get_briefingGeotone's daily global risk briefing for a date (YYYY-MM-DD): an analytical summary of coverage surges, tone shifts, and notable movers, with the statistics behind each claim.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | UTC date, e.g. 2026-07-02 |
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | ||
| meta | No | ||
| page | No | ||
| headline | Yes | ||
| bodyMarkdown | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "properties": {
+ "bodyMarkdown": {
+ "type": "string"
+ },
+ "date": {
+ "type": "string"
+ },
+ "headline": {
+ "type": "string"
+ },
+ "meta": {
+ "properties": {
+ "attribution": {
+ "type": "string"
+ },
+ "license": {
+ "type": "string"
+ },
+ "source": {
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "page": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "date",
+ "headline",
+ "bodyMarkdown"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds valuable context: it is an analytical summary with statistics behind each claim. This goes beyond the annotation by describing the content and type of analysis provided, improving transparency for an agent.
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?
The description is a single, well-structured sentence that immediately conveys the tool's purpose and output. Every word adds value; no redundancy or 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?
Given the tool has an output schema (not shown but noted) and all parameters are covered by the schema and description, the description is complete. It explains what the output contains, and the read-only annotation covers safety. No gaps are apparent.
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?
Schema coverage is 100% and the description reiterates the date format (YYYY-MM-DD) and its purpose (UTC date for the briefing). This adds practical meaning beyond the raw schema, helping agents understand the parameter's role.
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?
The description explicitly states the tool returns a daily global risk briefing with specific content (coverage surges, tone shifts, notable movers, statistics). It clearly distinguishes from sibling tools that target individual entities (e.g., get_country, get_topic) rather than a curated summary.
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?
The description implies usage for obtaining a daily risk briefing on a specific date, but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. The context of sibling tools suggests this is for an overview, but guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.