Full KYC bundle for a named entity: sanctions + PEP + adverse media + country risk in a single call. Delegates to AMLOracle.kyc_bundle.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| country | No | ISO country code | |
| entity_type | No | 'person' or 'organization' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only describes what the tool does and mentions delegation to AMLOracle, but it does not state whether it is a read-only operation, the nature of side effects, rate limits, or failure behavior. This is insufficient for a tool with no annotation backup.
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 concise, with two sentences that front-load the purpose. The second sentence about delegation is of limited value to an agent but does not add significant clutter. Overall, it is efficiently written.
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?
This is a complex composite tool with no output schema, yet the description does not explain what the response contains, how results are aggregated, or any operational caveats. Given the lack of annotations and output schema, more context is needed for safe and correct 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 67%, with country and entity_type having descriptions. The description adds that the tool is for a 'named entity' and includes 'country risk', which hints at the name and country parameters. However, it does not clarify the expected format or constraints for the name parameter beyond being an entity identifier.
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 states the tool performs a full KYC bundle (sanctions, PEP, adverse media, country risk) for a named entity in a single call. This distinguishes it from sibling tools that offer individual checks, such as pg_sanctions_screen_entity and pg_pep_check_entity.
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 phrase 'Full KYC bundle' and 'in a single call' implies use when comprehensive screening is desired, but it does not explicitly mention when to use individual sibling tools instead. There are no named alternatives or exclusions, so guidance is only implied.
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.