pg_overview
PredictionGuard platform overview: covered platforms, tool inventory, Polymarket Gamma API ping, Polygon RPC ping (Ankr-backed), known-case count.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
PredictionGuard platform overview: covered platforms, tool inventory, Polymarket Gamma API ping, Polygon RPC ping (Ankr-backed), known-case count.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose key behavior by listing the tool's checks, including external dependencies (Polymarket Gamma API ping, Polygon RPC ping via Ankr) and a known-case count. However, it does not explicitly state read-only behavior, error handling, data freshness, or potential side effects, though for an overview tool these are likely minimal.
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, front-loaded sentence that begins with the tool's purpose ('PredictionGuard platform overview') and then compactly enumerates the included items. Every word earns its place; there is no filler or repetition.
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?
For a zero-parameter overview tool with no output schema, the description provides enough information about the major result categories to set agent expectations. It could be slightly more explicit about whether this is a health/status check, timestamps, or error behavior, but the core content is covered and clearly distinguishes it from the more specialized sibling tools.
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?
The input schema has zero parameters and 100% schema description coverage, so there are no parameter meanings for the description to clarify. Baseline 4 applies for a no-parameter tool, and the description appropriately requires no parameter details.
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 platform overview and lists its contents (covered platforms, tool inventory, pings, known-case count), which distinguishes it from the more targeted sibling tools. However, it lacks an explicit verb like 'get' or 'retrieve,' so it reads more as a summary than a direct instruction.
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?
No explicit guidance is provided on when to use this tool versus sibling tools. The description implies a high-level snapshot, but it does not mention that specific details should be obtained from dedicated tools (e.g., pg_market_details, pg_wallet_lookup) or exclude any use cases.
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.