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Rahul D Sarker: Marketing & RevOps Tools

Creative Testing Duration Forecaster

creative_testing_duration_forecaster
Read-onlyIdempotent

Forecast how many days an ad creative test needs to reach a sound sample size, from daily spend, expected CPA, variant count, and conversions needed per variant. See the full version at https://rahuldsarker.co/calculators/creative-testing-duration-forecaster

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cpaYesExpected CPA
variantsYesNumber of variants being tested
dailySpendYesDaily test spend
convPerVariantYesConversions needed per variant for a stable read

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds only the calculation inputs, restated from the schema, with no assumptions, rounding, edge cases (e.g. zero CPA/spend), or output shape disclosed. Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence is front-loaded and functional, but the second sentence is a marketing URL that consumes space without helping an agent decide to call or how to invoke the tool. Not wasteful enough to be poor, but not tight.

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 simple four-parameter deterministic calculator with full annotations and no output schema, the description conveys both the input model and the unit of the result ('how many days'). Only the exact return structure and formula assumptions are missing, which is a minor gap.

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 description coverage is 100%, so all four parameters are already documented in the schema itself. The description mirrors those same labels ('daily spend, expected CPA, variant count, conversions needed per variant') without adding units, ranges, or format detail, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: forecast the number of days an ad creative test needs to reach a sound sample size, and names the four inputs that drive the estimate. It does not explicitly differentiate itself from near neighbors like ab_test_significance_calculator or ad_creative_fatigue_forecaster, but the purpose is clear on its own.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no routing to or away from sibling tools such as the significance calculator or fatigue forecaster. The only extra sentence is a promotional link to an external site, which gives no invocation guidance.

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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