Complete forensic dossier for a single Polymarket market: market details + integrity scan + volume anomaly profile + Trust Layer provenance trace — aggregated into one dossier ready for manual review, press inquiry, or as input to a SAR report.
| 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, the description bears the full burden. It discloses that the tool aggregates several data sources into one dossier, which is useful, but it does not mention read-only status, potential side effects, or any operational constraints like required permissions. The composition is described, but behavioral transparency is limited.
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, well-structured sentence that front-loads the core value and lists both components and use cases without unnecessary 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?
For a bundle tool with no output schema, the description explains what the dossier contains and its intended applications. However, it omits details about the output structure, whether parameters are required, and what 'Trust Layer provenance trace' means, leaving some ambiguity.
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?
Both parameters (id, slug) are already fully described in the schema, so schema coverage is 100%. The description adds no extra parameter semantics beyond 'single Polymarket market', so the baseline of 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 identifies the tool as a 'Complete forensic dossier' for a single Polymarket market, listing the constituent parts (integrity scan, volume anomaly profile, provenance trace) and distinguishing it from narrower sibling tools like pg_market_details or pg_market_integrity_scan. Though it lacks an explicit action verb, 'aggregated' conveys the bundling behavior.
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?
It states the dossier is 'ready for manual review, press inquiry, or as input to a SAR report', giving concrete use cases. It does not explicitly contrast with individual component tools or state when not to use, but the 'complete' and 'aggregated' language implies it replaces multiple separate queries.
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.