The Chancery Lane Project

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), or `all` (both, 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

Name	Required	Description	Default
`scope`	No		all

Output Schema

TableJSON Schema

Name	Required	Description	Default
`meta`	Yes
`facets`	Yes

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already indicate readOnlyHint=true (safe read operation) and destructiveHint=false, so the behavioral burden is reduced. The description adds value by explaining the return structure and that it returns vocabulary with counts, but does not mention rate limits or data freshness.

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?

The description is well-structured with clear sections (purpose, scope, returns) and front-loaded with the primary purpose. However, it could be slightly more concise—the 'Returns' section provides details that might be inferred from the output schema but adds clarity.

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 low parameter count (1), zero required parameters, rich annotations (readOnlyHint, openWorldHint), and available sibling tools, the description is complete. It clearly explains the tool's role in the workflow (discovery before taxonomy_content) and all relevant aspects.

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?

Schema coverage is 0%, so the description must compensate for the parameter 'scope'. It does this by detailing the three possible values (clause, guide, all) and their meanings. This provides substantial value beyond the input schema, which only gives type and 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?

The description clearly states it lists taxonomy facets and their value slugs across TCLP content, distinguishing it from sibling tools like taxonomy_content which uses chosen slugs. The specific verb 'list' and resource 'taxonomy facets' make the 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?

The description explains when to use this tool: to discover the vocabulary before calling taxonomy_content. However, it does not explicitly mention when not to use it or alternatives among siblings (like entity_lookup or search).

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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TDQS

A4.7/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: entity_lookup for exact entity matching, search for semantic/full-text search, taxonomy_content for filtered browsing, and taxonomy_facets for discovering filter options. There is no overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with descriptive, domain-specific names (entity_lookup, search, taxonomy_content, taxonomy_facets). The naming is predictable and self-explanatory.

Tool Count5/5

With 4 tools, the set is well-scoped for searching and browsing a legal content knowledge graph. Each tool serves a clear, necessary function without redundancy, and the count feels appropriate for the domain.

Completeness4/5

The tools cover key discovery use cases: exact lookup, free-text search, faceted browsing, and facet exploration. A minor gap is the lack of tools for creating, updating, or deleting content, but that aligns with a read-only knowledge graph server, so completeness is high.

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