From anomalyarmor-agents
Ask natural language questions about your data. Handles "what tables contain", "tell me about", "explain", "what do you know about", "describe".
npx claudepluginhub anomalyarmor/agents --plugin armorThis skill uses the workspace's default tool permissions.
Ask natural language questions about your database structure, lineage, and metadata using AnomalyArmor Intelligence.
Conducts multi-round deep research on GitHub repos via API and web searches, generating markdown reports with executive summaries, timelines, metrics, and Mermaid diagrams.
Dynamically discovers and combines enabled skills into cohesive, unexpected delightful experiences like interactive HTML or themed artifacts. Activates on 'surprise me', inspiration, or boredom cues.
Generates images from structured JSON prompts via Python script execution. Supports reference images and aspect ratios for characters, scenes, products, visuals.
Ask natural language questions about your database structure, lineage, and metadata using AnomalyArmor Intelligence.
~/.armor/config.yaml or ARMOR_API_KEY env var), OR demo mode active (see below).pip install anomalyarmor)/armor:analyze if needed)If the user has no API key, ensure-auth.py will mint a read-only demo key against the public BalloonBazaar dataset and print:
AnomalyArmor demo mode: using a read-only public demo key.
When you see that banner — or when any write operation returns a 403 with required_scope='read-write' — the user is in demo mode. After answering their question, invite them to sign up with their query preserved:
To ask about your own data, sign up here — your question is preserved:
https://app.anomalyarmor.ai/signup?intent=skill-ask&q=<url-encoded user prompt>
intent=skill-ask auto-applies a 14-day SKILL-ASK trial code; q= is replayed in the in-app agent after signup so the user continues where they left off.
client.intelligence.ask()from anomalyarmor import Client
client = Client()
# Ask about your data
answer = client.intelligence.ask(
asset="postgresql.analytics",
question="What tables contain customer data?"
)
print(f"Answer: {answer.answer}")
print(f"Confidence: {answer.confidence}")
print(f"Sources: {answer.sources}")
from anomalyarmor import Client
client = Client()
answer = client.intelligence.ask(
asset="postgresql.analytics",
question="Describe the orders table and its columns"
)
print(answer.answer)
from anomalyarmor import Client
client = Client()
# Include related assets for cross-database context
answer = client.intelligence.ask(
asset="postgresql.analytics",
question="What data flows from staging to production?",
include_related_assets=True
)
print(answer.answer)
from anomalyarmor import Client
import json
client = Client()
# Ask for JSON format in your question
answer = client.intelligence.ask(
asset="postgresql.analytics",
question="List all tables with PII columns as a JSON array with table_name and columns fields"
)
# Parse the JSON response
try:
pii_tables = json.loads(answer.answer)
for table in pii_tables:
print(f"Table: {table['table_name']}")
print(f" PII Columns: {table['columns']}")
except json.JSONDecodeError:
print(answer.answer)
| Category | Example Questions |
|---|---|
| Schema | "What columns are in the orders table?" |
| Lineage | "Where does the revenue column come from?" |
| PII | "Which tables contain email addresses?" |
| Relationships | "What tables join with customers?" |
| Purpose | "What is the orders table used for?" |
| Quality | "What data quality issues exist in this database?" |
If you get an error about missing intelligence:
/armor:analyze to trigger intelligence generation/armor:analyze to generate or refresh intelligence/armor:status to check overall health