Registry of publicly reported prediction-market integrity cases (Théo / French whale, Hyperliquid whale, Venezuela, Iran strikes, Nuclear, UMA Ukraine). Filter by category or minimum AML relevance (low/medium/high). Summaries only — no accusations against named parties.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Optional category substring (e.g. 'geopolitical', 'oracle') | |
| min_aml_relevance | No | Minimum AML relevance |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds valuable behavioral context by stating 'Summaries only — no accusations against named parties,' which discloses output limitations and ethical boundaries. The term 'Registry' also implies a read-only operation, though it does not explicitly state read-only or describe side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a compact two sentences that front-load the core purpose and follow with filtering and caveat. Every clause adds relevant information without waste, and the examples and constraints are efficiently embedded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with 2 optional parameters and no output schema. The description covers purpose, filtering, and a critical caveat about summaries/no accusations. It does not detail return fields, but given the simplicity and explicit examples, it is reasonably complete for agent selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both category and min_aml_relevance have descriptions). The description only restates the filter options and enum values, adding minimal meaning beyond the schema. The baseline of 3 is appropriate since the schema already provides complete parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a registry of publicly reported prediction-market integrity cases, listing concrete examples (Théo, Hyperliquid whale, etc.). It distinguishes itself from sibling tools like pg_wallet_lookup or pg_market_integrity_scan by focusing on known cases rather than scans or entity lookups, and the filtering verbs add operational clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving known integrity cases and mentions filtering by category or AML relevance, giving clear context. However, it does not explicitly name alternative tools or provide when-not-to-use exclusions, so it falls just short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a clear, distinct purpose covering different aspects of prediction market integrity (market analysis, wallet analysis, AML/KYC, alerting, reporting). There is minimal overlap risk, as even related tools (e.g., pg_insider_signal_scan vs. pg_information_advantage_score) are differentiated by input (market vs. wallet) and output type.
All tools share the 'pg_' prefix and use descriptive snake_case names, making the set predictable. However, the verb/noun order is inconsistent (e.g., pg_whale_add vs. pg_market_details). The pattern is still clear and functional, so minor deviation from a strict verb_noun pattern.
With 33 tools, the set is large but well-scoped for a comprehensive platform covering market analysis, wallet intelligence, compliance, and reporting. Each tool serves a distinct function, and the count is justified by the breadth of the domain, though it pushes the upper bound of 'reasonable'.
The toolset covers the full lifecycle of prediction market integrity work: from market discovery and integrity scanning to wallet analysis, entity resolution, AML/KYC, watchlist management, alerting, and SAR reporting. There are no obvious gaps for the stated purpose.