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Glama

check_price_guardrails

Read-onlyIdempotent

Validate a proposed SKU price against pricing guardrails to detect policy violations, returning block for hard-rule breaches, warn for soft-rule deviations, or pass when compliant.

Instructions

Check a proposed price against the pricing policy.

Hard rules (minimum margin, maximum change per move) produce "block". The soft rule (competitor price index band) produces "warn". Otherwise "pass".

Input Schema

NameRequiredDescriptionDefault
skuYes
proposed_priceYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

The description adds useful behavioral detail by explaining that hard rules produce 'block', the soft rule produces 'warn', and otherwise 'pass'. Annotations already confirm this is a read-only, idempotent check, so the description adds outcome semantics rather than repeating safety metadata. It does not describe error behavior or policy-source details, but it is solid for a read-only guardrail check.

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 is short, front-loaded with the core action, and immediately explains the possible outcomes. Every sentence contributes directly to understanding the tool.

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 tool has an output schema, so return values do not need full explanation. However, with 0% input schema description coverage, the description leaves gaps in parameter semantics and does not distinguish this check from closely related sibling tools.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the two undocumented parameters. It mentions the proposed price conceptually but does not explain SKU format, price currency, units, or expected value ranges, leaving parameter semantics largely to inference.

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 uses a specific verb and resource: checking a proposed price against the pricing policy. It clearly explains the tool's core function, but it does not explicitly distinguish it from similar siblings such as check_price_ladder or simulate_price_change.

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 by the name and description: use this to evaluate a proposed price before making a price change. However, there is no explicit guidance on when to use it versus simulate_price_change or check_price_ladder, nor are prerequisites or exclusions stated.

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