.explicit_date_scope = dateScope;
|
|
}
|
|
if (Number.isFinite(value.meaning_confidence)) {
|
|
result.meaning_confidence = Math.max(0, Math.min(1, Number(value.meaning_confidence)));
|
|
}
|
|
if (unsupported) {
|
|
result.unsupported_but_understood_family = unsupported;
|
|
}
|
|
if (value.stale_replay_forbidden !== null && value.stale_replay_forbidden !== undefined) {
|
|
result.stale_replay_forbidden = Boolean(value.stale_replay_forbidden);
|
|
}
|
|
return Object.keys(result).length > 0 ? result : null;
|
|
}
|
|
|
|
function hasGroundingAxis(input: {
|
|
turnMeaning: AssistantMcpDiscoveryTurnMeaningRef | null;
|
|
requiredAxes: string[];
|
|
}): boolean {
|
|
if (input.requiredAxes.length > 0) {
|
|
return true;
|
|
}
|
|
const meaning = input.turnMeaning;
|
|
return Boolean(
|
|
meaning?.asked_domain_family ||
|
|
meaning?.asked_action_family ||
|
|
meaning?.explicit_organization_scope ||
|
|
meaning?.explicit_date_scope ||
|
|
(meaning?.explicit_entity_candidates?.length ?? 0) > 0
|
|
);
|
|
}
|
|
|
|
export function isAssistantMcpDiscoveryPrimitive(value: string): value is AssistantMcpDiscoveryPrimitive {
|
|
return isAllowedPrimitive(value);
|
|
}
|
|
|
|
export function buildAssistantMcpDiscoveryPlan(
|
|
input: BuildAssistantMcpDiscoveryPlanInput
|
|
): AssistantMcpDiscoveryPlanContract {
|
|
const semanticDataNeed = toNonEmptyString(input.semanticDataNeed);
|
|
const turnMeaning = normalizeTurnMeaning(input.turnMeaning);
|
|
const requiredAxes = toStringList(input.requiredAxes);
|
|
const clarificationGaps = toStringList(input.clarificationGaps);
|
|
const proposed = toStringList(input.proposedPrimitives);
|
|
const reasonCodes: string[] = [];
|
|
const allowedPrimitives: AssistantMcpDiscoveryPrimitive[] = [];
|
|
const rejectedPrimitives: string[] = [];
|
|
|
|
for (const primitive of proposed) {
|
|
if (isAllowedPrimitive(primitive)) {
|
|
if (!allowedPrimitives.includes(primitive)) {
|
|
allowedPrimitives.push(primitive);
|
|
}
|
|
} else {
|
|
rejectedPrimitives.push(primitive);
|
|
}
|
|
}
|
|
|
|
if (rejectedPrimitives.length > 0) {
|
|
pushReason(reasonCodes, "model_proposed_unregistered_mcp_primitive");
|
|
}
|
|
if (!semanticDataNeed) {
|
|
pushReason(reasonCodes, "semantic_data_need_missing");
|
|
}
|
|
if (!turnMeaning) {
|
|
pushReason(reasonCodes, "turn_meaning_ref_missing");
|
|
}
|
|
if (!hasGroundingAxis({ turnMeaning, requiredAxes })) {
|
|
pushReason(reasonCodes, "grounding_axis_missing");
|
|
}
|
|
if (allowedPrimitives.length === 0 && proposed.length > 0) {
|
|
pushReason(reasonCodes, "no_allowed_mcp_primitives_after_runtime_filter");
|
|
}
|
|
if (allowedPrimitives.length === 0 && proposed.length === 0) {
|
|
pushReason(reasonCodes, "mcp_primitives_not_proposed");
|
|
}
|
|
|
|
let planStatus: AssistantMcpDiscoveryPlanStatus = "allowed";
|
|
if (allowedPrimitives.length === 0 && proposed.length > 0) {
|
|
planStatus = "blocked";
|
|
} else if (!semanticDataNeed || !turnMeaning || !hasGroundingAxis({ turnMeaning, requiredAxes })) {
|
|
planStatus = "needs_clarification";
|
|
} else if (allowedPrimitives.length === 0) {
|
|
planStatus = "needs_clarification";
|
|
}
|
|
|
|
if (planStatus === "allowed") {
|
|
pushReason(reasonCodes, "guarded_mcp_discovery_plan_allowed");
|
|
} else if (planStatus === "blocked") {
|
|
pushReason(reasonCodes, "guarded_mcp_discovery_plan_blocked");
|
|
} else {
|
|
pushReason(reasonCodes, "guarded_mcp_discovery_plan_needs_clarification");
|
|
}
|
|
|
|
return {
|
|
schema_version: ASSISTANT_MCP_DISCOVERY_PLAN_SCHEMA_VERSION,
|
|
policy_owner: "assistantMcpDiscoveryPolicy",
|
|
plan_status: planStatus,
|
|
semantic_data_need: semanticDataNeed,
|
|
turn_meaning_ref: turnMeaning,
|
|
allowed_primitives: allowedPrimitives,
|
|
rejected_primitives: rejectedPrimitives,
|
|
required_axes: requiredAxes,
|
|
clarification_gaps: clarificationGaps,
|
|
execution_budget: {
|
|
max_probe_count: clampInteger(input.maxProbeCount, DEFAULT_DISCOVERY_BUDGET.max_probe_count, 1, MAX_PROBE_COUNT),
|
|
max_rows_per_probe: clampInteger(
|
|
input.maxRowsPerProbe,
|
|
DEFAULT_DISCOVERY_BUDGET.max_rows_per_probe,
|
|
1,
|
|
MAX_ROWS_PER_PROBE
|
|
)
|
|
},
|
|
requires_evidence_gate: true,
|
|
answer_may_use_raw_model_claims: false,
|
|
reason_codes: reasonCodes
|
|
};
|
|
}
|
|
|
|
function collectProbeLimitations(probeResults: AssistantMcpDiscoveryProbeResult[]): string[] {
|
|
const limitations: string[] = [];
|
|
for (const probe of probeResults) {
|
|
const limitation = toNonEmptyString(probe.limitation);
|
|
if (limitation && !limitations.includes(limitation)) {
|
|
limitations.push(limitation);
|
|
}
|
|
}
|
|
return limitations;
|
|
}
|
|
|
|
function probeRowsMatched(probeResults: AssistantMcpDiscoveryProbeResult[]): number {
|
|
return probeResults.reduce((sum, probe) => {
|
|
const rows = Number(probe.rows_matched ?? 0);
|
|
return sum + (Number.isFinite(rows) && rows > 0 ? rows : 0);
|
|
}, 0);
|
|
}
|
|
|
|
function probeRowsReceived(probeResults: AssistantMcpDiscoveryProbeResult[]): number {
|
|
return probeResults.reduce((sum, probe) => {
|
|
const rows = Number(probe.rows_received ?? 0);
|
|
return sum + (Number.isFinite(rows) && rows > 0 ? rows : 0);
|
|
}, 0);
|
|
}
|
|
|
|
function hasProbeBypass(plan: AssistantMcpDiscoveryPlanContract, probeResults: AssistantMcpDiscoveryProbeResult[]): boolean {
|
|
const allowed = new Set<string>(plan.allowed_primitives);
|
|
return probeResults.some((probe) => !allowed.has(probe.primitive_id));
|
|
}
|
|
|
|
function confidenceReasonFor(status: AssistantMcpDiscoveryEvidenceStatus): string {
|
|
if (status === "confirmed") {
|
|
return "confirmed_facts_backed_by_allowed_mcp_probe_rows";
|
|
}
|
|
if (status === "inferred_only") {
|
|
return "only_inferred_facts_available_from_allowed_mcp_probe_rows";
|
|
}
|
|
if (status === "blocked") {
|
|
return "runtime_evidence_gate_blocked_discovery_answer";
|
|
}
|
|
return "allowed_mcp_probes_did_not_produce_sufficient_evidence";
|
|
}
|
|
|
|
export function resolveAssistantMcpDiscoveryEvidence(
|
|
input: ResolveAssistantMcpDiscoveryEvidenceInput
|
|
): AssistantMcpDiscoveryEvidenceContract {
|
|
const probeResults = Array.isArray(input.probeResults) ? input.probeResults : [];
|
|
const confirmedFacts = toStringList(input.confirmedFacts);
|
|
const inferredFacts = toStringList(input.inferredFacts);
|
|
const unknownFacts = toStringList(input.unknownFacts);
|
|
const sourceRowsSummary = toNonEmptyString(input.sourceRowsSummary);
|
|
const queryLimitations = [
|
|
...toStringList(input.queryLimitations),
|
|
...collectProbeLimitations(probeResults)
|
|
].filter((item, index, all) => all.indexOf(item) === index);
|
|
const reasonCodes: string[] = [...input.plan.reason_codes];
|
|
const rowsMatched = probeRowsMatched(probeResults);
|
|
const rowsReceived = probeRowsReceived(probeResults);
|
|
const bypassDetected = hasProbeBypass(input.plan, probeResults);
|
|
|
|
if (bypassDetected) {
|
|
pushReason(reasonCodes, "probe_result_used_primitive_outside_runtime_plan");
|
|
}
|
|
if (input.plan.plan_status !== "allowed") {
|
|
pushReason(reasonCodes, "plan_not_allowed_by_runtime");
|
|
}
|
|
if (confirmedFacts.length > 0 && rowsMatched <= 0) {
|
|
pushReason(reasonCodes, "confirmed_facts_without_matched_probe_rows");
|
|
}
|
|
if (!sourceRowsSummary && rowsReceived > 0) {
|
|
pushReason(reasonCodes, "source_rows_summary_missing");
|
|
}
|
|
|
|
let evidenceStatus: AssistantMcpDiscoveryEvidenceStatus = "insufficient";
|
|
let coverageStatus: AssistantMcpDiscoveryCoverageStatus = "blocked";
|
|
let answerPermission: AssistantMcpDiscoveryAnswerPermission = "checked_sources_only";
|
|
|
|
if (bypassDetected || input.plan.plan_status !== "allowed") {
|
|
evidenceStatus = "blocked";
|
|
coverageStatus = "blocked";
|
|
answerPermission = "checked_sources_only";
|
|
} else if (confirmedFacts.length > 0 && rowsMatched > 0 && sourceRowsSummary) {
|
|
evidenceStatus = "confirmed";
|
|
coverageStatus = "full";
|
|
answerPermission = "confirmed_answer";
|
|
pushReason(reasonCodes, "confirmed_facts_with_allowed_mcp_evidence");
|
|
} else if (inferredFacts.length > 0 && rowsReceived > 0) {
|
|
evidenceStatus = "inferred_only";
|
|
coverageStatus = "partial";
|
|
answerPermission = "bounded_inference";
|
|
pushReason(reasonCodes, "inferred_facts_require_bounded_answer");
|
|
} else {
|
|
pushReason(reasonCodes, "mcp_discovery_evidence_insufficient");
|
|
}
|
|
|
|
return {
|
|
schema_version: ASSISTANT_MCP_DISCOVERY_EVIDENCE_SCHEMA_VERSION,
|
|
policy_owner: "assistantMcpDiscoveryPolicy",
|
|
evidence_status: evidenceStatus,
|
|
coverage_status: coverageStatus,
|
|
answer_permission: answerPermission,
|
|
confirmed_facts: confirmedFacts,
|
|
inferred_facts: inferredFacts,
|
|
unknown_facts: unknownFacts,
|
|
source_rows_summary: sourceRowsSummary,
|
|
query_plan: input.plan,
|
|
query_limitations: queryLimitations,
|
|
confidence_reason: confidenceReasonFor(evidenceStatus),
|
|
recommended_next_probe: toNonEmptyString(input.recommendedNextProbe),
|
|
reason_codes: reasonCodes
|
|
};
|
|
}
|