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Glama

validate_human_overrides

Compare human-set fair values against market data to flag potential errors before approving trades.

Instructions

Check if human fair value overrides are reasonable by comparing against market data and flagging potential errors. Use before executing approved trades.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
overridesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

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

There are no annotations, so the description carries the behavioral burden. It clearly implies a read-only validation action ('Check', 'flagging') rather than a mutation, but it does not state whether the tool modifies state, requires special permissions, or how it handles invalid input. The return format of the flagged errors is also unspecified.

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

Conciseness5/5

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

The description consists of two short sentences with no filler. The main purpose is front-loaded, followed by a clear usage directive, making it easy for an agent to parse quickly.

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

Completeness3/5

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

The description gives enough context to understand why and when to call the tool, and the schema defines the input. However, with no output schema and no explanation of the return value, an agent cannot anticipate whether the tool returns a pass/fail boolean, a list of flagged errors, or some other structure. The lack of side-effect and output details leaves a notable gap.

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?

The tool description adds the conceptual context of 'human fair value overrides' and 'market data', but the input schema already documents the array structure, required fields, bounds, and individual property meanings. The description does not significantly compensate for the top-level parameter's lack of description beyond what the schema already provides.

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?

The description uses a specific verb ('Check') and names the exact resource ('human fair value overrides') while stating the mechanism ('comparing against market data') and expected outcome ('flagging potential errors'). It clearly distinguishes itself from sibling tools like calculate_trade or auto_research_market by framing itself as a pre-trade validation step.

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

Usage Guidelines4/5

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

The phrase 'Use before executing approved trades' provides explicit timing and context for when to invoke the tool. However, it does not mention when not to use it or identify alternative tools for different scenarios.

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