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adjust_stock

Update product stock quantities with a positive or negative change, attach a reason, and automatically log the stock movement.

Instructions

Adjust physical stock quantity for a product (+/- change) with an audit reason (e.g. 'purchase', 'damage', 'adjustment', 'return'). Automatically records a stock movement.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesProduct UUID (required).
noteNoOptional audit note for the stock adjustment.
reasonNoReason: 'purchase', 'sale', 'adjustment', 'damage', 'return'.
quantityChangeYesQuantity change (e.g. +10 to add stock, -3 for damaged goods).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoResult data payload from Chirak API.
successNoStatus of the tool execution.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=false and idempotentHint=false, so it's a mutating, non-idempotent operation. The description adds that it 'Automatically records a stock movement,' which is a non-obvious side effect not captured by the annotations. This provides valuable extra behavioral context.

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?

Two concise sentences front-load the primary action and side effect. Every word earns its place, with no fluff or repetition. The examples are directly relevant to usage.

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?

The description covers the core purpose, side effect, and gives representative reasons. With an existing output schema and 100% parameter coverage, the missing pieces (e.g., when to use vs. record_sale, edge cases) are minor. It's sufficient for an agent to invoke correctly in most scenarios.

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%, so parameters are already documented. The description adds examples for quantityChange (+10, -3) and reason types, but these largely echo the schema descriptions. It adds marginal value over the schema, topping up with the phrase 'audit reason' but not providing substantial new meaning.

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 clearly states the action: 'Adjust physical stock quantity for a product (+/- change)' with a specific resource (product) and scope. It also mentions the audit reason and examples, making the tool's purpose unambiguous and distinct from siblings like record_sale or update_product.

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 description implies usage through reason examples ('purchase', 'damage', 'adjustment', 'return') but does not explicitly contrast with alternatives such as record_sale or update_product. It lacks a direct 'use when...' or 'instead of...' instruction, leaving the decision partly to inference.

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