omega_brain_report
Generate an audit report to inspect your agent's trust and governance layer, showing SEAL chain entries, Cortex verdicts, and vault statistics.
Instructions
Generates a human-readable audit report showing SEAL chain entries, Cortex verdicts, and vault statistics. Use this to inspect the trust and governance layer; use omega_brain_status for a quick health summary instead. Returns formatted text report with sections: seal_tail, cortex_verdicts, vault_stats, session_health.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lines | No | Number of recent SEAL ledger entries to include, between 1 and 100. |
Implementation Reference
- omega_brain_mcp_standalone.py:1334-1395 (handler)The main handler function for the 'omega_brain_report' tool. It queries the SEAL ledger tail, Cortex verdict breakdown, VERITAS RAG scores, and vault statistics, then composes a formatted text audit report returned to the caller.
elif name == "omega_brain_report": n = int(arguments.get("lines", 10)) conn = _db() # SEAL chain tail ledger_rows = conn.execute( "SELECT event_type, hash, timestamp FROM ledger ORDER BY id DESC LIMIT ?", (n,) ).fetchall() # Cortex verdict breakdown blocked = conn.execute("SELECT COUNT(*) FROM ledger WHERE event_type='cortex_steer_block'").fetchone()[0] steered = conn.execute("SELECT COUNT(*) FROM ledger WHERE event_type='cortex_steer_corrected'").fetchone()[0] approved = conn.execute("SELECT COUNT(*) FROM ledger WHERE event_type='cortex_check' OR event_type='omega_execute'").fetchone()[0] # VERITAS: last few RAG queries from tape rag_scores = [] tape_rows = conn.execute( "SELECT payload FROM tape ORDER BY id DESC LIMIT 20" ).fetchall() for row in tape_rows: try: p = json.loads(row["payload"]) if "veritas_score" in p: rag_scores.append(float(p["veritas_score"])) except Exception: pass # Vault stats sessions = conn.execute("SELECT COUNT(*) FROM sessions").fetchone()[0] entries = conn.execute("SELECT COUNT(*) FROM entries").fetchone()[0] frags = conn.execute("SELECT COUNT(*) FROM fragments").fetchone()[0] ledger_total = conn.execute("SELECT COUNT(*) FROM ledger").fetchone()[0] conn.close() avg_veritas = round(sum(rag_scores)/len(rag_scores), 4) if rag_scores else None seal_tail = "\n".join( f" {r['timestamp'][:19]} {r['event_type']:<30} {r['hash'][:16]}..." for r in reversed(ledger_rows) ) or " (no entries yet)" report = ( f"═══════════════════════════════════════════════════\n" f" OMEGA BRAIN AUDIT REPORT\n" f" Session: {_SESSION_ID[:16]}... Engine: {_EMBED_ENGINE}\n" f" Generated: {datetime.now(timezone.utc).isoformat()[:19]}Z\n" f"═══════════════════════════════════════════════════\n\n" f"CORTEX VERDICTS (all time)\n" f" Blocked : {blocked}\n" f" Steered : {steered}\n" f" Approved : {approved}\n\n" f"VERITAS\n" f" Avg score (last {len(rag_scores)} queries): {avg_veritas if avg_veritas is not None else 'n/a'}\n\n" f"VAULT\n" f" Sessions: {sessions} Entries: {entries} Fragments: {frags}\n" f" Total SEAL entries: {ledger_total}\n\n" f"SEAL CHAIN TAIL (last {n})\n" f" {'TIMESTAMP':<20} {'EVENT':<30} HASH\n" f"{seal_tail}\n\n" f"HANDOFF: {'PRESENT ' + chr(0x2713) if _STARTUP_PRELOAD.get('handoff_present') else 'not found'}\n" f"═══════════════════════════════════════════════════" ) return [TextContent(type="text", text=report)] - The MCP Tool definition for omega_brain_report, declaring its name, description, and inputSchema (with a single optional 'lines' integer parameter defaulting to 10).
Tool(name="omega_brain_report", description=( "Generates a human-readable audit report showing SEAL chain entries, Cortex verdicts, and vault statistics. " "Use this to inspect the trust and governance layer; use omega_brain_status for a quick health summary instead. " "Returns formatted text report with sections: seal_tail, cortex_verdicts, vault_stats, session_health." ), inputSchema={"type": "object", "properties": { "lines": { "type": "integer", "description": "Number of recent SEAL ledger entries to include, between 1 and 100.", "default": 10 } }}), - omega_brain_mcp_standalone.py:968-1195 (registration)The tool is registered as an MCP tool via the @app.list_tools() decorator, which returns it in the list alongside all other Omega Brain tools.
@app.list_tools() async def list_tools(): return [ Tool(name="omega_preload_context", description=( "Loads episodic context for a new task by querying the RAG store, vault history, and any sealed handoff. " "Call this once at the start of every new task before doing any work. " "Returns JSON with fields: rag_matches, vault_history, handoff, continuity_type (CONTINUATION | CONTEXT_SWITCH | FRESH_START)." ), inputSchema={"type": "object", "properties": { "task": { "type": "string", "description": "Natural-language description of the task to load context for, e.g. 'Fix authentication bug in login module'." } }, "required": ["task"]}), Tool(name="omega_rag_query", description=( "Searches the provenance RAG store using semantic similarity and returns ranked text fragments. " "Use this for meaning-based search; use omega_vault_search instead for exact keyword matching. " "Returns JSON array of {fragment, similarity_score, quality_score, source, tier}." ), inputSchema={"type": "object", "properties": { "query": { "type": "string", "description": "Natural-language search query, e.g. 'How was the authentication module designed?'." }, "top_k": { "type": "integer", "default": 5, "description": "Maximum number of results to return, between 1 and 50." } }, "required": ["query"]}), Tool(name="omega_ingest", description=( "Stores a new knowledge fragment in the provenance RAG store with source and evidence tier metadata. " "Use this to persist decisions, patterns, or findings for future retrieval via omega_rag_query. " "Returns JSON with fields: fragment_id, stored (boolean), timestamp." ), inputSchema={"type": "object", "properties": { "content": { "type": "string", "description": "Text content to store, e.g. 'Switched from Poetry to setuptools for pyproject.toml compatibility'." }, "source": { "type": "string", "description": "Origin identifier for provenance tracking, e.g. 'code-review', 'user-session', 'documentation'." }, "tier": { "type": "string", "description": "Evidence confidence tier: A (verified/reproducible), B (reliable), C (single source), D (unverified).", "default": "B", "enum": ["A", "B", "C", "D"] } }, "required": ["content"]}), Tool(name="omega_vault_search", description=( "Searches the vault database using exact keyword matching via SQLite FTS5. " "Use this for precise keyword lookups; use omega_rag_query instead for semantic/meaning-based search. " "Returns JSON array of matching vault entries with timestamps and session context." ), inputSchema={"type": "object", "properties": { "query": { "type": "string", "description": "FTS5 keyword query supporting AND, OR, NOT, and quoted phrases, e.g. '\"deploy production\" NOT staging'." } }, "required": ["query"]}), Tool(name="omega_cortex_check", description=( "Read-only alignment gate that measures semantic similarity between a proposed action and the task baseline. " "Use this to check alignment before high-impact operations without modifying any arguments; " "use omega_cortex_steer instead if you want automatic argument correction. " "Returns JSON with fields: approved (boolean), similarity (float 0-1), verdict (APPROVED | BLOCKED)." ), inputSchema={"type": "object", "properties": { "tool": { "type": "string", "description": "Name of the tool to check alignment for, e.g. 'omega_ingest'." }, "args": { "type": "object", "description": "The proposed arguments for the tool call, serialized as a JSON object." }, "baseline_prompt": { "type": "string", "description": "Task baseline describing the intended operation, e.g. 'Refactoring the auth module for OAuth2 support'." } }, "required": ["tool", "args", "baseline_prompt"]}), Tool(name="omega_cortex_steer", description=( "Alignment gate with automatic argument correction for drifting tool calls. " "Use this instead of omega_cortex_check when you want arguments auto-corrected toward the baseline; " "blocks hard if similarity < 0.45, steers if 0.45-0.65, passes unchanged if > 0.65. " "Returns JSON with fields: similarity (float), steered_args (object), corrections (array), verdict (PASSED | STEERED | BLOCKED)." ), inputSchema={"type": "object", "properties": { "tool": { "type": "string", "description": "Name of the tool whose arguments may need correction, e.g. 'omega_seal_run'." }, "args": { "type": "object", "description": "The original arguments that may be drifting from baseline. Will be corrected if in the steering range." }, "baseline_prompt": { "type": "string", "description": "Task baseline to steer toward, e.g. 'Deploying hotfix to staging environment'." } }, "required": ["tool", "args", "baseline_prompt"]}), Tool(name="omega_seal_run", description=( "Appends a tamper-proof entry to the SEAL (Secure Evidence Audit Ledger) SHA-256 hash chain. " "Use this to create an immutable audit record of significant events, decisions, or state changes. " "Returns JSON with fields: seal_hash (hex string), chain_position (integer), timestamp (ISO 8601)." ), inputSchema={"type": "object", "properties": { "context": { "type": "object", "description": "Structured event metadata, e.g. {\"action\": \"deploy\", \"target\": \"production\", \"version\": \"2.1.0\"}." }, "response": { "type": "string", "description": "Outcome text to seal into the immutable ledger, e.g. 'Deployment succeeded with zero errors'." } }, "required": ["context", "response"]}), Tool(name="omega_log_session", description=( "Writes a complete session record to the vault for cross-session persistence. " "Use this at the end of a work session to record what was done; data is retrievable via omega_vault_search. " "Returns JSON with fields: session_id, stored (boolean), entry_count (integer)." ), inputSchema={"type": "object", "properties": { "session_id": { "type": "string", "description": "Unique session identifier. Auto-generated if omitted." }, "task": { "type": "string", "description": "Description of the task completed, e.g. 'Migrated database schema to v3'." }, "decisions": { "type": "array", "items": {"type": "string"}, "description": "Key decisions made, e.g. ['Used Alembic for migrations', 'Kept backward compatibility']." }, "files_modified": { "type": "array", "items": {"type": "string"}, "description": "File paths changed, e.g. ['src/models.py', 'alembic/versions/001.py']." } }, "required": ["task"]}), Tool(name="omega_write_handoff", description=( "Creates a SHA-256 sealed handoff document that auto-loads on the next server restart via omega://session/preload. " "Use this at the end of a session to ensure seamless context continuity for the next session. " "Returns JSON with fields: handoff_hash (hex string), file_path (string)." ), inputSchema={"type": "object", "properties": { "task": { "type": "string", "description": "Task title for the handoff, e.g. 'OAuth2 migration phase 2'." }, "summary": { "type": "string", "description": "Concise summary of progress and current state for the next session." }, "decisions": { "type": "array", "items": {"type": "string"}, "description": "Key decisions the next session should know about." }, "files_modified": { "type": "array", "items": {"type": "string"}, "description": "Files changed during this session." }, "next_steps": { "type": "array", "items": {"type": "string"}, "description": "Ordered list of recommended next actions." }, "conversation_id": { "type": "string", "description": "Optional external conversation tracking ID." } }, "required": ["task", "summary"]}), Tool(name="omega_execute", description=( "Cortex-governed execution wrapper that checks alignment, steers if needed, executes, and auto-logs to the SEAL chain. " "Use this as the default way to invoke any Omega Brain tool with full governance; " "only wraps Omega Brain tools — external tools are returned with steered_args for manual invocation. " "Returns JSON with fields: result (object), cortex_verdict (string), seal_hash (hex string)." ), inputSchema={"type": "object", "properties": { "tool": { "type": "string", "description": "Omega Brain tool name to execute, e.g. 'omega_ingest', 'omega_rag_query', 'omega_seal_run'." }, "args": { "type": "object", "description": "Arguments for the target tool. May be steered by the Cortex before execution." }, "baseline": { "type": "string", "description": "Task baseline for the Cortex alignment check, e.g. 'Ingesting code review findings'." } }, "required": ["tool", "args", "baseline"]}), Tool(name="omega_brain_report", description=( "Generates a human-readable audit report showing SEAL chain entries, Cortex verdicts, and vault statistics. " "Use this to inspect the trust and governance layer; use omega_brain_status for a quick health summary instead. " "Returns formatted text report with sections: seal_tail, cortex_verdicts, vault_stats, session_health." ), inputSchema={"type": "object", "properties": { "lines": { "type": "integer", "description": "Number of recent SEAL ledger entries to include, between 1 and 100.", "default": 10 } }}), Tool(name="omega_brain_status", description=( "Returns a quick health summary of all Omega Brain subsystems as structured JSON. " "Use this for a fast status check; use omega_brain_report for a detailed audit report instead. " "Returns JSON with fields: vault_sessions (int), vault_entries (int), rag_fragments (int), " "seal_entries (int), session_id (string), uptime_seconds (float), call_count (int)." ), inputSchema={"type": "object", "properties": {}}), ] + (_veritas_build_tools() if HAS_BUILD_GATES else []) - omega_brain_mcp_standalone.py:968-1195 (registration)The call_tool handler dispatches the 'omega_brain_report' name to the handler block at line 1334.
@app.list_tools() async def list_tools(): return [ Tool(name="omega_preload_context", description=( "Loads episodic context for a new task by querying the RAG store, vault history, and any sealed handoff. " "Call this once at the start of every new task before doing any work. " "Returns JSON with fields: rag_matches, vault_history, handoff, continuity_type (CONTINUATION | CONTEXT_SWITCH | FRESH_START)." ), inputSchema={"type": "object", "properties": { "task": { "type": "string", "description": "Natural-language description of the task to load context for, e.g. 'Fix authentication bug in login module'." } }, "required": ["task"]}), Tool(name="omega_rag_query", description=( "Searches the provenance RAG store using semantic similarity and returns ranked text fragments. " "Use this for meaning-based search; use omega_vault_search instead for exact keyword matching. " "Returns JSON array of {fragment, similarity_score, quality_score, source, tier}." ), inputSchema={"type": "object", "properties": { "query": { "type": "string", "description": "Natural-language search query, e.g. 'How was the authentication module designed?'." }, "top_k": { "type": "integer", "default": 5, "description": "Maximum number of results to return, between 1 and 50." } }, "required": ["query"]}), Tool(name="omega_ingest", description=( "Stores a new knowledge fragment in the provenance RAG store with source and evidence tier metadata. " "Use this to persist decisions, patterns, or findings for future retrieval via omega_rag_query. " "Returns JSON with fields: fragment_id, stored (boolean), timestamp." ), inputSchema={"type": "object", "properties": { "content": { "type": "string", "description": "Text content to store, e.g. 'Switched from Poetry to setuptools for pyproject.toml compatibility'." }, "source": { "type": "string", "description": "Origin identifier for provenance tracking, e.g. 'code-review', 'user-session', 'documentation'." }, "tier": { "type": "string", "description": "Evidence confidence tier: A (verified/reproducible), B (reliable), C (single source), D (unverified).", "default": "B", "enum": ["A", "B", "C", "D"] } }, "required": ["content"]}), Tool(name="omega_vault_search", description=( "Searches the vault database using exact keyword matching via SQLite FTS5. " "Use this for precise keyword lookups; use omega_rag_query instead for semantic/meaning-based search. " "Returns JSON array of matching vault entries with timestamps and session context." ), inputSchema={"type": "object", "properties": { "query": { "type": "string", "description": "FTS5 keyword query supporting AND, OR, NOT, and quoted phrases, e.g. '\"deploy production\" NOT staging'." } }, "required": ["query"]}), Tool(name="omega_cortex_check", description=( "Read-only alignment gate that measures semantic similarity between a proposed action and the task baseline. " "Use this to check alignment before high-impact operations without modifying any arguments; " "use omega_cortex_steer instead if you want automatic argument correction. " "Returns JSON with fields: approved (boolean), similarity (float 0-1), verdict (APPROVED | BLOCKED)." ), inputSchema={"type": "object", "properties": { "tool": { "type": "string", "description": "Name of the tool to check alignment for, e.g. 'omega_ingest'." }, "args": { "type": "object", "description": "The proposed arguments for the tool call, serialized as a JSON object." }, "baseline_prompt": { "type": "string", "description": "Task baseline describing the intended operation, e.g. 'Refactoring the auth module for OAuth2 support'." } }, "required": ["tool", "args", "baseline_prompt"]}), Tool(name="omega_cortex_steer", description=( "Alignment gate with automatic argument correction for drifting tool calls. " "Use this instead of omega_cortex_check when you want arguments auto-corrected toward the baseline; " "blocks hard if similarity < 0.45, steers if 0.45-0.65, passes unchanged if > 0.65. " "Returns JSON with fields: similarity (float), steered_args (object), corrections (array), verdict (PASSED | STEERED | BLOCKED)." ), inputSchema={"type": "object", "properties": { "tool": { "type": "string", "description": "Name of the tool whose arguments may need correction, e.g. 'omega_seal_run'." }, "args": { "type": "object", "description": "The original arguments that may be drifting from baseline. Will be corrected if in the steering range." }, "baseline_prompt": { "type": "string", "description": "Task baseline to steer toward, e.g. 'Deploying hotfix to staging environment'." } }, "required": ["tool", "args", "baseline_prompt"]}), Tool(name="omega_seal_run", description=( "Appends a tamper-proof entry to the SEAL (Secure Evidence Audit Ledger) SHA-256 hash chain. " "Use this to create an immutable audit record of significant events, decisions, or state changes. " "Returns JSON with fields: seal_hash (hex string), chain_position (integer), timestamp (ISO 8601)." ), inputSchema={"type": "object", "properties": { "context": { "type": "object", "description": "Structured event metadata, e.g. {\"action\": \"deploy\", \"target\": \"production\", \"version\": \"2.1.0\"}." }, "response": { "type": "string", "description": "Outcome text to seal into the immutable ledger, e.g. 'Deployment succeeded with zero errors'." } }, "required": ["context", "response"]}), Tool(name="omega_log_session", description=( "Writes a complete session record to the vault for cross-session persistence. " "Use this at the end of a work session to record what was done; data is retrievable via omega_vault_search. " "Returns JSON with fields: session_id, stored (boolean), entry_count (integer)." ), inputSchema={"type": "object", "properties": { "session_id": { "type": "string", "description": "Unique session identifier. Auto-generated if omitted." }, "task": { "type": "string", "description": "Description of the task completed, e.g. 'Migrated database schema to v3'." }, "decisions": { "type": "array", "items": {"type": "string"}, "description": "Key decisions made, e.g. ['Used Alembic for migrations', 'Kept backward compatibility']." }, "files_modified": { "type": "array", "items": {"type": "string"}, "description": "File paths changed, e.g. ['src/models.py', 'alembic/versions/001.py']." } }, "required": ["task"]}), Tool(name="omega_write_handoff", description=( "Creates a SHA-256 sealed handoff document that auto-loads on the next server restart via omega://session/preload. " "Use this at the end of a session to ensure seamless context continuity for the next session. " "Returns JSON with fields: handoff_hash (hex string), file_path (string)." ), inputSchema={"type": "object", "properties": { "task": { "type": "string", "description": "Task title for the handoff, e.g. 'OAuth2 migration phase 2'." }, "summary": { "type": "string", "description": "Concise summary of progress and current state for the next session." }, "decisions": { "type": "array", "items": {"type": "string"}, "description": "Key decisions the next session should know about." }, "files_modified": { "type": "array", "items": {"type": "string"}, "description": "Files changed during this session." }, "next_steps": { "type": "array", "items": {"type": "string"}, "description": "Ordered list of recommended next actions." }, "conversation_id": { "type": "string", "description": "Optional external conversation tracking ID." } }, "required": ["task", "summary"]}), Tool(name="omega_execute", description=( "Cortex-governed execution wrapper that checks alignment, steers if needed, executes, and auto-logs to the SEAL chain. " "Use this as the default way to invoke any Omega Brain tool with full governance; " "only wraps Omega Brain tools — external tools are returned with steered_args for manual invocation. " "Returns JSON with fields: result (object), cortex_verdict (string), seal_hash (hex string)." ), inputSchema={"type": "object", "properties": { "tool": { "type": "string", "description": "Omega Brain tool name to execute, e.g. 'omega_ingest', 'omega_rag_query', 'omega_seal_run'." }, "args": { "type": "object", "description": "Arguments for the target tool. May be steered by the Cortex before execution." }, "baseline": { "type": "string", "description": "Task baseline for the Cortex alignment check, e.g. 'Ingesting code review findings'." } }, "required": ["tool", "args", "baseline"]}), Tool(name="omega_brain_report", description=( "Generates a human-readable audit report showing SEAL chain entries, Cortex verdicts, and vault statistics. " "Use this to inspect the trust and governance layer; use omega_brain_status for a quick health summary instead. " "Returns formatted text report with sections: seal_tail, cortex_verdicts, vault_stats, session_health." ), inputSchema={"type": "object", "properties": { "lines": { "type": "integer", "description": "Number of recent SEAL ledger entries to include, between 1 and 100.", "default": 10 } }}), Tool(name="omega_brain_status", description=( "Returns a quick health summary of all Omega Brain subsystems as structured JSON. " "Use this for a fast status check; use omega_brain_report for a detailed audit report instead. " "Returns JSON with fields: vault_sessions (int), vault_entries (int), rag_fragments (int), " "seal_entries (int), session_id (string), uptime_seconds (float), call_count (int)." ), inputSchema={"type": "object", "properties": {}}), ] + (_veritas_build_tools() if HAS_BUILD_GATES else [])