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

With no annotations, the description carries the burden and does disclose the return shape and a subtle semantic detail (panel_age_range is often wider than age_range). It is implicitly a safe, stateless enumeration, but never states there are no side effects or how large the list may be.

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

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

Front-loaded with purpose, then usage routing, then return shape. Every sentence — including the panel_age_range clarification — earns its place and prevents a downstream mistake.

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

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

No output schema exists, yet the description enumerates the returned fields (key, label, description, age_range, panel_age_range) and their meanings, so an agent knows exactly what it gets and how to use the key.

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

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

The tool takes zero parameters, so the baseline of 4 applies; there are no parameter semantics to clarify beyond the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List all available demographic presets') and immediately defines what a preset is (a calibrated mix of demographics + Big Five OCEAN distributions). This distinguishes it from simulation siblings like run_focus_group, which consume rather than enumerate presets.

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

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

Explicitly says 'Call this first if you don't know which preset to use', which is exactly the discovery condition, and names the two downstream consumers (run_focus_group / run_debate) plus the field to pass (demographic_preset). The routing is fully spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.