tool loading: require explicit autoLoad, clean package structure

Remove lazy tool loading (load-on-call). Tools must now be explicitly
listed in the agent's autoLoad config. Calling an unloaded tool fails
with a clear error message.

Package structure improvements:
- embedding/index.go: generic Index type for semantic matching
- skills/skills.go: uses embedding.Index internally, keeps Skill type
- agent/skill_match.go: matchSkills() for skill discovery
- agent/tool_match.go: matchTools() for tool hints (new file)

Tool hints now match only loaded tools, not all tools on disk.
This makes agent capabilities explicit and auditable.

cmd/olliesrv/internal/agent/skill_match.go

@@ -1,39 +1,22 @@
 package agent
 
 import (
-	"encoding/json"
-	"os"
-	"path/filepath"
-	"sort"
 	"strings"
 	"sync"
 
-	"ollie/embedding"
 	"ollie/skills"
-	"ollie/util"
 )
 
 // Skill matching configuration.
 const (
-	// skillMatchThreshold is the minimum cosine similarity to include a skill.
 	skillMatchThreshold = 0.35
-	// skillMatchLimit is the maximum number of skills to inject per turn.
-	skillMatchLimit = 3
-
-	// toolMatchThreshold is the minimum cosine similarity to include a tool hint.
-	toolMatchThreshold = 0.35
-	// toolMatchLimit is the maximum number of tool hints to inject per turn.
-	toolMatchLimit = 5
+	skillMatchLimit     = 3
 )
 
 var (
 	skillIndex   *skills.Index
 	skillInitErr error
 	skillOnce    sync.Once
-
-	toolIndex   *skills.Index
-	toolInitErr error
-	toolOnce    sync.Once
 )
 
 // matchSkills finds skills relevant to the user's input and returns
@@ -69,7 +52,6 @@ func matchSkills(input string) string {
 		sb.WriteString("\" relevance=\"")
 		sb.WriteString(formatScore(r.Score))
 		sb.WriteString("\">\n")
-		// Include full skill content (already includes frontmatter)
 		sb.WriteString(r.Skill.Content)
 		if !strings.HasSuffix(r.Skill.Content, "\n") {
 			sb.WriteString("\n")
@@ -80,113 +62,10 @@ func matchSkills(input string) string {
 	return sb.String()
 }
 
-// matchTools finds tools relevant to the user's input and returns
-// a hint block telling the model to call them.
-func matchTools(input string) string {
-	toolOnce.Do(func() {
-		idx, err := newToolIndex()
-		if err != nil {
-			toolInitErr = err
-			return
-		}
-		toolIndex = idx
-	})
-
-	if toolIndex == nil {
-		return ""
-	}
-
-	workflowText := normalizeWorkflow(input).SearchText()
-	workflow := normalizeWorkflow(input)
-	searchInput := input
-	if workflowText != "" {
-		searchInput += " Workflow: " + workflowText
-	}
-	results, err := toolIndex.Match(searchInput, toolMatchThreshold, toolMatchLimit)
-	if err != nil {
-		return ""
-	}
-	for i := range results {
-		results[i].Score += workflowToolAdjustment(results[i].Skill.Name, workflow)
-	}
-	sort.SliceStable(results, func(i, j int) bool {
-		return results[i].Score > results[j].Score
-	})
-	if len(results) == 0 {
-		return ""
-	}
-
-	var sb strings.Builder
-	sb.WriteString("<tool-hints>\n")
-	sb.WriteString("Relevant tools for this request:\n\n")
-	for _, r := range results {
-		sb.WriteString("→ `")
-		sb.WriteString(r.Skill.Name)
-		sb.WriteString("({...})` — ")
-		sb.WriteString(r.Skill.Description)
-		sb.WriteString("\n")
-	}
-	sb.WriteString("\nTo make one callable, use client_9p to load it through the agent ctl file:\n")
-	sb.WriteString("client_9p(op=\"rdwr\", path=\"session/$OLLIE_SESSION_ID/agent/$OLLIE_UNAME/ctl\", data=\"tool_load <name>\")\n")
-	sb.WriteString("Then call the loaded tool.\n")
-	sb.WriteString("</tool-hints>\n")
-	return sb.String()
-}
-
 func formatScore(s float32) string {
-	// Format as percentage
 	pct := int(s * 100)
 	if pct > 99 {
 		pct = 99
 	}
 	return string([]byte{'0' + byte(pct/10), '0' + byte(pct%10), '%'})
 }
-
-// newToolIndex creates a skill-compatible index from tool .meta files.
-func newToolIndex() (*skills.Index, error) {
-	model, err := embedding.LoadModel(skills.DefaultModelDir())
-	if err != nil {
-		return nil, err
-	}
-
-	toolsDir := filepath.Join(util.CfgDir(), "tools")
-	entries, err := os.ReadDir(toolsDir)
-	if err != nil {
-		model.Close()
-		return nil, err
-	}
-
-	var toolSkills []skills.Skill
-	for _, entry := range entries {
-		if entry.IsDir() || !strings.HasSuffix(entry.Name(), ".meta") {
-			continue
-		}
-		metaPath := filepath.Join(toolsDir, entry.Name())
-		data, err := os.ReadFile(metaPath)
-		if err != nil {
-			continue
-		}
-		var meta struct {
-			Description string   `json:"description"`
-			Prompt      string   `json:"prompt"`
-			Keywords    []string `json:"keywords"`
-		}
-		if json.Unmarshal(data, &meta) != nil || meta.Description == "" {
-			continue
-		}
-		toolName := strings.TrimSuffix(entry.Name(), ".meta")
-		searchText := meta.Description
-		if meta.Prompt != "" {
-			searchText += " Usage: " + meta.Prompt
-		}
-		if len(meta.Keywords) > 0 {
-			searchText += " Keywords: " + strings.Join(meta.Keywords, ", ")
-		}
-		toolSkills = append(toolSkills, skills.Skill{
-			Name:        toolName,
-			Description: searchText,
-		})
-	}
-
-	return skills.NewIndexFromSkills(model, toolSkills)
-}

cmd/olliesrv/internal/agent/tool_match.go

@@ -0,0 +1,107 @@
+package agent
+
+import (
+	"sort"
+	"strings"
+	"sync"
+
+	"ollie/embedding"
+	"ollie/skills"
+	"ollie/toolsrv/protocol"
+)
+
+// Tool matching configuration.
+const (
+	toolMatchThreshold = 0.35
+	toolMatchLimit     = 5
+)
+
+var (
+	// Shared embedding model for tool matching.
+	toolEmbedModel *embedding.Model
+	toolEmbedErr   error
+	toolEmbedOnce  sync.Once
+)
+
+// getToolEmbedModel returns the shared embedding model, loading it on first call.
+func getToolEmbedModel() *embedding.Model {
+	toolEmbedOnce.Do(func() {
+		toolEmbedModel, toolEmbedErr = embedding.LoadModel(skills.DefaultModelDir())
+	})
+	return toolEmbedModel
+}
+
+// matchTools finds tools relevant to the user's input from the loaded tools
+// and returns a hint block telling the model to call them.
+func matchTools(input string, tools []protocol.ToolInfo) string {
+	if len(tools) == 0 {
+		return ""
+	}
+
+	model := getToolEmbedModel()
+	if model == nil {
+		return ""
+	}
+
+	// Convert tools to embedding items
+	items := make([]embedding.Item, 0, len(tools))
+	for _, ti := range tools {
+		if ti.Description == "" {
+			continue
+		}
+		searchText := ti.Description
+		if ti.Prompt != "" {
+			searchText += " Usage: " + ti.Prompt
+		}
+		items = append(items, embedding.Item{
+			Name:        ti.Name,
+			Description: searchText,
+		})
+	}
+	if len(items) == 0 {
+		return ""
+	}
+
+	// Build index and match
+	idx, err := embedding.NewIndex(model, items)
+	if err != nil {
+		return ""
+	}
+
+	workflowText := normalizeWorkflow(input).SearchText()
+	workflow := normalizeWorkflow(input)
+	searchInput := input
+	if workflowText != "" {
+		searchInput += " Workflow: " + workflowText
+	}
+
+	results, err := idx.Match(searchInput, toolMatchThreshold, toolMatchLimit)
+	if err != nil {
+		return ""
+	}
+
+	// Apply workflow adjustments
+	for i := range results {
+		results[i].Score += workflowToolAdjustment(results[i].Item.Name, workflow)
+	}
+	sort.SliceStable(results, func(i, j int) bool {
+		return results[i].Score > results[j].Score
+	})
+
+	if len(results) == 0 {
+		return ""
+	}
+
+	var sb strings.Builder
+	sb.WriteString("<tool-hints>\n")
+	sb.WriteString("Relevant tools for this request:\n\n")
+	for _, r := range results {
+		sb.WriteString("→ `")
+		sb.WriteString(r.Item.Name)
+		sb.WriteString("({...})` — ")
+		sb.WriteString(r.Item.Description)
+		sb.WriteString("\n")
+	}
+	sb.WriteString("</tool-hints>\n")
+	return sb.String()
+}

cmd/olliesrv/internal/agent/turn.go

@@ -131,8 +131,13 @@ func (ag *Agent) executeTurn(ctx context.Context, input string) string {
 	if skillContent := matchSkills(input); skillContent != "" {
 		contextParts = append(contextParts, skillContent)
 	}
-	if ag.runtime.ToolServer != nil {
-		if toolHints := matchTools(input); toolHints != "" {
+	if len(ag.runtime.ToolMeta) > 0 {
+		// Convert map to slice for matching
+		tools := make([]protocol.ToolInfo, 0, len(ag.runtime.ToolMeta))
+		for _, ti := range ag.runtime.ToolMeta {
+			tools = append(tools, ti)
+		}
+		if toolHints := matchTools(input, tools); toolHints != "" {
 			contextParts = append(contextParts, toolHints)
 		}
 	}

cmd/toolsrv/internal/server/proc.go

@@ -290,14 +290,7 @@ func (st *State) NewProc(ctx context.Context, payload string, background bool) (
 
 	info, ok := reg.Lookup(aid, toolName)
 	if !ok {
-		// Auto-load if tool exists
-		if err := reg.Load(aid, toolName); err != nil {
-			return "", 0, err // "tool not found: X"
-		}
-		info, _ = reg.Lookup(aid, toolName)
-		if st.OnToolsChanged != nil {
-			st.OnToolsChanged()
-		}
+		return "", 0, fmt.Errorf("tool not loaded: %s (add to autoLoad in agent config)", toolName)
 	}
 
 	// Reject shell calls that invoke a native tool.

embedding/index.go

@@ -0,0 +1,87 @@
+package embedding
+
+import (
+	"fmt"
+	"sort"
+	"sync"
+)
+
+// Item represents something that can be embedded and matched.
+type Item struct {
+	Name        string
+	Description string // text used for embedding
+}
+
+// Index holds precomputed embeddings for semantic matching.
+type Index struct {
+	model *Model
+	items []Item
+	vecs  []Vector
+	mu    sync.RWMutex
+}
+
+// NewIndex creates an index from items using the given embedding model.
+// The model is borrowed, not owned — caller is responsible for its lifecycle.
+func NewIndex(model *Model, items []Item) (*Index, error) {
+	if model == nil {
+		return nil, fmt.Errorf("model is nil")
+	}
+
+	vecs := make([]Vector, len(items))
+	for i, item := range items {
+		vec, err := model.Embed(item.Description)
+		if err != nil {
+			return nil, fmt.Errorf("embed %q: %w", item.Name, err)
+		}
+		vecs[i] = vec
+	}
+
+	return &Index{
+		model: model,
+		items: items,
+		vecs:  vecs,
+	}, nil
+}
+
+// Match returns items matching the query, sorted by relevance.
+// threshold is the minimum cosine similarity (0-1) to include.
+// limit is the maximum number of results (0 for no limit).
+func (idx *Index) Match(query string, threshold float32, limit int) ([]MatchResult, error) {
+	idx.mu.RLock()
+	defer idx.mu.RUnlock()
+
+	if len(idx.items) == 0 {
+		return nil, nil
+	}
+
+	qvec, err := idx.model.Embed(query)
+	if err != nil {
+		return nil, fmt.Errorf("embed query: %w", err)
+	}
+
+	var results []MatchResult
+	for i, item := range idx.items {
+		sim := CosineSimilarity(qvec, idx.vecs[i])
+		if sim >= threshold {
+			results = append(results, MatchResult{
+				Item:  item,
+				Score: sim,
+			})
+		}
+	}
+
+	sort.Slice(results, func(i, j int) bool {
+		return results[i].Score > results[j].Score
+	})
+
+	if limit > 0 && len(results) > limit {
+		results = results[:limit]
+	}
+	return results, nil
+}
+
+// MatchResult holds a matched item and its similarity score.
+type MatchResult struct {
+	Item  Item
+	Score float32
+}

skills/skills.go

@@ -1,4 +1,5 @@
-// Package skills provides skill discovery, embedding, and matching.
+// Package skills provides skill discovery and matching.
+// Skills are markdown knowledge modules with YAML frontmatter.
 package skills
 
 import (
@@ -7,7 +8,6 @@ import (
 	"fmt"
 	"os"
 	"path/filepath"
-	"sort"
 	"strings"
 	"sync"
 
@@ -27,10 +27,16 @@ type Skill struct {
 type Index struct {
 	model  *embedding.Model
 	skills []Skill
-	vecs   []embedding.Vector
+	index  *embedding.Index
 	mu     sync.RWMutex
 }
 
+// MatchResult holds a matched skill and its similarity score.
+type MatchResult struct {
+	Skill Skill
+	Score float32
+}
+
 // NewIndex creates a new skill index with precomputed embeddings.
 // modelDir is the path to the directory containing the ONNX model.
 // skillDirs is a list of directories to scan for skills.
@@ -48,25 +54,6 @@ func NewIndex(modelDir string, skillDirs []string) (*Index, error) {
 	return idx, nil
 }
 
-// NewIndexFromSkills creates an index from pre-loaded skills.
-// Takes ownership of the model.
-func NewIndexFromSkills(model *embedding.Model, skills []Skill) (*Index, error) {
-	idx := &Index{model: model, skills: skills}
-
-	// Compute embeddings
-	vecs := make([]embedding.Vector, len(skills))
-	for i, skill := range skills {
-		vec, err := model.Embed(skill.Description)
-		if err != nil {
-			return nil, fmt.Errorf("embed skill %q: %w", skill.Name, err)
-		}
-		vecs[i] = vec
-	}
-	idx.vecs = vecs
-
-	return idx, nil
-}
-
 // Close releases resources.
 func (idx *Index) Close() error {
 	if idx.model != nil {
@@ -82,41 +69,27 @@ func (idx *Index) Match(query string, threshold float32, limit int) ([]MatchResu
 	idx.mu.RLock()
 	defer idx.mu.RUnlock()
 
-	if len(idx.skills) == 0 {
+	if idx.index == nil {
 		return nil, nil
 	}
 
-	qvec, err := idx.model.Embed(query)
+	results, err := idx.index.Match(query, threshold, limit)
 	if err != nil {
-		return nil, fmt.Errorf("embed query: %w", err)
+		return nil, err
 	}
 
-	var results []MatchResult
-	for i, skill := range idx.skills {
-		sim := embedding.CosineSimilarity(qvec, idx.vecs[i])
-		if sim >= threshold {
-			results = append(results, MatchResult{
-				Skill: skill,
-				Score: sim,
-			})
+	// Convert embedding.MatchResult to MatchResult with full Skill
+	out := make([]MatchResult, len(results))
+	for i, r := range results {
+		// Find the skill by name
+		for _, skill := range idx.skills {
+			if skill.Name == r.Item.Name {
+				out[i] = MatchResult{Skill: skill, Score: r.Score}
+				break
+			}
 		}
 	}
-
-	// Sort by score descending
-	sort.Slice(results, func(i, j int) bool {
-		return results[i].Score > results[j].Score
-	})
-
-	if limit > 0 && len(results) > limit {
-		results = results[:limit]
-	}
-	return results, nil
-}
-
-// MatchResult holds a matched skill and its similarity score.
-type MatchResult struct {
-	Skill Skill
-	Score float32
+	return out, nil
 }
 
 // All returns all indexed skills.
@@ -167,18 +140,23 @@ func (idx *Index) loadSkillsLocked(dirs []string) error {
 		}
 	}
 
-	// Compute embeddings
-	vecs := make([]embedding.Vector, len(skills))
+	// Convert to embedding.Item for the generic index
+	items := make([]embedding.Item, len(skills))
 	for i, skill := range skills {
-		vec, err := idx.model.Embed(skill.Description)
-		if err != nil {
-			return fmt.Errorf("embed skill %q: %w", skill.Name, err)
+		items[i] = embedding.Item{
+			Name:        skill.Name,
+			Description: skill.Description,
 		}
-		vecs[i] = vec
+	}
+
+	// Build embedding index
+	embIdx, err := embedding.NewIndex(idx.model, items)
+	if err != nil {
+		return err
 	}
 
 	idx.skills = skills
-	idx.vecs = vecs
+	idx.index = embIdx
 	return nil
 }