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Position- and reputation-tagged human comments on a market (read-only)

problee_list_market_comments
Read-onlyIdempotent

Read human comments on a market (newest first, read-only): comment body + timestamps, the commenter wallet, their black-box reputation tier, and the position they held plus the market prices frozen when they wrote it (shares per outcome, avg entry, prices at write) — position- and reputation-tagged sentiment for trade decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
cursorNonextCursor from a prior call.
addressYesMarket contract address.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly/ idempotent/ non-destructive, so the safety bar is low. The description adds genuine behavioral context beyond them: ordering ('newest first') and the 'black-box reputation tier' plus frozen-at-write pricing semantics of the payload.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence begins with the core action, and every element earns its place. It is dense with stacked parentheticals, slightly straining readability, but not verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained. The description covers purpose, ordering, and payload semantics adequately for a read-only list tool; only auth/permission prerequisites are unaddressed, which matters little for a read call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%; cursor and address carry descriptions, while limit is defined only by numeric bounds. The description adds no parameter-level meaning (the field list it gives refers to response content, not inputs), so it does not compensate for the gap. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Read human comments on a market') and enumerates the returned content (body, timestamps, wallet, reputation tier, position, frozen prices). It is clearly distinguishable from sibling list tools like problee_list_market_trades or problee_get_market_holders.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The closing phrase 'for trade decisions' implies the intended use case, giving implied usage guidance. However, it never states when to prefer this over alternatives such as reading trades or holders, and names no exclusions or prerequisites.

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

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