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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, lowering the bar, but the description adds extensive behavioral context beyond these. It discloses safety mechanisms (low-confidence resolution suppresses analysis fields, closed markets return blocking status), wide-spread tradeability notes, cancellation-rule parsing with ev_impact quantification, and news fallback behaviors. No contradiction with annotations.

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 long but well-structured with uppercase section headers (CLASSIFIERS, FAN-OUT EXAMPLES, RESPONSE SHAPES, etc.) that aid scanning. The first sentence front-loads the core purpose, and every section adds critical operational information for a complex tool. While dense, it earns its length; a 5 would require even tighter prose.

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 thoroughly explains return shapes (market, analysis, evidence), resolver contract, parent-event extractor, news fields, and safety routes. It covers edge cases like low-confidence matches, closed markets, wide spreads, and cancellation rules. This is a complete operational picture for an agent to invoke and interpret the tool correctly.

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%, so the baseline is 3. The description adds some context for the market parameter (slug, URL, or question text), but this duplicates what the schema already states. It does not add meaningful semantics for depth or include_raw beyond what the schema provides. The description's value lies more in explaining tool behavior than in clarifying parameter meanings.

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: 'Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call.' It clearly differentiates from siblings like polymarket_arbitrage or polymarket_edges by focusing on a single bet and its evidence packet. It also provides explicit use cases ('should I bet on X', 'what does the data say about Y', 'is there edge in Z'), 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 lists when to use the tool ('Use for...') and gives detailed fan-out examples by bet type, which implies appropriate contexts. However, it does not explicitly state when not to use it or name alternative sibling tools, so it stops short of a 5. The clear context and examples still provide strong guidance.

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