Use this file to discover all available pages before exploring further.
For LLM agents: documentation index at /llms.txt, full text at /llms-full.txt. Append .md to any page URL for plain markdown.
The Web Agent is an AI assistant built into AnomalyArmor’s Intelligence page. It has access to 30+ tools across 9 domains and can chain them together to investigate issues, set up monitoring, manage alerts, and answer questions about your data.
You: Why is the orders dashboard broken?Agent: Let me investigate...[Tool: list_schema_changes > gold.fact_orders] Found: discount_pct column removed, Tuesday 4:12 PM[Tool: check_freshness > gold.fact_orders] Status: FRESH (last update 12 minutes ago)[Tool: get_lineage > gold.fact_orders] Upstream: staging.orders_raw Downstream: analytics.order_summary, reporting.daily_revenue[Tool: list_schema_changes > staging.orders_raw] Found: discount_pct column removed, Tuesday 3:47 PMThe dashboard is broken because the discount_pct column was removedfrom gold.fact_orders on Tuesday at 4:12 PM.Root cause: The column was first removed from staging.orders_raw at3:47 PM, then the ETL propagated the removal downstream.2 views reference this column:- analytics.order_summary- reporting.daily_revenueFreshness is normal, so the table is still updating. The issue isthe missing column, not stale data.
The agent called 4 tools across 3 domains (schema drift, freshness, lineage) to build a complete diagnosis from a single question.
Create metrics and validity rules. The agent asks for confirmation before creating anything.
You: Add null checks on all email columns across my tablesAgent: I found email columns in 4 tables: - gold.dim_customer.email (current null rate: 12.4%) - silver.silver_customers.email_address (current: 0.4%) - raw.user_signups.email (current: 0.0%) - staging.email_events.recipient_email (current: 1.2%) I'll create null_percentage metrics for each. Proceed? [Yes/No]You: YesAgent: Created 4 null_percentage metrics. Note: gold.dim_customer.email already has an elevated null rate (12.4%). You may want to investigate before setting alert thresholds, otherwise you'll get an immediate alert.
Review changes, trace their origin, and understand downstream impact.
You: What schema changes happened this week? Show me the impact.Agent: 3 schema changes detected this week: 1. gold.fact_orders.discount_pct REMOVED (Tuesday 4:12 PM) Impact: 2 downstream views reference this column Origin: Removed from staging.orders_raw at 3:47 PM 2. gold.dim_customer.loyalty_tier ADDED (Wednesday 9:30 AM) Type: VARCHAR(50) Impact: No downstream references yet (new column) 3. silver.silver_products.weight REMOVED (Monday 2:15 PM) Impact: 1 downstream table (gold.dim_product) joins on this Origin: Source table raw.products no longer has this column
Apply and manage tags for organization and compliance.
You: Find all tables with email columns and tag them as PIIAgent: Found email columns in 4 tables. Applied PII tag: - gold.dim_customer (column: email) - silver.silver_customers (column: email_address) - raw.user_signups (column: email) - staging.email_events (column: recipient_email) These tables now appear when you ask "which tables have PII?" and will be flagged in compliance reports.
Do I need to install anything to use the Web Agent?
No. The Web Agent is built into AnomalyArmor. Open any asset’s Intelligence tab and click Ask Agent. There’s no extension, no API key, and no local setup.
Yes. Conversations are saved as sessions. Each session keeps full context so follow-ups work naturally, and you can pin important sessions or resume them later from the sidebar.
Will the agent change my monitoring without asking?
No. For any action that creates, modifies, or deletes configuration (metrics, rules, tags, schedules), the agent previews the plan and waits for confirmation. Read-only queries (freshness checks, lineage, alerts) run without prompting.
Why does the agent sometimes call multiple tools for one question?
The agent chains tools to answer cross-domain questions. “Why is this dashboard broken?” can trigger schema, freshness, and lineage checks in sequence. You can see each call and its result inline, which is how the agent shows its reasoning.