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Prediction market risk review

Skill S3YED/appie-kit/skills/ecc/prediction-market-risk-review

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.From its SKILL.md

Install
npx -y skills add S3YED/appie-kit --skill prediction-market-risk-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

1.8 KB, 324 tokens by cl100k_base, as published. Nobody here has run it

Prediction Market Risk Review

Use this skill before a prediction-market workflow touches user financial context, venue authentication, portfolio data, automation, or execution-capable tools.

Review Gates

Advice Boundary

  • Confirm the output is informational.
  • Remove buy/sell/hold/size recommendations.
  • Keep manual user decision points explicit.

Venue And Regulatory Boundary

  • Identify venue terms, geography restrictions, account limits, and API rules.
  • Flag betting, derivatives, securities, or commodities ambiguity for legal review when relevant.
  • Do not bypass venue restrictions or rate limits.

Data Quality

  • Check market liquidity, spread, resolution rules, stale prices, and source timestamps.
  • Separate public venue data from Itô gated data.
  • Do not mix public and private sources without labels.

Security

  • Do not request or store private keys, seed phrases, or passwords.
  • Keep ITO_API_KEY and venue API keys out of logs and docs.
  • Use read-only scopes by default.
  • Require circuit breakers, spend limits, dry runs, and human approval before any private implementation adds execution.

Privacy

  • Minimize user portfolio, financial, and knowledge-base data.
  • Redact private sources in public artifacts.
  • Preserve only the fields needed for the review.

Output Contract

Return:

  1. scope reviewed
  2. pass/warn/fail findings
  3. blocked actions
  4. required mitigations
  5. safe next step

If any execution-capable step is requested, require a separate implementation plan and explicit user approval.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most review quality skills give in 324 tokens

Counted across 1,273 of the 2,403 authors here whose files we hold, read 2026-09-06

  • Ask one question at a timein 63 of 1273, across 62 files
  • Provide a recommended answer for each questionin 47 of 1273, across 45 files
  • Rank findings by severityin 44 of 1273
  • Use parameterized queries for database accessin 38 of 1273, across 20 files
  • Validate all user input with schemasin 33 of 1273, across 15 files
  • Store secrets in environment variablesin 32 of 1273, across 14 files
  • Explore the codebase to answer questionsin 31 of 1273, across 29 files
  • Store tokens in httpOnly cookiesin 30 of 1273, across 12 files
  • Implement rate limiting on API endpointsin 30 of 1273, across 12 files
  • Sanitize user-provided HTMLin 29 of 1273, across 11 files
  • Return generic error messages to usersin 28 of 1273, across 10 files
  • Cite file and line for every findingin 28 of 1273, across 25 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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