kalshi_paper_portfolio

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

No annotations are provided, so the description carries full disclosure burden. It reveals a non-obvious side effect: calling this tool brings the portfolio up to date, settling markets and matching resting orders, which is critical for an agent to know before invoking it. It stops short of detailing sequence or edge cases, but the core behavioral trait is clearly stated.

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?

Three sentences deliver the main purpose, usage scenario, and side effect with no filler. The first sentence packs the valuation components, and each subsequent sentence adds necessary context (when to call, what happens).

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 4-parameter, no-output-schema tool, the description covers what it returns, why to use it, and its state-updating nature. It lacks a formal return structure, but the enumerated components give sufficient guidance. The side-effect disclosure is especially valuable for a tool that appears read-only at first glance.

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 covers 75% of parameters with descriptions, but the tool description itself adds no parameter-specific semantics. It mentions output fields rather than explaining fill_limit or how include_fills/include_orders affect behavior, so it does not compensate for fill_limit's missing description.

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 explicitly states the tool values a simulated portfolio against live prices and enumerates the valuation components (cash, positions, P&L, fees, total return). It distinguishes itself from siblings like kalshi_paper_order or kalshi_get_positions by focusing on portfolio valuation with mark-to-market, not order placement or live positions.

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 explicitly says 'Call this to monitor paper positions over time,' giving a clear use case. It also explains that it updates the portfolio state (settled markets pay out, resting orders match), which tells users when to call it for simulation advancement. However, it does not name alternative tools or say when not to use it, so it lacks explicit exclusions.

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