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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuine analytical context the annotations cannot: the relationships are Granger-significant at a p<0.01 threshold and carry lag-in-days and F-statistic values, which tells the agent how to interpret and trust the output. It omits rate limits, coverage windows, and empty-result behavior.

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?

Two sentences, both front-loaded: the first defines the resource and its statistical content, the second gives the use case. Every clause carries information (significance threshold, lag, F-statistic, purpose) with no filler.

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?

With no output schema, the description carries the burden and does describe the shape of the returned relationships and their fields. It does not say how results are ordered, how many are returned, or what happens when no significant relationships exist, which are minor gaps for a single-parameter read tool.

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?

There is a single required parameter with 100% schema description coverage, so the schema already documents it. The description only implies a country scope and adds no format or accepted-value detail (e.g. ISO codes vs names) beyond what the schema states. Baseline 3 applies 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.

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

States a specific verb and resource ('causal network for a country') and pins down exactly what is returned: Granger-significant lead-lag relationships at p<0.01, with lag in days and F-statistic. This is clearly distinguishable from siblings like get_country_risk or get_early_warning, which report status rather than causal structure.

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?

'Use to explain WHY a risk is building, not just that it is' gives a concrete selection criterion that separates this from the descriptive risk tools. It stops short of naming the specific alternatives (e.g. get_early_warning, get_country_risk) or stating exclusions, so it is clear context rather than a full routing rule.

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