get_edge_opportunities

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

With no annotations provided, the description carries the full burden. It discloses the tool's purpose (finding mispriced markets with AI disagreement) and output (top edge opportunities with positions), but lacks details on behavioral traits like rate limits, authentication needs, or what 'mispriced' entails operationally. It adds basic context but misses deeper behavioral insights.

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 front-loaded and highly concise—two sentences with zero waste. The first sentence defines the purpose and scope, and the second specifies the return value, 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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is reasonably complete. It covers the purpose, output, and high-level logic (AI vs. market probability), but could benefit from more detail on behavioral aspects or output structure to fully compensate for the lack of annotations and output schema.

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 schema fully documents both parameters. The description does not add any parameter-specific meaning beyond what the schema provides (e.g., it doesn't explain 'edge percentage' in more detail or how 'limit' interacts with ranking). Baseline 3 is appropriate as the schema handles the heavy lifting.

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 states the specific action ('Find mispriced Polymarket prediction markets') and resource ('edge opportunities'), distinguishing it from siblings like 'analyze_market' or 'get_top_markets' by emphasizing AI-disagreement analysis and recommended positions. It goes beyond a simple list to identify mispriced opportunities.

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 implies usage when seeking mispriced markets based on AI analysis, but does not explicitly state when to use this tool versus alternatives like 'analyze_market' or 'get_top_markets'. No exclusions or prerequisites are mentioned, leaving some ambiguity about optimal context.

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