latest_observationMost recent observation for a single series, as {date, value}. Example: seriesId "SECBREPOEFF" returns the current Riksbank policy rate; "SEKUSDPMI" returns the latest USD/SEK fixing.
| Name | Required | Description | Default |
|---|---|---|---|
| seriesId | Yes | Series ID, e.g. "SECBREPOEFF" (policy rate) or "SEKUSDPMI" (USD/SEK). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "seriesId": "SECBREPOEFF"
+ },
+ {
+ "seriesId": "SEKUSDPMI"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, idempotentHint) already mark it as safe. The description adds return format {date, value} and concrete examples, providing context beyond annotations. No contradictions.
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 plus examples, front-loaded with purpose. No wasted words, efficient and clear.
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?
For a simple tool with one parameter and no output schema, the description fully covers what it does, return structure, and parameter usage. Combined with annotations, it is complete.
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 single parameter 'seriesId' has full schema coverage. The description enriches it with examples and their real-world meaning (e.g., policy rate, exchange rate), helping the agent choose meaningful values.
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 it returns the most recent observation for a single series as {date, value}. Examples with specific series IDs clarify its function. It is distinct from sibling tool 'get_observations' which likely returns multiple observations.
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 use when a single latest observation is needed, but it does not directly compare to alternatives like 'get_observations' nor provide explicit when-not-to-use guidance.
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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