Polymarket Agent Mcp

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 states this is a write operation ('Record... to the database'), implying mutation, but doesn't disclose behavioral traits like authentication requirements, error handling, or whether the operation is idempotent. It mentions the purpose ('for dashboard tracking and performance analysis') but lacks details on response format or potential side effects. For a write tool with zero annotation coverage, this is a moderate gap.

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 two sentences, front-loaded with the core purpose and followed by a clear usage directive. Every word earns its place: the first sentence defines what it does and why, the second tells when to call it. No redundancy or fluff, making it highly efficient and well-structured.

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 complexity (12 parameters, write operation) and lack of annotations or output schema, the description is moderately complete. It covers purpose, usage timing, and hints at stored data, but doesn't address behavioral aspects like error handling, response format, or dependencies. For a logging tool with no output schema, more context on what happens after logging (e.g., confirmation, error messages) would improve completeness.

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 already documents all 12 parameters thoroughly. The description adds minimal value beyond the schema by listing some metrics stored (PnL, win rate, positions, budget usage, notes), which loosely maps to parameters like realized_pnl, win_rate, positions_open/closed, and budget_used/limit. However, it doesn't provide additional syntax, constraints, or usage context beyond what's in the schema descriptions. Baseline 3 is appropriate when schema does 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 ('Record an AI agent's trading cycle metrics to the database') and resource ('for dashboard tracking and performance analysis'), distinguishing it from sibling tools like config.dashboard or config.history. It explicitly lists the metrics stored (PnL, win rate, positions, budget usage, notes), making the purpose highly specific and unambiguous.

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 provides explicit usage guidance: 'Call this after each automated trading cycle.' This tells the agent precisely when to use this tool versus alternatives like config.dashboard (for viewing) or config.history (for retrieving past logs). The timing directive is clear and actionable.

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