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by getsimba-ai

get_contribution_groups

Retrieve stored contribution groups for a marketing mix model using its model hash. Access legacy dashboard-saved configs verbatim.

Instructions

Read the stored contribution groups for a model (#436). Legacy dashboard-saved configs are served verbatim.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_hashYes
Behavior3/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It adds a useful behavioral detail: 'Legacy dashboard-saved configs are served verbatim.' However, it does not address what happens for invalid or missing model hashes, auth requirements, or possible transformations for non-legacy configs.

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 two terse sentences with the main action front-loaded. The legacy-config note earns its place and does not add clutter, so the structure is efficient and scannable.

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

Completeness3/5

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

This is a low-complexity, single-parameter read tool, so a very long description is not required. Still, with no output schema and no annotations, the description leaves the return shape and error behavior to inference; mentioning the legacy verbatim case helps but does not fully complete the picture.

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 coverage is 0%, and the description does not explain 'model_hash' beyond associating it with a model. The parameter name is somewhat self-explanatory, but the description offers no guidance on where the hash comes from, its format, or how it should be supplied, leaving an uncompensated gap.

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 uses a specific verb ('Read') and identifies the resource ('stored contribution groups for a model'). It clearly differentiates this getter from the sibling 'set_contribution_groups' tool without needing to open schemas.

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

Usage Guidelines3/5

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

The description implies this tool is for retrieving stored contribution groups, but it provides no explicit guidance on when to prefer it over alternatives or when it should not be used. The existence of a setter sibling is evident from the sibling list, but the description does not explicitly route the agent.

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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