Polygon wallet base profile via JSON-RPC (Ankr-backed when RPC_POLYGON is set, public fallback otherwise). Returns MATIC balance, outbound tx count, contract-vs-EOA detection, and a lightweight risk heuristic.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Polygon address (0x + 40 hex chars) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It transparently mentions the data source (JSON-RPC), its fallback behavior ('Ankr-backed when RPC_POLYGON is set, public fallback otherwise'), and the exact return data. It does not explicitly state that the operation is read-only or discuss error handling, but the read-only nature is clearly implied and the network dependency is disclosed.
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 single, dense sentence that front-loads the tool's purpose and immediately provides key details. Every phrase adds value: data source, fallback behavior, and specific return fields. There is no redundancy or fluff.
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?
Given the simplicity of the tool (single parameter, no output schema, no annotations), the description is fully complete. It explains what the tool does, how it works (JSON-RPC with fallback), what it returns (balance, tx count, contract/EOA, risk heuristic), and its place in the tool ecosystem ('base profile'). No critical information is missing for an agent to decide when and how to invoke it.
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 coverage is 100%, with the single 'address' parameter fully described as a 'Polygon address (0x + 40 hex chars)'. The tool description adds no additional semantic detail about the parameter beyond what the schema already provides. Baseline 3 is appropriate since the schema does the heavy lifting.
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's purpose: retrieving a 'Polygon wallet base profile via JSON-RPC'. It specifies the resource (Polygon wallet), the action (lookup/profile retrieval), and the key outputs (MATIC balance, outbound tx count, contract-vs-EOA detection, risk heuristic). This distinguishes it from sibling tools by emphasizing 'base profile' and 'lightweight risk heuristic', differentiating from more specialized tools like pg_wallet_risk_profile.
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 context (a base-level wallet lookup) but does not explicitly state when to use this tool versus alternatives like pg_wallet_risk_profile or pg_wallet_entity_resolve. The phrase 'base profile' and 'lightweight risk heuristic' hints at a quick first-pass check, but no explicit when-to-use or when-not-to-use guidance is provided. This is implied rather than clear direction.
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.