package mcp

import (
	"context"
	"encoding/json"
	"fmt"

	"github.com/mathiasbq/hyperguild/ingestion/internal/search"
)

// tools returns the tool descriptors. Handler bodies for each tool are filled
// in subsequent tasks; this file currently only provides the descriptors.
func (s *Server) tools() []map[string]any {
	str := func(desc string) map[string]any {
		return map[string]any{"type": "string", "description": desc}
	}
	int_ := func(desc string) map[string]any {
		return map[string]any{"type": "integer", "description": desc}
	}
	schema := func(required []string, props map[string]any) json.RawMessage {
		b, _ := json.Marshal(map[string]any{
			"type": "object", "required": required, "properties": props,
		})
		return b
	}

	return []map[string]any{
		{
			"name":        "brain_query",
			"description": "BM25 full-text search across brain/knowledge/ and brain/wiki/ markdown files.",
			"inputSchema": schema([]string{"query"}, map[string]any{
				"query": str("search terms"),
				"limit": int_("max results, default 5"),
			}),
		},
		{
			"name":        "brain_write",
			"description": "Write a raw knowledge note to brain/knowledge/.",
			"inputSchema": schema([]string{"content"}, map[string]any{
				"content":  str("markdown content"),
				"filename": str("optional filename"),
				"type":     str("optional frontmatter type"),
				"domain":   str("optional frontmatter domain"),
			}),
		},
		{
			"name":        "brain_ingest_raw",
			"description": "Ingest pre-structured pages into the brain wiki, bypassing the LLM extraction step.",
			"inputSchema": schema([]string{"source", "pages"}, map[string]any{
				"source":  str("source name"),
				"pages":   map[string]any{"type": "array"},
				"dry_run": map[string]any{"type": "boolean"},
			}),
		},
		{
			"name":        "brain_ingest",
			"description": "Ingest content into the brain wiki via the LLM extraction pipeline.",
			"inputSchema": schema([]string{}, map[string]any{
				"content": str("raw content; required when path is empty"),
				"source":  str("source name; required when path is empty"),
				"path":    str("file path; mutually exclusive with content+source"),
				"dry_run": map[string]any{"type": "boolean"},
			}),
		},
		{
			"name":        "session_log",
			"description": "Append a structured entry to brain/sessions/<session_id>.jsonl.",
			"inputSchema": schema([]string{"session_id"}, map[string]any{
				"session_id":   str("session identifier"),
				"skill":        str("skill name"),
				"phase":        str("phase within the skill"),
				"project_root": str("absolute project root"),
				"final_status": str("ok | error | skipped"),
				"file_path":    str("optional file produced"),
				"model_used":   str("optional model identifier"),
				"duration_ms":  int_("optional duration in ms"),
				"message":      str("optional free-text"),
			}),
		},
	}
}

type brainQueryArgs struct {
	Query string `json:"query"`
	Limit int    `json:"limit,omitempty"`
}

func (s *Server) brainQuery(ctx context.Context, args json.RawMessage) (json.RawMessage, error) {
	var a brainQueryArgs
	if err := json.Unmarshal(args, &a); err != nil {
		return nil, fmt.Errorf("parse args: %w", err)
	}
	if a.Query == "" {
		return nil, fmt.Errorf("query is required")
	}
	if a.Limit == 0 {
		a.Limit = 5
	}
	results, err := search.Query(s.brainDir, a.Query, a.Limit)
	if err != nil {
		return nil, fmt.Errorf("search: %w", err)
	}
	return json.Marshal(map[string]any{"results": results})
}