get_relationBilateral co-coverage signal for a monitored country pair (e.g. a='cn', b='us'): how much the world's press mentions the two countries together, and in what tone. ~50 strategic pairs are monitored.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First country ISO2 | |
| b | Yes | Second country ISO2 |
| Name | Required | Description | Default |
|---|---|---|---|
| meta | No | ||
| pair | Yes | ||
| snapshots | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "properties": {
+ "meta": {
+ "properties": {
+ "attribution": {
+ "type": "string"
+ },
+ "license": {
+ "type": "string"
+ },
+ "source": {
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "pair": {
+ "type": "string"
+ },
+ "snapshots": {
+ "items": {
+ "additionalProperties": true,
+ "properties": {
+ "coCoverageVol": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "date": {
+ "type": "string"
+ },
+ "meta": {
+ "properties": {
+ "attribution": {
+ "type": "string"
+ },
+ "license": {
+ "type": "string"
+ },
+ "source": {
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "toneAvg": {
+ "type": [
+ "number",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "pair",
+ "snapshots"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds context about the 'signal' nature (coverage + tone) and the limited set of monitored pairs (~50), providing behavioral insight beyond annotations.
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, front-loaded with example and clear purpose. 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.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple parameters, existing output schema, and annotations, the description adequately explains what the tool returns (coverage and tone) and its scope (monitored pairs). No missing critical details.
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% with self-explanatory ISO2 parameters. The description adds value by providing an example (a='cn', b='us') and stating the monitored pair scope, going beyond the schema's minimal descriptions.
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 clearly states the tool retrieves a bilateral co-coverage signal, with an example (a='cn', b='us') and explains what it measures (coverage amount and tone). This distinguishes it from siblings like get_country (single country) or get_trending.
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 bilateral country pairs but does not explicitly state when to use this tool vs alternatives like get_country or get_topic. No exclusions or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.