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Skills affaan-m ecc

prediction-market-oracle-research

Use it when:
You're considering prediction markets as a data source, forecasting input or oracle-like signal for a product, agent, dashboard or decision.
It does:
Records market-implied probabilities with timestamps and links, rates liquidity, spread, age and resolution, and compares them with filings, news, polls or internal data.
You get:
A report from decision context to caveats, with a verdict that the signal is usable, weak or unsuitable for that decision.
Won't:
Treat prices as objective truth or give investment advice or trading recommendations.

TL;DR

A research workflow for teams thinking of using prediction markets as an input rather than a bet. The agent starts from the decision the signal is meant to inform, finds the relevant markets, events and venues, and records each implied probability with a timestamp and source link. It then judges signal quality: liquidity, spread, market age, trader or incentive concentration where known, who resolves the market, and geography or account restrictions, calling out manipulation, thin liquidity, stale markets and ambiguous outcomes. Market signals are checked against non-market sources such as filings, news, polls, research, customer data or internal KPIs. It suggests ways to use a signal: context for a human analyst, a figure on a dashboard beside internal metrics, a time-stamped input to agent memory, threshold alerts, or scenario planning without automated trades. The report runs from decision context, market sources, signal quality and comparison sources to an integration recommendation and caveats, and ends with a line saying the signals are not investment advice. For on-chain or execution-linked systems it points to ECC's llm-trading-agent-security skill before granting any write authority.

Summarizes the skill at d2ef268.

npx skills add https://github.com/affaan-m/ecc --skill prediction-market-oracle-research

skills.sh pageSource on GitHubAll skills from affaan-m/ecc

Total Downloads
5,200 on skills.sh, Nov 9, 2026
Repo stars
299,776 affaan-m/ecc
First seen
May 25, 2026 on skills.sh
Weekly Downloads
439
+67% over the 8 weeks to Nov 9
Weekly values
Week toInstalls
Sep 21263
Sep 28158
Oct 5137
Oct 12228
Oct 19404
Oct 26396
Nov 2468
Nov 9439
Category
category:science

Research reproduction, financial data, charts and diagrams.
Type
type:workflow

A multi-step process the agent follows: interview, debug, run a TDD loop, review.
Effect
effect:none

Adds no side effects of its own. It shapes how the agent thinks, writes or reviews. Guidelines and routers are always effect:none, even when the task they support edits code.
Needs
needs:none

Instructions only. Works in any agent that supports skills.
Publisher
by:community

Everyone else. Unverified vendor claims default to community.
Topics
researchfinance

SKILL.md

From affaan-m/ecc at d2ef268. Checked daily, last changed Nov 6, 2026.

Frontmatter
name: prediction-market-oracle-research
description: Research prediction markets as data sources or oracle signals for products, agents, dashboards, and corporate decision intelligence. Use for source-grounded analysis of market-implied probabilities, caveats, and integration patterns without investment advice. Use when evaluating prediction markets as a data source or oracle signal for a product, agent, or dashboard.
metadata:
  origin: ECC

Prediction Market Oracle Research

Use this skill when prediction markets are being considered as a data source, forecasting input, oracle-like signal, or decision-intelligence layer.

Guardrails

  • Do not treat market prices as objective truth.
  • Do not provide investment advice or trading recommendations.
  • Separate venue mechanics, liquidity, incentives, and resolution rules from the implied signal.
  • Call out manipulation, thin liquidity, stale markets, and ambiguous outcomes.
  • For on-chain or execution-linked systems, run llm-trading-agent-security before granting any write authority.

Research Workflow

  1. Define the decision the signal is meant to inform.
  2. Find relevant markets, events, tags, and venues.
  3. Record market-implied probabilities with timestamps and source links.
  4. Evaluate signal quality:
    • liquidity
    • spread
    • market age
    • trader/incentive concentration if known
    • resolution authority
    • geography or account restrictions
  5. Compare against non-market sources such as filings, news, polls, research, customer data, or internal KPIs.
  6. Recommend whether the signal is usable, weak, or unsuitable for the stated decision.

Integration Patterns

  • Research assistant: source-grounded context for a human analyst.
  • Dashboard signal: market-implied probability alongside internal metrics.
  • Agent memory input: a time-stamped signal that can be retrieved later.
  • Alerting input: notify when probabilities, spreads, or liquidity cross a threshold.
  • Scenario planning: compare multiple event outcomes without automating trades.

Output Contract

Use:

  1. decision context
  2. market sources
  3. signal quality
  4. comparison sources
  5. integration recommendation
  6. caveats

End with:

Prediction-market signals are informational inputs, not investment advice.