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MarketingBNG

tally-mcp

by MarketingBNG

tally_calculate_materiality

Compute overall, performance, and clearly-trivial materiality thresholds from a benchmark amount, with the documented basis for audit workpapers.

Instructions

Compute overall materiality, performance materiality and the clearly-trivial threshold from a benchmark figure, with the basis documented alongside.

WHEN TO USE: when planning an audit or review, and whenever a question depends on whether an amount is material. Use the returned figures rather than working thresholds out in conversation — the arithmetic here is exact and it is recorded with its basis, which is what a workpaper needs.

YOU MUST SUPPLY THE BENCHMARK AMOUNT. This tool does not read it from TallyPrime, on purpose: deciding which figure is "revenue" or "profit before tax" in a particular set of books is a judgement, and a tool that guessed wrong would produce a credible threshold on the wrong base. Read the figure from tally_get_statement, agree it with the user, then pass it here.

RETURNS: overall materiality, performance materiality, the clearly-trivial threshold, and the full basis — benchmark used, amount, percentages applied, and the customary range for that benchmark so the choice can be seen to be reasonable or deliberately not.

PERCENTAGES: sensible defaults are applied and stated (see the basis in the response), and every one can be overridden. No auditing standard fixes a percentage — materiality is a judgement about the users of the financial statements — so treat the defaults as a documented starting point to discuss, never as the answer.

PAGINATION: not applicable.

Read-only: nothing here can modify TallyPrime.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYesThe benchmark amount, as a plain number string, e.g. "12500000". Read it from the financial statements and agree it with the user first. Sign is ignored — a loss is as valid a base as a profit.
currencyNoCurrency label for the output. Defaults to INR.
benchmarkYesWhich figure the threshold is based on. The choice is a judgement: profit-based for profitable trading entities, revenue or assets where profit is volatile or marginal.
overallPercentNoPercentage of the benchmark for overall materiality, e.g. "5". Defaults to the customary figure for the chosen benchmark, which is stated in the response.
performancePercentNoPerformance materiality as a percentage OF OVERALL MATERIALITY, e.g. "75". Customarily 50–75%, lower where the risk of misstatement is higher. Defaults to 75.
clearlyTrivialPercentNoClearly-trivial threshold as a percentage OF OVERALL MATERIALITY, e.g. "5". Customarily 5%. Defaults to 5.
Behavior5/5

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

No annotations are provided, so the description carries full responsibility. It discloses that the tool does not read from TallyPrime by design, explains the reasoning about benchmark judgement, states defaults and override capabilities, and confirms read-only behavior. It also describes the exact return content (materiality figures and documented basis), leaving no surprises.

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 well-structured with clear sections (WHEN TO USE, REQUIREMENTS, RETURNS, PERCENTAGES, PAGINATION) and front-loads the core purpose. Each sentence adds necessary information without padding. The length is justified by the tool's complexity and the need to explain the judgment calls involved.

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 tool with no output schema, the description thoroughly explains what will be returned (materiality figures and full basis). It covers prerequisite actions (reading and agreeing on the benchmark), parameter relationships, and the philosophical grounding of materiality percentages. Nothing an agent needs to decide whether and how to invoke the tool is missing.

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?

Although schema coverage is 100%, the description adds significant value: it explains that perfomancePercent is relative to overall materiality, clearlyTrivialPercent also relative to overall materiality, the benchmark choice as a judgement call, and the amount as a plain string with sign ignored. It clarifies relationships between parameters that the schema alone does not convey, making the tool easier to use correctly.

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 ('Compute') and resource ('overall materiality, performance materiality and the clearly-trivial threshold') with a clear basis document. The description differentiates from sibling tools by explicitly noting it calculates rather than reads data, and the 'WHEN TO USE' section makes the intended role unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use (planning an audit/review or when materiality is in question) and when not to rely on it for reading figures (must supply the benchmark manually, read from tally_get_statement and agree with the user). It effectively guides the agent to the correct sibling tool for data retrieval while positioning this tool as the computation layer.

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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