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aleccritser

storelink-mcp

by aleccritser

create_replenishment

Raise a replenishment order when stock vs POS delta reaches 6 or more, ordering in case-pack multiples.

Instructions

Raise a replenishment order when get_on_hand_vs_pos delta >= 6.

Call after get_on_hand_vs_pos when units_sold − available is at least 6. Prefer ordering in multiples of product.case_pack from that response.

Args: store_id: Store identifier (e.g. 47). sku: Product SKU to replenish (e.g. 8847291). quantity: Units to order (must be > 0; prefer case_pack multiples). reason: Why you are raising this order (required for audit). order_reason: Optional note stored on the replenishment order record. priority: One of low, normal, high, urgent (default normal).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skuYes
reasonYes
priorityNonormal
quantityYes
store_idYes
order_reasonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It mentions the audit requirement ('reason... required for audit') and the priority options, but does not disclose side effects such as whether calling it multiple times creates duplicate orders, or if special permissions are needed. This is a moderate disclosure, not comprehensive.

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?

The description is well-organized with a purpose sentence, usage guideline, and an Args list. The first two sentences are slightly redundant ('delta >= 6' vs 'units_sold − available is at least 6'), but otherwise every sentence contributes important information. This is efficient and easy to scan.

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 6-parameter create tool with an output schema, the description covers all parameter semantics, the trigger condition, and even a default value. The only missing piece is a note about what happens on success (e.g., returns order ID), but the output schema covers return values, so the description is effectively complete for an agent to invoke it correctly.

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

Parameters5/5

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

The schema has zero description coverage, so the description must explain all parameters. It does this thoroughly: each parameter has an example, constraints (e.g., quantity > 0), and clarification that order_reason is optional, while priority lists its enum values and default. This fully compensates for the absent schema descriptions.

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 opens with 'Raise a replenishment order' – a specific verb + resource that clearly identifies the tool's action. It further distinguishes itself from siblings by tying to 'get_on_hand_vs_pos delta >= 6', making its purpose unique and unambiguous.

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 description gives explicit guidance: 'Call after get_on_hand_vs_pos when units_sold − available is at least 6' and 'Prefer ordering in multiples of product.case_pack from that response.' This provides a clear trigger condition and ordering preference, but it does not explicitly mention alternatives or when not to use the tool, so it falls just short of a 5.

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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