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generate_audience

Generate a reproducible synthetic audience from a YAML specification, creating a frozen set of personas and social network to test campaign variants against identical conditions.

Instructions

Generate and save a synthetic audience from a YAML spec.

The audience is a frozen, seeded population of personas plus a social network — the same spec always produces the same people, so campaign variants can be tested against an identical audience.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
spec_yamlYesYAML audience spec. Minimal example: name: saas-founders product_context: "a churn-analytics SaaS tool" size: 300 seed: 42 distributions: age: {mean: 33, sd: 8, min: 22, max: 60} income_bracket: {low: 0.2, mid: 0.5, high: 0.3} trust_in_ads: {mean: 0.2, sd: 0.1} network: topology: watts-strogatz # or barabasi-albert (influencer-heavy) k: 8

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so the description carries full burden. It discloses that the tool generates and saves a synthetic audience with personas and a social network, and that it is seeded for reproducibility. However, it does not mention whether it overwrites existing audiences, authentication needs, or rate limits. The behavioral overview is decent but not exhaustive.

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 sentences plus a short explanation, front-loaded with the main action. Every sentence adds value, no wasted words.

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 low complexity (single parameter, no annotations), the description covers the tool's purpose, input format, and key behavioral trait (frozen/seeded). An output schema exists so description does not need to detail return values. It is sufficiently complete for an agent to understand the tool's role.

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 coverage is 100% and includes a detailed example in the parameter description. The main description adds context about what the YAML spec represents (audience specification) but does not significantly extend beyond the schema-provided information. Baseline score of 3 is appropriate.

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 clearly states the verb 'Generate and save' and the resource 'synthetic audience from a YAML spec'. It distinguishes from sibling tools like 'get_audience' (retrieval) and 'list_audiences' (listing).

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

Usage Guidelines4/5

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

The description explains that the audience is 'frozen, seeded' and 'the same spec always produces the same people', providing strong context for when to use: testing campaign variants against identical audiences. It does not explicitly exclude alternative tools but the usage intent is clear.

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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