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pg_resolution_risk_score

Multi-signal resolution-risk score (0–100, CLEAN/LOW/MEDIUM/HIGH/CRITICAL) for a Polymarket market. Combines category priors (geopolitical/election/sanctions patterns from pg_known_cases), resolution-phase proximity, market volume, resolution-source sanity check (is the UMA adapter a real deployed contract), UMA global dispute ratio, and thin-book flag. Returns triggered signals with point deductions for full auditability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
slugNo

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the computation logic, the output (score plus triggered signals), and the auditability mechanism (point deductions). It does not explicitly state read-only status, but the 'returns' phrasing and nature of a scoring tool strongly imply a non-mutating query.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, with the core purpose in the first phrase. Each clause adds a distinct signal type or output feature, with no wasted words. The structure is easy to scan and digest.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of the tool and lack of output schema, the description adequately covers the score range, categories, and the return of triggered signals with point deductions. It could be more explicit about parameter requirements, but overall it provides sufficient context for an agent to understand the tool's function.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, and the tool description does not elaborate on the 'id' and 'slug' parameters. It only says 'for a Polymarket market,' leaving unclear whether both are required, what formats are expected, or how they map to market identification.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool computes a multi-signal resolution-risk score for a Polymarket market, with a specific 0–100 scale and CLEAN/LOW/MEDIUM/HIGH/CRITICAL categories. It distinguishes itself from siblings by detailing unique signal components such as category priors, resolution-phase proximity, and UMA dispute ratio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for use—assessing resolution risk for a Polymarket market—and implies this tool is for detailed risk analysis. However, it does not explicitly name alternatives or state when-not-to-use conditions, though the rich signal list implies a specialized role among siblings.

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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TDQS

A3.9/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count4/5

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'.

Completeness5/5

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.

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