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Glama

Riksbank Se

by io.github.pipeworx-io
OverviewAdmin

List Series

list_series
Read-onlyIdempotent

Browse/search the Riksbank SWEA catalogue of time series (interest rates and SEK exchange rates). Returns series IDs plus descriptions and available date ranges. Optionally filter by a case-insensitive substring matched against the series ID and descriptions, e.g. "policy", "rate", "EUR", or "exchange". Series IDs are string codes; well-known ones: SECBREPOEFF (policy rate, formerly repo rate), SECBDEPOEFF (deposit rate), SECBLENDEFF (lending rate), SEKEURPMI (EUR/SEK fixing), SEKUSDPMI (USD/SEK fixing), SEKGBPPMI (GBP/SEK), SEKJPYPMI (JPY/SEK). Omit query to list all (~117 series).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (default 50).
queryNoCase-insensitive substring matched against series ID/descriptions, e.g. "EUR" or "policy".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "policy"
+  },
+  {
+    "limit": 20,
+    "query": "EUR"
+  }
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld. Description adds substantive behavioral details: case-insensitive substring matching, return content, and the fact that omitting query returns full list. This goes beyond annotations without contradicting them.

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

Conciseness5/5

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

Description is concise (5 sentences), front-loaded with core purpose, then expands with filtering details and examples. No redundant or missing information; every sentence serves a clear function.

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

Completeness5/5

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

Given the tool's simplicity (2 optional params, no output schema, read-only annotations), the description covers all necessary aspects: purpose, result contents, filtering behavior, and practical examples. An agent has sufficient information to use this tool correctly.

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

Parameters5/5

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

Although schema covers both parameters (100% coverage), description adds significant practical value: examples of query values ('policy', 'EUR'), lists well-known series IDs, explains default behavior (list all ~117 series). This is exactly the kind of enrichment that helps an agent select correct parameter values.

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

Purpose5/5

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

Description clearly states verb 'Browse/search' and specific resource 'Riksbank SWEA catalogue of time series'. It details what is returned (series IDs, descriptions, date ranges) and provides concrete examples of well-known series, making purpose unambiguous.

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

Usage Guidelines4/5

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

Description implies usage: for finding and filtering series. Provides examples of useful queries and notes omitting query lists all. Does not explicitly contrast with sibling tools like 'get_observations' or 'latest_observation', but context is clear enough for an agent to infer when to use this tool.

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

All Riksbank Se toolsInspect
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