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lokesh-sparrow

PNPC-MCP-Tally-Prime

set_bill_of_materials

DestructiveIdempotent

Attach a bill of materials to a finished-goods stock item in Tally Prime, so manufacturing journals use the predefined component ratio instead of typed quantities.

Instructions

Attach a Bill of Materials (recipe) to an existing finished-goods stock item, so a Manufacturing/Stock Journal producing this item can have its component quantities computed from a fixed ratio instead of typed by hand every time. Uses Tally's native MULTICOMPONENTLIST.LIST structure. This is a pure convenience layer over create_stock_journal — it does not affect stock or post anything by itself; you still call create_stock_journal to actually record a production run, scaling each component's qty by the ratio to basicQty yourself (this tool does not auto-compute that scaling for you). EXTRAPOLATED from a genuine Tally-exported XML template's stock item master shape, not reverse-engineered from a real manually-created BOM — verify carefully after use, especially natureOfItem's accepted values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitNoUnit of measure for basicQty, e.g. 'Nos'.
basicQtyNoThe quantity of stockItem this recipe produces (the ratio base). Defaults to 1.
stockItemYesExact name of the existing finished-goods stock item to attach this BOM to
componentsYesThe raw materials (and any co-products/scrap) in this recipe.
componentListNameNoName for this BOM/recipe (Tally allows more than one per item). Defaults to 'Primary'.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.11.2

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already mark destructiveHint=true and idempotentHint=true, but the description goes further: it states this tool 'does not affect stock or post anything by itself', clarifies that scaling is NOT auto-computed, and warns about being extrapolated from an XML template, advising verification. This adds significant behavioral detail beyond annotations.

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 longer than minimal but every sentence earns its place: purpose, mechanism, limitation, and caveat are all covered. There is no fluff, though it could be slightly tightened without losing essential information.

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?

For a mutation tool with destructive hints and no output schema, the description thoroughly covers what the tool does, its side effects (or lack thereof), the required companion call, and a verification warning. An agent has enough context to use it correctly and safely.

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

Parameters4/5

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

Schema coverage is 100%, so the schema documents all parameters. The description adds meaning by explaining that components should be scaled by the ratio to basicQty (and you must do this yourself), and flags caution about natureOfItem's accepted values. This goes beyond schema definitions.

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 states a specific verb and resource ('Attach a Bill of Materials to an existing finished-goods stock item') and clearly distinguishes it from create_stock_journal by calling it a convenience layer. The purpose is unambiguous and not a tautology.

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?

It explicitly explains when this tool is used (to set up a fixed-ratio recipe) and that you 'still call create_stock_journal to actually record a production run', which guides the agent toward the correct companion tool. It doesn't list exclusion criteria (e.g., when not to use), but the context is clear enough.

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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