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by getsimba-ai

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Python

Hybrid

Get Incrementality Test Design

get_incrementality_test_design

Read-onlyIdempotent

Retrieve an incrementality test design calculation for a Bayesian marketing mix model, returning status, power, detectable effects, and diagnostics.

Instructions

Read one test-design calculation: {calculation_id, model_hash, status, submitted_at, started_at, completed_at, request, error, result}. status is operational: queued, running, complete, failed or cancelled; error is {code, message} only when failed (artifact_unreadable, timeout, worker_lost, internal) and a failed calculation carries no numbers. result is present only when complete and is read by its own state, never by key presence: available, unsupported, insufficient_evidence or no_feasible_design, with reasons [{code, detail}] non-empty exactly when not available, plus warnings, assumptions, diagnostics and provenance (method, model artefact, posterior draws, training periods). An available result carries intervention (dates, carryover and measurement end, spend change), model_implied_effect (mean and 94% HDI, parameter uncertainty only; available may be false, e.g. a geo split on a national model, which then gives a national reference only), detectable_effect (cumulative, per-period, relative and, for revenue KPIs, iROAS MDE at the stated alpha and target power), power (at the model mean effect, at the named effect, and assurance), noise, and candidates per duration with the selected one marked. Power here is posterior-averaged: assuming the model is correctly specified and its posterior calibrated, the probability that the pre-specified analysis rejects the null, averaged over the model's forecast uncertainty and observation noise; it is not the probability that this experiment will detect the effect, and a model-implied effect is not a prediction of what the experiment will measure. Requires read:results.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`model_hash`	Yes
`calculation_id`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.17.0Oct 4, 2026

TDQS

B3.1/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent and non-destructive, so safety is covered. The description adds genuinely useful behavioral context beyond the schema: the read:results permission requirement and the non-obvious rule that result must be read by its own state rather than key presence, with defined state values.

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

Conciseness2/5

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

The description is a single dense run-on paragraph that buries the operation's purpose behind an exhaustive payload enumeration. It is information-rich but poorly structured and far longer than needed given that an output schema already exists.

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?

Given the complexity and the presence of an output schema, the description is thorough about state semantics, error codes, auth requirements and the caveats around power/model-implied effect. The main gap is that it never grounds the two required identifiers.

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

Parameters2/5

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

Schema description coverage is 0% and the description never defines model_hash or calculation_id beyond echoing them as output fields. It does not say where these identifiers come from or how they relate, so the description fails to compensate for the coverage gap on the two required params.

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 ('Read one test-design calculation') and lists the identifying fields and payload shape, so an agent can tell it is a singular retrieval of a design calculation. It does not, however, explicitly differentiate itself from siblings like design_incrementality_test or get_incrementality_test.

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?

There is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives. The only usage signal is the trailing 'Requires read:results' permission note; the agent must infer the workflow position from the name alone.

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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