import { z } from "zod";
import type { McpTool } from "../tool.js";
declare const inputSchema: z.ZodObject<{
    /**
     * Entity identifier. For `type='project'`, a slug or alias. For
     * `type='person'`, a slug, email, or display name. For 'topic',
     * any free-text label that names the thing you want context on
     * (e.g. "auth migration", "payment processor evaluation").
     */
    entity: z.ZodString;
    /**
     * Entity kind. `project` and `person` route through the taxonomy
     * (canonical structured data + recent activity). `topic` falls back
     * to a top-K hybrid search since it has no canonical record.
     */
    type: z.ZodDefault<z.ZodEnum<["project", "person", "topic"]>>;
    /** Recent-activity count when applicable. Default 10, cap 50. */
    topK: z.ZodDefault<z.ZodNumber>;
    /** Days to look back for recent activity. Default 60. */
    recentDays: z.ZodDefault<z.ZodNumber>;
}, "strip", z.ZodTypeAny, {
    type: "project" | "person" | "topic";
    recentDays: number;
    topK: number;
    entity: string;
}, {
    entity: string;
    type?: "project" | "person" | "topic" | undefined;
    recentDays?: number | undefined;
    topK?: number | undefined;
}>;
interface DossierResult {
    entity: string;
    type: "project" | "person" | "topic";
    found: boolean;
    /**
     * Canonical structured data when the entity has a taxonomy record:
     *   - project: { slug, name, description, active, aliases, sources, people }
     *   - person:  { slug, name, email, role? }
     *   - topic:   undefined (no canonical record)
     */
    canonical?: Record<string, unknown>;
    /** Top relevant chunks (recent activity for project/person; ranked search for topic). */
    related: Array<{
        id: string;
        snippet: string;
        title?: string;
        type?: string;
        source?: string;
        project?: string | string[];
        date?: string;
        source_url?: string;
        score?: number;
    }>;
    hint?: string;
}
/**
 * Knowledge-base dossier.
 *
 * Mirrors the Engram `memory_dossier({entity})` pattern from the local-
 * context roadmap, but at the org-knowledge level. Pre-loads canonical
 * structured data PLUS top relevant chunks for an entity in one call so
 * the consumer (Pyre's coordinator, an agent, a chat reply) doesn't
 * need to chain `get_project_context` + `search_related` itself.
 *
 * Implementation:
 *   - `type=project`: routes through get_project_context (taxonomy +
 *     recent activity scoped to the project).
 *   - `type=person`: looks up the person in the taxonomy, then runs a
 *     name-based search for recent mentions/activity.
 *   - `type=topic`: no canonical record; returns a top-K search by name.
 */
export declare const kbDossier: McpTool<typeof inputSchema, DossierResult>;
export {};
//# sourceMappingURL=kb-dossier.d.ts.map