Six tools for intent-aware search, pattern-based scanning, structural hole detection, stacktrace analysis, temporal history, and multi-repository federation.
Intent-aware semantic code search. Finds code by purpose, not text pattern. Combines keyword matching, graph activation (PageRank), and trigram similarity for ranking.
Unlike activate (which propagates signal through edges), seek scores every node independently against the query, making it better for finding specific code when you know what it does but not where it lives.
| Parameter | Type | Required | Default | Description |
|---|
query | string | Yes | – | Natural language description of what the agent is looking for. Example: "code that validates user credentials". |
agent_id | string | Yes | – | Calling agent identifier. |
top_k | integer | No | 20 | Maximum results to return. |
scope | string | No | – | File path prefix to limit search scope. Example: "backend/". None = entire graph. |
node_types | string[] | No | [] | Filter by node type: "function", "class", "struct", "module", "file". Empty = all types. |
min_score | number | No | 0.1 | Minimum combined score threshold. Range: 0.0 to 1.0. |
graph_rerank | boolean | No | true | Whether to run graph re-ranking (PageRank weighting) on candidates. Disable for pure text matching. |
combined = keyword_match * 0.6 + graph_activation * 0.3 + trigram * 0.1
V2 upgrade path will replace keyword matching with real embeddings (fastembed-rs + jina-embeddings-v2-base-code).
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "m1nd.seek",
"arguments": {
"agent_id": "orchestrator",
"query": "code that validates user credentials",
"top_k": 5,
"node_types": ["function", "class"]
}
}
}
{
"query": "code that validates user credentials",
"results": [
{
"node_id": "file::auth_discovery.py::fn::validate_credentials",
"label": "validate_credentials",
"type": "function",
"score": 0.87,
"score_breakdown": {
"embedding_similarity": 0.92,
"graph_activation": 0.78,
"temporal_recency": 0.65
},
"intent_summary": "Validates user credentials against provider store",
"file_path": "backend/auth_discovery.py",
"line_start": 45,
"line_end": 82,
"connections": [
{ "node_id": "file::principal_registry.py", "label": "principal_registry.py", "relation": "calls" }
]
}
],
"total_candidates_scanned": 9767,
"embeddings_used": false,
"elapsed_ms": 25.0
}
- “Find the code that does X” – when you know the purpose, not the filename
- Codebase onboarding – exploring unfamiliar code by intent
- Pre-modification search – find all code related to a feature before changing it
m1nd.activate – graph-propagation search (better for exploring neighborhoods)m1nd.scan – pattern-based structural analysis (finds anti-patterns, not features)
Pattern-aware structural code analysis with graph-validated findings. Detects structural issues using predefined patterns, then validates each finding against the graph to filter false positives. Works across file boundaries.
| Parameter | Type | Required | Default | Description |
|---|
pattern | string | Yes | – | Pattern ID or custom pattern string. Built-in patterns: "error_handling", "resource_cleanup", "api_surface", "state_mutation", "concurrency", "auth_boundary", "test_coverage", "dependency_injection". |
agent_id | string | Yes | – | Calling agent identifier. |
scope | string | No | – | File path prefix to limit scan scope. |
severity_min | number | No | 0.3 | Minimum severity threshold. Range: 0.0 to 1.0. |
graph_validate | boolean | No | true | Validate findings against graph edges (cross-file analysis). Disable for raw pattern matching only. |
limit | integer | No | 50 | Maximum findings to return. |
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "m1nd.scan",
"arguments": {
"agent_id": "orchestrator",
"pattern": "error_handling",
"scope": "backend/",
"severity_min": 0.5
}
}
}
{
"pattern": "error_handling",
"findings": [
{
"pattern": "error_handling",
"status": "confirmed",
"severity": 0.78,
"node_id": "file::worker.py::fn::spawn_agent",
"label": "spawn_agent",
"file_path": "backend/worker.py",
"line": 89,
"message": "Bare except clause catches all exceptions including KeyboardInterrupt",
"graph_context": [
{ "node_id": "file::process_manager.py", "label": "process_manager.py", "relation": "calls" }
]
}
],
"files_scanned": 77,
"total_matches_raw": 23,
"total_matches_validated": 8,
"elapsed_ms": 150.0
}
| Status | Meaning |
|---|
"confirmed" | Graph validation confirms the issue is real |
"mitigated" | The issue exists but is handled by a related module |
"false_positive" | Graph context shows the pattern match is not actually an issue |
- Code quality audit – scan for anti-patterns across the codebase
- Security review – use
"auth_boundary" to find auth bypass paths
- Pre-deploy check – scan for
"error_handling" and "resource_cleanup" issues
- Test gaps – use
"test_coverage" to find untested code
Detect structural holes and missing connections. Given a topic query, finds areas where the graph suggests something should exist but does not. Identifies absent abstractions, missing connections, and incomplete patterns.
| Parameter | Type | Required | Default | Description |
|---|
query | string | Yes | – | Search query to find structural holes around. |
agent_id | string | Yes | – | Calling agent identifier. |
min_sibling_activation | number | No | 0.3 | Minimum sibling activation threshold. Siblings with activation below this are not considered for hole detection. |
{
"jsonrpc": "2.0",
"id": 3,
"method": "tools/call",
"params": {
"name": "m1nd.missing",
"arguments": {
"agent_id": "orchestrator",
"query": "database connection pooling",
"min_sibling_activation": 0.3
}
}
}
{
"query": "database connection pooling",
"holes": [
{
"node_id": "structural_hole_1",
"label": "connection lifecycle",
"type": "structural_hole",
"reason": "No dedicated connection pool abstraction -- 4 adjacent modules manage connections independently"
},
{
"node_id": "structural_hole_2",
"label": "pool metrics",
"type": "structural_hole",
"reason": "No pool health monitoring -- 3 adjacent modules expose metrics but pool does not"
}
],
"total_holes": 9,
"elapsed_ms": 67.0
}
- Gap analysis – “what am I missing?” before implementing a feature
- Pre-spec – identify areas that need design before building
- Architecture review – find missing abstractions or connections
- Feature completeness – after building, check for structural holes around the feature
m1nd.activate – activate with include_structural_holes: true for inline hole detectionm1nd.hypothesize – test a specific claim about missing structure
Map runtime errors to structural root causes via stacktrace analysis. Parses the stacktrace, maps frames to graph nodes, and scores each node’s suspiciousness using trace depth, modification recency, and centrality. Also finds co-change suspects (files modified around the same time as the top suspect).
| Parameter | Type | Required | Default | Description |
|---|
error_text | string | Yes | – | Full error output (stacktrace + error message). |
agent_id | string | Yes | – | Calling agent identifier. |
language | string | No | – | Language hint: "python", "rust", "typescript", "javascript", "go". Auto-detected if omitted. |
window_hours | number | No | 24.0 | Temporal window (hours) for co-change suspect scan. |
top_k | integer | No | 10 | Max suspects to return. |
{
"jsonrpc": "2.0",
"id": 4,
"method": "tools/call",
"params": {
"name": "m1nd.trace",
"arguments": {
"agent_id": "orchestrator",
"error_text": "Traceback (most recent call last):\n File \"backend/handler.py\", line 234, in handle_message\n File \"backend/pool.py\", line 89, in acquire\n File \"backend/worker.py\", line 156, in submit\nTimeoutError: pool exhausted",
"language": "python",
"top_k": 5
}
}
}
{
"language_detected": "python",
"error_type": "TimeoutError",
"error_message": "pool exhausted",
"frames_parsed": 3,
"frames_mapped": 3,
"suspects": [
{
"node_id": "file::worker.py::fn::submit",
"label": "submit",
"type": "function",
"suspiciousness": 0.91,
"signals": { "trace_depth_score": 1.0, "recency_score": 0.85, "centrality_score": 0.88 },
"file_path": "backend/worker.py",
"line_start": 150,
"line_end": 175,
"related_callers": ["pool.py::acquire"]
},
{
"node_id": "file::pool.py::fn::acquire",
"label": "acquire",
"type": "function",
"suspiciousness": 0.78,
"signals": { "trace_depth_score": 0.67, "recency_score": 0.72, "centrality_score": 0.65 },
"file_path": "backend/pool.py",
"line_start": 80,
"line_end": 110,
"related_callers": ["handler.py::handle_message"]
}
],
"co_change_suspects": [
{ "node_id": "file::config.py", "label": "config.py", "modified_at": 1710295000.0, "reason": "Modified within 2h of top suspect" }
],
"causal_chain": ["worker.py::submit", "pool.py::acquire", "handler.py::handle_message"],
"fix_scope": {
"files_to_inspect": ["backend/worker.py", "backend/pool.py", "backend/config.py"],
"estimated_blast_radius": 23,
"risk_level": "medium"
},
"unmapped_frames": [],
"elapsed_ms": 3.5
}
| Signal | Weight | Description |
|---|
trace_depth_score | High | 1.0 = deepest frame (most specific); decays linearly |
recency_score | Medium | Exponential decay from last modification time |
centrality_score | Medium | Normalized PageRank centrality |
- Bug investigation – paste an error and get ranked suspects
- Root cause analysis – the causal chain shows the error propagation path
- Fix scoping –
fix_scope tells you which files to inspect and the risk level
Git-based temporal history for a node. Returns the change history, co-change partners, velocity, stability score, and churn data for a specific file or module.
| Parameter | Type | Required | Default | Description |
|---|
node | string | Yes | – | Node external_id. Example: "file::backend/handler.py". |
agent_id | string | Yes | – | Calling agent identifier. |
depth | string | No | "30d" | Time depth. Values: "7d", "30d", "90d", "all". |
include_co_changes | boolean | No | true | Include co-changed files with coupling scores. |
include_churn | boolean | No | true | Include lines added/deleted churn data. |
top_k | integer | No | 10 | Max co-change partners to return. |
{
"jsonrpc": "2.0",
"id": 5,
"method": "tools/call",
"params": {
"name": "m1nd.timeline",
"arguments": {
"agent_id": "orchestrator",
"node": "file::backend/handler.py",
"depth": "30d",
"top_k": 5
}
}
}
{
"node": "file::backend/handler.py",
"depth": "30d",
"changes": [
{
"date": "2026-03-10",
"commit": "a1b2c3d",
"author": "cosmophonix",
"delta": "+45/-12",
"co_changed": ["parser.py", "chat_routes.py"]
},
{
"date": "2026-03-05",
"commit": "e4f5g6h",
"author": "cosmophonix",
"delta": "+120/-30",
"co_changed": ["pool.py", "worker.py"]
}
],
"co_changed_with": [
{ "file": "parser.py", "times": 8, "coupling_degree": 0.72 },
{ "file": "chat_routes.py", "times": 6, "coupling_degree": 0.55 },
{ "file": "pool.py", "times": 4, "coupling_degree": 0.38 }
],
"velocity": "accelerating",
"stability_score": 0.35,
"pattern": "churning",
"total_churn": { "lines_added": 580, "lines_deleted": 120 },
"commit_count_in_window": 12,
"elapsed_ms": 45.0
}
| Value | Meaning |
|---|
"accelerating" | Change frequency is increasing |
"decelerating" | Change frequency is decreasing |
"stable" | Consistent change rate |
| Value | Meaning |
|---|
"expanding" | Growing (net positive churn) |
"shrinking" | Reducing (net negative churn) |
"churning" | High add+delete with little net growth |
"dormant" | Few or no changes in the window |
"stable" | Small, consistent changes |
- Hotspot detection – find files that change too frequently (stability_score < 0.3)
- Co-change discovery – find files that always change together (coupling_degree > 0.6)
- Refactoring signals – churning files may need redesign
Ingest multiple repositories into a unified federated graph with automatic cross-repo edge detection. After federation, all existing query tools (activate, impact, why, etc.) traverse cross-repo edges automatically.
Node IDs in the federated graph use {repo_name}::file::path format.
| Parameter | Type | Required | Default | Description |
|---|
agent_id | string | Yes | – | Calling agent identifier. |
repos | object[] | Yes | – | List of repositories to federate. Each object has: name (string, required – namespace prefix), path (string, required – absolute path), adapter (string, default "code"). |
detect_cross_repo_edges | boolean | No | true | Auto-detect cross-repo edges: config, API, import, type, deployment, MCP contract. |
incremental | boolean | No | false | Only re-ingest repos that changed since last federation. |
| Edge Type | Description |
|---|
shared_config | Two repos reference the same configuration key |
api_contract | One repo’s API client matches another’s API server |
package_dep | Direct package dependency |
shared_type | Same type/interface definition used across repos |
deployment_dep | Deployment configuration dependency |
mcp_contract | MCP tool consumer/provider relationship |
{
"jsonrpc": "2.0",
"id": 6,
"method": "tools/call",
"params": {
"name": "m1nd.federate",
"arguments": {
"agent_id": "orchestrator",
"repos": [
{ "name": "backend", "path": "/project/backend" },
{ "name": "frontend", "path": "/project/frontend" },
{ "name": "mcp-server", "path": "/project/mcp-server", "adapter": "code" }
],
"detect_cross_repo_edges": true,
"incremental": false
}
}
}
{
"repos_ingested": [
{ "name": "backend", "path": "/project/backend", "node_count": 9767, "edge_count": 26557, "from_cache": false, "ingest_ms": 910.0 },
{ "name": "frontend", "path": "/project/frontend", "node_count": 1200, "edge_count": 3500, "from_cache": false, "ingest_ms": 320.0 },
{ "name": "mcp-server", "path": "/project/mcp-server", "node_count": 250, "edge_count": 680, "from_cache": false, "ingest_ms": 85.0 }
],
"total_nodes": 11217,
"total_edges": 30737,
"cross_repo_edges": [
{
"source_repo": "frontend",
"target_repo": "backend",
"source_node": "frontend::file::src/lib/apiConfig.ts",
"target_node": "backend::file::main.py",
"edge_type": "api_contract",
"relation": "calls_api",
"weight": 0.85,
"causal_strength": 0.72
},
{
"source_repo": "mcp-server",
"target_repo": "backend",
"source_node": "mcp-server::file::src/mcp-server.js",
"target_node": "backend::file::main.py",
"edge_type": "mcp_contract",
"relation": "calls_api",
"weight": 0.78,
"causal_strength": 0.65
}
],
"cross_repo_edge_count": 18203,
"incremental": false,
"skipped_repos": [],
"elapsed_ms": 1315.0
}
- Multi-repo projects – analyze dependencies across frontend, backend, and infrastructure repos
- Monorepo decomposition – understand how packages depend on each other
- API impact analysis – find which repos are affected by an API change
m1nd.ingest – single-repo ingestionm1nd.impact – blast radius analysis (works across federated repos)m1nd.why – path explanation (traverses cross-repo edges)