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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the output components (markets traded, top 20 cotraders, aggregate severity score) and explicitly states the scoring thresholds (≥3 = MEDIUM, ≥5 = HIGH). It does not state whether the operation is read-only or if there are side effects, but the 'Find' verb implies a read operation. The detailed threshold and output description provide substantial behavioral transparency.

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 three sentences, each serving a purpose: the first states the core function, the second enumerates the returns, and the third provides the use case. It is front-loaded and avoids fluff. Every sentence earns its place, making it efficient and easy to parse.

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?

The description fully covers the tool's inputs, outputs, and scoring logic. Since there is no output schema, it compensates by detailing exactly what is returned. Given the tool's moderate complexity (2 parameters, no nested objects), this description is complete enough for an agent to select and invoke it correctly. The mention of market slugs and sensitivity also aligns with the predictive-market integrity context of 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 schema already describes both parameters well (wallet address format and 2-10 market slugs), so the baseline is 3. The description reinforces the parameter constraints in prose but does not add significant new meaning beyond the schema. It ties the parameters to the output (e.g., 'which markets the target traded'), which is slight added value, but not enough to raise the score above baseline.

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 opens with a specific verb and resource: 'Find wallets that co-trade across multiple sensitive Polymarket markets with a target wallet.' It clearly differentiates from siblings like pg_wallet_lookup or pg_wallet_risk_profile by focusing on co-trading correlation across multiple markets. It also specifies the exact deliverable (top 20 cotraders, severity score), making the purpose unmistakable.

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 explicitly states the input requirements ('Given a wallet and 2-10 market slugs') and a concrete use case: 'detect coordinated trading rings, shared-info syndicates, or wallet clusters that consistently bet on the same sensitive events.' This gives clear context for when to use the tool, though it does not mention alternatives or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.