Screen a named entity against global sanctions lists (OFAC SDN, EU FSF, UN SC, Interpol). Delegates to AMLOracle. Use after resolving a wallet/trader to a real name via public reporting or known-case registry.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Person or entity name | |
| threshold | No | Optional fuzzy-match threshold (0..1) | |
| entity_type | No | Optional: 'person' or 'organization' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It mentions the delegation to AMLOracle, which is useful, but it does not disclose whether this is a read-only operation, potential rate limits, external dependency behavior, or what happens when no match is found. Some behavioral context is present but incomplete.
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 two sentences long, front-loaded with the primary purpose and followed by a usage hint. There is no filler, and every sentence contributes useful information.
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 has no output schema, so the description should ideally hint at return values or match behavior. It does not mention what the tool returns (e.g., match list, risk score, Boolean). The usage context is strong, but the absence of output/error semantics leaves a notable gap.
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%, so the schema fully documents all three parameters. The description does not add any additional meaning beyond the schema, which is acceptable per the baseline but provides no extra value.
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 uses a specific verb ('Screen') and clearly specifies the resource ('named entity against global sanctions lists') with concrete list names (OFAC SDN, EU FSF, UN SC, Interpol). This distinctly separates it from sibling tools like pg_pep_check_entity or pg_adverse_media_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 description provides clear context on when to use the tool: 'Use after resolving a wallet/trader to a real name via public reporting or known-case registry.' It does not explicitly mention alternatives or exclusions, but the timing and prerequisite are well-defined.
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.