Itô Data Atlas Agent

Guardrails

• Keep all execution behind explicit human approval.
• Require

  ITO_API_KEY

  only for read-only Itô data access unless a separate private implementation explicitly adds execution controls.
• Do not persist private user data unless the target repo already has a storage contract and the user asks for it.
• Do not expose private strategy logic, venue credentials, or local paths in public docs.

Architecture Pattern

1. Research collector: public web, X, GitHub, venue docs, API metadata, and Itô read endpoints when gated access exists.
2. Basket drafter: turns sources into candidate underliers, weights, rules, and questions.
3. Risk reviewer: checks data freshness, venue limits, resolution ambiguity, compliance notes, and prompt-injection exposure.
4. Human editor: opens a chat or UI state where the user can approve, reject, adjust, or ask for more research.

Workflow

1. Define the user objective and excluded actions.
2. List data sources and access requirements.
3. Draft a basket spec with provenance for every underlier.
4. Produce editable parameters rather than executable orders.
5. Store an audit trail: inputs, model output, sources, and human decision.

Useful Skill Chains

• deep-research

  for source collection.

• x-api

  for current social/event signal.

• ito-market-intelligence

  for venue and underlier context.

• ito-basket-compare

  for user knowledge-base matching.

• prediction-market-risk-review

  before any execution-capable integration.

Output Contract

• data sources
• access gates
• agent roles
• human approval points
• storage/audit boundary
• non-goals