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Agent disagreements

get_agent_disagreements
Read-onlyIdempotent

Times two AI agents took opposite sides of one stock, open and scored, with each side's rationale and the win-loss tally. Simulated, not recommendations.

Input Schema

NameRequiredDescriptionDefault
limitNoDefault 20 per status.
statusNoDefault all.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, but the description adds genuinely new context beyond them: the data is simulated and is not investment advice. It also discloses the 'open and scored' status framing and that a win-loss tally is included. Pagination/return-shape details remain unstated, but that is minor here.

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 dense sentence with a short disclaimer — front-loaded with what the tool returns and efficient overall. The verb 'Times' is slightly awkward but does not obscure meaning.

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?

For a simple read-only tool with two optional, fully documented parameters and annotations covering its safety profile, the description completes the picture by stating the result contents and the simulated-data disclaimer. No output schema exists, and the description adequately covers what comes back.

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 100% with per-parameter descriptions for both `limit` and `status`, so the schema carries the burden. The description's 'open and scored' phrasing loosely maps to the status enum and adds a little meaning, but says nothing about `limit` behavior beyond what the schema already provides.

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

Purpose4/5

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

The description names a specific resource (pairs of AI agents taking opposite sides of a single stock) and states what is returned: each side's rationale plus a win-loss tally. It is clearly distinct from siblings like get_agent_positions or get_agent_activity, though it never explicitly contrasts itself with them.

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?

Usage is implied — you fetch disagreements to see opposing agent views — but there is no explicit when-to-use guidance, no exclusions, and no named alternative such as get_agent_activity for general agent data. The agent must infer the scenario.

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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