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tclp-mcp

by io.github.thechancerylaneproject
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taxonomy_facets

Read-only

List taxonomy facets and their value slugs across TCLP content.

Facets are taxonomy categories like `sector`, `practice_area`,
`application`, and `jurisdiction`. Each facet returns the list of slugs
that actually appear on the graph, with counts. Use this to discover
the vocabulary, then call `taxonomy_content` with chosen slugs.

Args:
    scope: Which labels to include — `clause` (ClauseName only), `guide`
           (Guide only), `legal_resource` (laws, regulations, standards and
           frameworks; facets `jurisdiction` and `sector` only), or `all`
           (clauses and guides, the default).

Returns:
    JSON with "meta" and "facets". Each facet has `name`, `applies_to`
    (list of Neo4j labels carrying it), and `values` (list of
    `{slug, count}`, sorted by count desc).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoall

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaYes
facetsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / scope / enum
      Added value: +[
+  "clause",
+  "guide",
+  "legal_resource",
+  "all"
+]
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$defs": {
+    "_TaxonomyFacet": {
+      "properties": {
+        "applies_to": {
+          "items": {
+            "type": "string"
+          },
+          "title": "Applies To",
+          "type": "array"
+        },
+        "name": {
+          "title": "Name",
+          "type": "string"
+        },
+        "values": {
+          "items": {
+            "$ref": "#/$defs/_TaxonomyFacetValue"
+          },
+          "title": "Values",
+          "type": "array"
+        }
+      },
+      "required": [
+        "name",
+        "applies_to",
+        "values"
+      ],
+      "title": "_TaxonomyFacet",
+      "type": "object"
+    },
+    "_TaxonomyFacetValue": {
+      "properties": {
+        "count": {
+          "title": "Count",
+          "type": "integer"
+        },
+        "slug": {
+          "title": "Slug",
+          "type": "string"
+        }
+      },
+      "required": [
+        "slug",
+        "count"
+      ],
+      "title": "_TaxonomyFacetValue",
+      "type": "object"
+    },
+    "_TaxonomyFacetsMeta": {
+      "properties": {
+        "request_id": {
+          "title": "Request Id",
+          "type": "string"
+        },
+        "took_ms": {
+          "title": "Took Ms",
+          "type": "integer"
+        }
+      },
+      "required": [
+        "took_ms",
+        "request_id"
+      ],
+      "title": "_TaxonomyFacetsMeta",
+      "type": "object"
+    }
+  },
+  "properties": {
+    "facets": {
+      "items": {
+        "$ref": "#/$defs/_TaxonomyFacet"
+      },
+      "title": "Facets",
+      "type": "array"
+    },
+    "meta": {
+      "$ref": "#/$defs/_TaxonomyFacetsMeta"
+    }
+  },
+  "required": [
+    "meta",
+    "facets"
+  ],
+  "title": "TaxonomyFacetsResult",
+  "type": "object"
+}
  3. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, openWorld), so the bar is lower. The description adds genuinely useful behavior: facets are filtered by graph labels, counts reflect slugs that 'actually appear on the graph', and legal_resource scope is restricted to jurisdiction/sector facets only.

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

Conciseness4/5

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

Front-loaded with purpose then Args/Returns, with little waste. The Returns section partly restates what the output schema would provide, but it also clarifies that values are count-sorted, so it mostly earns its place.

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?

For a single-parameter discovery tool with an output schema and annotations, the description covers purpose, workflow routing, scope semantics, and return shape. Nothing an agent needs to invoke it correctly is missing.

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?

Schema coverage is 0% (only an enum with no descriptions), so the description must carry semantics. It defines all four scope values, including the non-obvious restriction that legal_resource yields only jurisdiction and sector facets, and gives the default.

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?

States a specific verb and resource ('List taxonomy facets and their value slugs') with the scope of content it covers ('across TCLP content'). It also names the sibling it feeds into ('then call taxonomy_content'), so an agent can distinguish it from related taxonomy tools.

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?

Explicitly prescribes the workflow: use this to discover the vocabulary, then call taxonomy_content with chosen slugs. That is a clear when-to-use statement plus a named alternative, leaving nothing to inference.

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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