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Bis

by io.github.pipeworx-io
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List Curated Flows

list_curated_flows
Read-onlyIdempotent

List BIS dataflow refs we have pre-vetted, grouped by topic (rates, fx, banking, debt, credit, property, derivatives, finance). Use the flow_ref with fetch_dataset. For everything else use search_dataflows or browse https://stats.bis.org.

Input Schema

NameRequiredDescriptionDefault
topicNoOptional topic filter

Output Schema

NameRequiredDescriptionDefault
noteYesAdditional information about full catalog
countYesNumber of flows matching the filter
flowsYesCurated dataflow objects
topicsYesAll available topics in the curated catalog

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "topic": "rates"
+  },
+  {}
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of flows matching the filter",
+      "type": "number"
+    },
+    "flows": {
+      "description": "Curated dataflow objects",
+      "items": {
+        "properties": {
+          "flow_ref": {
+            "description": "SDMX dataflow reference",
+            "type": "string"
+          },
+          "title": {
+            "description": "Human-readable flow title",
+            "type": "string"
+          },
+          "topic": {
+            "description": "Topic category",
+            "type": "string"
+          }
+        },
+        "required": [
+          "flow_ref",
+          "topic",
+          "title"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "note": {
+      "description": "Additional information about full catalog",
+      "type": "string"
+    },
+    "topics": {
+      "description": "All available topics in the curated catalog",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "count",
+    "topics",
+    "flows",
+    "note"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds relevant context about pre-vetted content and topic grouping, which goes beyond the annotations. It doesn't mention pagination or return format, but this is covered by the output schema and the low-risk nature of the tool.

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?

Two tight sentences front-load the purpose, list topics, and provide usage directions. Every word earns its place; no fluff or redundancy.

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 simple input schema, an output schema, and annotations that cover safety, the description fully covers what the tool does, how to use it, and when to use alternatives. No gaps remain.

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

Parameters4/5

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

The schema describes the 'topic' parameter as an optional filter, and the description enriches this by enumerating valid topic values (rates, fx, banking, etc.). This adds meaningful semantic value beyond the schema's generic description.

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?

The description clearly states the tool lists pre-vetted BIS dataflow refs grouped by topic, with explicit topic examples. It differentiates from siblings by directing users to use fetch_dataset with the flow_ref and search_dataflows for everything else.

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

Usage Guidelines5/5

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

Provides explicit usage guidance: use the flow_ref with fetch_dataset, and for everything else use search_dataflows or browse stats.bis.org. This clearly delineates when to use this tool versus alternatives.

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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