hyperguild/internal/skills/brain/skill.go

// internal/skills/brain/skill.go
package brain

import (
	"encoding/json"

	"github.com/mathiasbq/supervisor/internal/registry"
)

// Config holds brain skill configuration.
type Config struct {
	IngestBaseURL  string // base URL of the ingestion HTTP server (brain_query, brain_write)
	IngestSvcURL   string // base URL of the ingestion-svc HTTP server (brain_ingest)
	KBRetrievalURL string // base URL of the kb-retrieval server (brain_search)
}

// Skill implements registry.Skill for brain_query and brain_write.
type Skill struct {
	cfg Config
}

// New constructs a brain Skill.
func New(cfg Config) *Skill { return &Skill{cfg: cfg} }

// Name returns the skill name used for routing.
func (s *Skill) Name() string { return "brain" }

// Tools returns the MCP tool definitions for brain_query and brain_write.
func (s *Skill) Tools() []registry.ToolDef {
	schema := func(required []string, props map[string]any) json.RawMessage {
		b, _ := json.Marshal(map[string]any{"type": "object", "required": required, "properties": props})
		return b
	}
	str := map[string]any{"type": "string"}
	num := map[string]any{"type": "integer"}

	tools := []registry.ToolDef{
		{
			Name:        "brain_query",
			Description: "BM25 full-text search across brain/knowledge/ and brain/wiki/ markdown files. Fast, no embeddings needed. Call before any significant task.",
			InputSchema: schema([]string{"query"}, map[string]any{
				"query": str,
				"limit": num,
			}),
		},
		{
			Name:        "brain_write",
			Description: "Write a raw knowledge note to brain/knowledge/ for later ingestion.",
			InputSchema: schema([]string{"content"}, map[string]any{
				"content":  str,
				"type":     str,
				"domain":   str,
				"filename": str,
			}),
		},
	}
	if s.cfg.IngestSvcURL != "" {
		tools = append(tools, registry.ToolDef{
			Name: "brain_ingest_raw",
			Description: "Ingest pre-structured pages into the brain wiki, bypassing the LLM extraction step. " +
				"Use when you (the calling agent) have already extracted entities, concepts, and content from a source. " +
				"Provide source (human-readable name) and pages (array of {title, type, subtype, domain, content} objects). " +
				"The pipeline computes slugs, paths, frontmatter, wikilink canonicalization, and source back-references. " +
				"Returns the list of wiki pages written.",
			InputSchema: schema([]string{"source", "pages"}, map[string]any{
				"source": map[string]any{"type": "string", "description": "human-readable name for the source, e.g. 'shape-up-book'"},
				"pages": map[string]any{
					"type": "array",
					"items": map[string]any{
						"type":     "object",
						"required": []string{"title", "type", "content"},
						"properties": map[string]any{
							"title":   map[string]any{"type": "string", "description": "page title, e.g. 'Hash Encoding'"},
							"type":    map[string]any{"type": "string", "enum": []string{"source", "concept", "entity"}, "description": "page type"},
							"subtype": map[string]any{"type": "string", "description": "entity: person|company|tool|model|framework|technology; source: article|pdf|book|video|note|project"},
							"domain":  map[string]any{"type": "string", "description": "knowledge domain, e.g. 'Machine Learning'"},
							"content": map[string]any{"type": "string", "description": "markdown body — no frontmatter, use [[Display Name]] for wikilinks"},
						},
					},
				},
				"dry_run": map[string]any{"type": "boolean"},
			}),
		})
		tools = append(tools, registry.ToolDef{
			Name: "brain_ingest",
			Description: "Ingest content into the brain wiki (brain/wiki/). Calls an LLM to produce structured wiki pages. " +
				"Use for substantial documents, articles, or knowledge worth structuring. " +
				"Provide EITHER (a) path — absolute path to a file or directory, " +
				"OR (b) content + source — raw text and a human-readable name. " +
				"Providing both is an error. Returns the list of wiki pages written.",
			InputSchema: schema([]string{}, map[string]any{
				"content": map[string]any{"type": "string", "description": "raw text to ingest; required when path is not set"},
				"source":  map[string]any{"type": "string", "description": "human-readable name for the content, e.g. 'shape-up-book'; required when path is not set"},
				"path":    map[string]any{"type": "string", "description": "absolute path to a file or directory to ingest; mutually exclusive with content+source"},
				"dry_run": map[string]any{"type": "boolean"},
			}),
		})
	}
	if s.cfg.KBRetrievalURL != "" {
		tools = append(tools, registry.ToolDef{
			Name:        "brain_search",
			Description: "Semantic vector search across the brain wiki using embeddings. Use when brain_query returns no results or you need conceptually-related results rather than keyword matches.",
			InputSchema: schema([]string{"query"}, map[string]any{
				"query":      str,
				"collection": str,
				"limit":      num,
			}),
		})
	}
	return tools
}