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Get audience targeting

get_targeting
Read-onlyIdempotent

Current audience: country, gender, age ranges, employment, education, ethnicity, marital status, household income, location selection — plus the option dictionaries for each dimension and a live price quote.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
survey_idYesSurvey id (see list_surveys, or the survey_id returned by a create tool).

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=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that it returns 'current audience' and a 'live price quote,' implying real-time data retrieval. It doesn't disclose any side effects or requirements beyond that, but given the annotations, this is acceptable.

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 a single sentence that front-loads the key subject ('Current audience') and enumerates the dimensions without waste. It is concise and structured effectively.

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?

The tool has one required parameter, no output schema, and annotations covering safety. The description tells the agent exactly what the response contains—audience dimensions, option dictionaries, and a live price quote—which is sufficient for a read operation. It doesn't mention error cases or whether the survey must exist, but the schema implies survey_id is required. This is fairly complete for its simplicity.

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?

The schema fully describes survey_id with a clear explanation and a minimum value, and the description does not mention parameters at all. With 100% schema coverage, the baseline is 3; the description adds no additional parameter meaning.

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?

The description explicitly lists the returned data (country, gender, age ranges, etc., plus option dictionaries and a live price quote), clearly indicating this is a retrieval of current targeting settings. It distinguishes from set_targeting (which modifies) and get_price_quote (which only returns a quote), though the inclusion of a price quote might overlap with the latter. The name and title reinforce the get action.

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?

The description provides no guidance on when to use this tool versus alternatives like get_price_quote, set_targeting, or get_survey_options. It doesn't mention that this is read-only or that it should be used to review current settings before editing. The agent must infer usage from the name and annotations.

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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