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Forthcast Inventory

Forecast demand series

forecast_demand_series
Read-onlyIdempotent

Use this when someone pastes past sales numbers and asks what to expect next month, next quarter or next season. Takes 3 to 365 monthly, weekly or daily totals (oldest first) and returns the next periods with an 80 percent range, the model used (Holt-Winters seasonal, damped trend, Croston for intermittent demand, or moving average) and why. Works without a connected store.

Input Schema

NameRequiredDescriptionDefault
salesYesPast sales totals per period, oldest first.
periodNoGranularity of the sales list.monthly
horizonNoPeriods to forecast: up to 12 monthly, 26 weekly, 90 daily.

Output Schema

NameRequiredDescriptionDefault
lowerYes
notesYes
trendYes
upperYes
methodYes
periodYes
forecastYes
confidenceYes
seasonalityYes
connect_hintNoHow to get this done automatically on live store data.Forthcast does this automatically for Shopify stores: https://apps.shopify.com/forthcast
method_labelYes
history_pointsYes
history_averageYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuine value beyond that: it discloses return content (next periods, 80% interval, named model and rationale) and that no store connection is required.

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 sentences, front-loaded with the use case before mechanics, and every clause carries information an agent needs. No filler or redundancy.

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

Completeness5/5

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

A low-complexity, three-parameter read tool with full schema coverage, an output schema, and complete annotations. The description's extra note about model selection and the disconnected-store capability covers the remaining operational questions an agent would have.

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 `sales`, `period` and `horizon` are all documented, including the min/max item counts and enum values. The description restates the 3–365 range and the monthly/weekly/daily choice already present in the schema and adds no format detail beyond 'oldest first', so baseline 3 applies.

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?

States a specific verb and resource (forecast a demand series from past sales totals) plus scope: 3–365 periods, monthly/weekly/daily, returning future periods with an 80% range and the model chosen. An agent can distinguish this from reorder-point or order-quantity siblings without opening any schema.

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?

Gives a clear triggering condition — someone pastes historical sales and asks what to expect next month/quarter/season — and notes it works without a connected store, removing a prerequisite. It doesn't explicitly name which sibling to use instead when the question is about reorder points or order sizing, so it stops short of the 5 bar.

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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