Best fit
- Review prediction-market, basket, oracle, and trading-agent workflows for compliance, safety, data-quality, privacy, and execution risk. Use before any workflow handles venue auth, user portfolio data, API keys, or trade planning.
affaan-m/ECC
Review prediction-market, basket, oracle, and trading-agent workflows for compliance, safety, data-quality, privacy, and execution risk. Use before any workflow handles venue auth, user portfolio data, API keys, or trade planning.
npx skills add https://github.com/affaan-m/ECC --skill "skills/prediction-market-risk-review"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
According to the pinned SKILL.md from affaan-m/ECC: Use this skill before a prediction-market workflow touches user financial context, venue authentication, portfolio data, automation, or execution-capable tools.
npx skills add https://github.com/affaan-m/ECC --skill "skills/prediction-market-risk-review"Best fit
Bring this context
Expected outputs
Key source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
Confirm the output is informational.
Confirm the output is informational.
Identify venue terms, geography restrictions, account limits, and API rules.
Check market liquidity, spread, resolution rules, stale prices, and source
Do not request or store private keys, seed phrases, or passwords.
SkillSignal prompt templates
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Task-start prompt
Confirm source fit, inputs, and outputs before acting.
Use prediction-market-risk-review to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.
Source-guided execution
Make the Agent explicitly follow the key extracted sections.
Apply the pinned prediction-market-risk-review source to [task]. Pay particular attention to these source sections: “Review Gates”, “Advice Boundary”, “Venue And Regulatory Boundary”, “Data Quality”, “Security”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].
Result-review prompt
Check omissions, permissions, and source drift before delivery.
Review the current prediction-market-risk-review result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.
Output checklist
The task matches the purpose documented in the SKILL.md.
The source section “Review Gates” has been checked.
The source section “Advice Boundary” has been checked.
The source section “Venue And Regulatory Boundary” has been checked.
The source section “Data Quality” has been checked.
Inputs, constraints, and acceptance criteria are explicit.
Unverified facts, compatibility, and outcome claims are clearly marked.
Any file, command, network, or data action has been reviewed.
Choose a different workflow
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A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
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A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
Use this skill before a prediction-market workflow touches user financial context, venue authentication, portfolio data, automation, or execution-capable tools.
The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/prediction-market-risk-review". Inspect the command and pinned source before running it.
No dedicated Agent platform is declared in the pinned source record.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
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Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
Use when writing, generating, or improving Pest tests for Laravel — clear intent, good coverage, maintainable structure, and alignment with project testing conventions.
Use this skill before a prediction-market workflow touches user financial context, venue authentication, portfolio data, automation, or execution-capable tools.
ITO_API_KEY and venue API keys out of logs and docs.Return:
If any execution-capable step is requested, require a separate implementation plan and explicit user approval.