Design background Data Atlas style agents for Itô basket research, market discovery, parameter drafting, and human-in-the-loop editing. Use for architecture and workflow planning, not live order execution.
Scanned 9/4/2026
Install to Claude Code
npx -y skills add NeverSight/skills_feed --skill ito-data-atlas-agent --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Ito Data Atlas Agent?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/neversight-ito-data-atlas-agent)More formats (shields.io, HTML) on the badges page.
---
name: ito-data-atlas-agent
description: Design background Data Atlas style agents for Itô basket research, market discovery, parameter drafting, and human-in-the-loop editing. Use for architecture and workflow planning, not live order execution.
origin: ECC
---
# Itô Data Atlas Agent
Use this skill to design an agent that watches data sources, builds candidate
prediction-market baskets, drafts parameter changes, and hands the result to a
human for review.
This skill describes architecture and workflow. It does not run live trading.
## 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
Use four lanes:
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
Return an implementation-ready workflow spec with:
- data sources
- access gates
- agent roles
- human approval points
- storage/audit boundary
- non-goals
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!