Ito Data Atlas Agent
- 1.2k installs
- 238k repo stars
- Updated August 5, 2026
- affaan-m/ecc
ito-data-atlas-agent is an architecture-planning skill that designs human-in-the-loop Data Atlas agents for Itô basket research, market discovery, and parameter drafting.
About
ito-data-atlas-agent is an ECC-origin skill for designing background Data Atlas-style agents that watch data sources, assemble candidate prediction-market baskets, draft parameter changes, and route output to a human reviewer. The skill covers workflow architecture and planning only—it does not run live trading or place orders. Guardrails require explicit human approval before any execution step and limit ITO_API_KEY usage to read-only Itô data access unless a separate approved execution path exists. Developers reach for ito-data-atlas-agent when scaffolding automated basket research pipelines that need review gates, source watchers, and draft parameter tables instead of one-off manual worksheets.
- Four-lane architecture pattern
- Explicit human-in-the-loop handoff
- Guardrails keep execution behind user approval
Ito Data Atlas Agent by the numbers
- 1,246 all-time installs (skills.sh)
- +82 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #917 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 1.2k |
|---|---|
| repo stars | ★ 238k |
| Last updated | August 5, 2026 |
| Repository | affaan-m/ecc ↗ |
How do you architect a prediction market research agent?
Design the architecture and workflow for a background agent that drafts prediction-market baskets and hands results to a human for review.
Who is it for?
Developers building background research agents for Itô prediction markets who need explicit human-in-the-loop review before any execution.
Skip if: Teams wanting immediate trade execution, single-worksheet planning, or basket comparison without agent architecture design.
When should I use this skill?
A user asks to design a background agent for Itô basket research, market discovery, or parameter drafting with human approval gates.
What you get
Agent architecture diagram, data-source watch workflow, basket draft pipeline, parameter change tables, and human approval checkpoints.
- Agent workflow architecture
- Basket draft pipeline spec
- Human review checkpoint map
Files
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_KEYonly 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-researchfor source collection.x-apifor current social/event signal.ito-market-intelligencefor venue and underlier context.ito-basket-comparefor user knowledge-base matching.prediction-market-risk-reviewbefore 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
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Does ito-data-atlas-agent execute trades automatically?
ito-data-atlas-agent describes architecture and workflow only. All execution stays behind explicit human approval, and the skill does not run live trading or place orders.
What API access does ito-data-atlas-agent assume?
ito-data-atlas-agent expects ITO_API_KEY for read-only Itô data access during design unless the user defines a separate approved execution integration.