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pg_insider_signal_scan

Real-time insider-trading signal scan for a single Polymarket market. Aggregates 5 signals: (1) very large pre-event positions, (2) high ratio of wallets new to this market, (3) coordinated minute-bucket timing clusters, (4) one-sided positioning, (5) sensitive-keyword category match (military/regime/intel). Returns a 0-100 score (CLEAN/LOW/MEDIUM/HIGH/CRITICAL), triggered signals with evidence, top 5 positioners with new-wallet flag, and full methodology for audit. Default window = 72h before market end.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoMarket id / conditionId
slugNoPolymarket market slug
window_hoursNoPre-event window to analyze (default 72h)
min_position_usdNoMin notional to flag (default $1000)

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the default window (72h), the output structure (score, triggered signals, top 5 positioners, methodology), and the aggregated nature of the scan. It implicitly conveys a read-only operation via 'returns', but it does not explicitly state side-effect freedom or auth requirements.

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

Conciseness4/5

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

Single cohesive paragraph that front-loads the core purpose and lists the 5 signals efficiently. It is dense but all information is relevant, no redundancy, and it covers inputs, outputs, and defaults without excessive length.

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

Completeness5/5

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

No output schema exists, so the description must explain return values – it does thoroughly (score, CLEAN/CRITICAL categories, evidence, top 5, methodology). For a complex tool with 4 parameters and 5 signal types, it covers all essential behavioral and output aspects with no obvious critical gaps.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining the window is 'before market end' and that min_position_usd is the threshold for flagging large positions, enriching the schema's basic descriptions for these parameters.

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?

States 'Real-time insider-trading signal scan for a single Polymarket market' – a specific verb (scan) and resource (Polymarket market). It enumerates 5 distinct signal types, clearly differentiating it from sibling tools that focus on individual signals like pg_position_timing_anomaly or pg_pre_event_flow_analysis.

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

Usage Guidelines3/5

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

No explicit when-to-use or alternative recommendations. It implies usage for single-market insider signal scanning, but does not contrast with sibling tools such as pg_market_integrity_scan or pg_information_advantage_score, leaving the agent to infer placement.

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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