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Look up an audience

get_audience
Read-onlyIdempotent

Look up one audience in detail. Free. How many people, who they are, which real survey answers anchor them, and what this workspace has already asked them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audience_idYesAn id from list_audiences

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
okNofalse means the call failed: read `error` and `hint`
hintNoWhat to change, when ok is false
kindNo
nameNo
nextNoWhat to do next
noteNoSomething to tell the user or keep in mind
sizeNo
errorNoError code, when ok is false
usageNoWhat this workspace has already asked this audience
peopleNoThe people a run would seat: total, and whether more can be drawn
priorsNoThe real survey questions that anchor this audience
definitionNomeasured, estimated, unsupported
populationNoScale: n, share_pct, scope, tier
provenanceNoEvidence tier: anchored, verified, calibrated or model_est
size_scopeNoWhat `size` counts: people in the measured population, real respondents or synthetic individuals
demographicsNoOne entry per dimension, each with its shares

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedOutput schema / properties / provenance / description
      Previous value: -"Evidence tier: verified, calibrated or model_est"New value: +"Evidence tier: anchored, verified, calibrated or model_est"
    • changedOutput schema / properties / size_scope / description
      Previous value: -"What `size` counts: people in the census frame, real respondents or synthetic individuals"New value: +"What `size` counts: people in the measured population, real respondents or synthetic individuals"
  2. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so the safety profile is fully covered. The description adds genuinely new behavioral context with 'Free' (no cost implication) and by sketching what the response contains; beyond that it discloses nothing about auth, rate limits, or error modes.

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?

Three short, front-loaded sentences with no filler; the purpose leads and the payoff is itemized compactly. The teletype-style fragments ('in detail. Free.') read slightly clipped rather than as a flowing spec, but nothing is wasted.

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?

With an output schema present, the description needn't explain return values, and its annotations cover the safety profile, so the omission of parameter detail and usage exclusions is tolerable for a one-parameter read tool. It falls short of complete only in not naming the sibling it complements.

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?

There is a single required parameter with 100% schema description coverage ('An id from list_audiences'), so the schema already carries the semantics. The description adds nothing about the id, its format, or valid sources, matching the baseline of 3 when the schema does the heavy lifting.

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 names a specific verb and resource ('Look up one audience') and the word 'one' implicitly distinguishes it from the sibling list_audiences. It also enumerates the depth of the lookup ('How many people, who they are, which real survey answers anchor them'), so an agent knows exactly what this tool returns versus a listing tool.

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?

Usage is only implied: 'one audience' suggests use after list_audiences and before per-audience actions, and 'Free' hints it is cheap to call. There is no explicit when-to-use statement, no exclusion, and no alternative tool named, so the agent must infer context from the sibling list.

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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