Resolution source and phase for a specific Polymarket market. Fetches market metadata from Gamma, extracts the resolutionSource address, verifies it's a deployed contract on Polygon, and classifies the resolution phase (active_trading / approaching_resolution / imminent_resolution_window / past_end_awaiting_resolution / resolved).
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Market id / conditionId | |
| slug | No | Market slug |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the entire operational flow: fetching from Gamma, extracting the resolutionSource address, verifying deployment on Polygon, and classifying the phase. This gives a clear expectation of behavior, though it does not address potential side effects, rate limits, or failure modes, so a 4 is appropriate.
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 compact and front-loaded with the core purpose, then efficiently lists the step-by-step process and the possible phase values. Every clause contributes meaningful information with no redundancy, making it an excellent model of concise, structured description.
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 there is no output schema, the description explains the main outputs (resolution source and phase) and lists all phase categories, which is essential for understanding what to expect. It could go further by describing the exact return format or error handling, but for a tool with only two documented parameters, it is sufficiently complete.
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% with both 'id' and 'slug' documented. The tool description does not add any additional parameter-level detail beyond what the schema already provides, so the baseline 3 applies.
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: returning resolution source and phase for a specific Polymarket market. It includes a detailed step-by-step breakdown (fetching metadata, extracting resolutionSource, verifying contract, classifying phase) and enumerates the exact phase categories, which fully distinguishes it from sibling tools like pg_market_details or pg_resolution_risk_score.
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 makes the usage context evident: for a specific Polymarket market when you need resolution source and phase. However, it does not explicitly mention when NOT to use this tool or compare it to alternatives such as pg_uma_status or pg_resolution_risk_score, so it falls short of a 5.
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.