branchly

get_top_locales

Read-only

Top locales (BCP-47 style, e.g. 'de_DE', 'en_US') across chat, search, and navigation requests, ranked by occurrence count. Use this to understand which languages/regions are being served and where content gaps may exist.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum number of rows to return, ordered by count descending.
`time_filter`	No	Time window for the analytics query. Accepts either: (a) a preset enum value: 'this_month', 'this_year', 'last_month', 'last_30_days' (default), 'last_6_months', 'last_12_months'; or (b) an explicit ISO date range as 'YYYY-MM-DD,YYYY-MM-DD' (inclusive).	last_30_days

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already mark this as read-only and closed-world, so the bar for behavioral disclosure is lower. The description adds meaningful behavioral detail beyond the annotations: it specifies the ranking by count, the BCP-47 style, and the cross-channel aggregation (chat, search, navigation). No contradictions with annotations are present.

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?

The description is two sentences long and front-loads the core output ('Top locales... ranked by occurrence count') before adding a purpose statement. Every phrase earns its place with no repetition or filler.

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 that an output schema exists and annotations cover the read-only safety profile, the description is complete enough for an agent to invoke the tool correctly. It explains what the metric means, the locale format, the data sources, and a practical interpretation of results. Nothing critical is missing.

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

Parameters3/5

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

The input schema has 100% description coverage: both limit and time_filter are fully documented with defaults, constraints, and formats. The description itself adds no parameter-level semantics, but it does not need to because the schema already carries that burden. A baseline of 3 is appropriate.

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

Purpose4/5

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

The description clearly identifies the resource ('locales' in BCP-47 style) and the ordering ('ranked by occurrence count'), and it conveys the aggregation scope across chat, search, and navigation requests. It does not explicitly name sibling tools like get_top_languages or get_top_geographies, but the locale granularity and examples implicitly distinguish it from them.

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 gives an explicit use case: 'Use this to understand which languages/regions are being served and where content gaps may exist.' This is clear context for when to use the tool. It does not mention exclusions or when to prefer a sibling tool instead, which would be needed for a 5.

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

A3.6/5.0

Disambiguation5/5

Each tool targets a distinct resource or metric, and even the closely related analytics tools (e.g. get_top_languages vs get_top_locales, get_top_interaction_sources vs get_top_clicked_urls) are explicitly differentiated in their descriptions. There is no real overlap that would cause an agent to misselect.

Naming Consistency4/5

The verb prefixes create_, get_, list_, read_, and update_ are used predictably, and there is no mixing of camelCase or other conventions. The main inconsistency is that read_sessions is actually a list operation while list_nodes is the equivalent pattern for nodes, and read_session_detail is the singular read.

Tool Count2/5

At 33 tools, this set is well beyond the 16-25 'heavy' range and far above the typical well-scoped 3-15 range. Many of the get_top_* analytics endpoints are individually distinct but could likely be consolidated into fewer parameterized tools to reduce agent selection overhead.

Completeness3/5

The read and analytics side is comprehensive, but the management lifecycle has notable gaps: knowledge nodes support create/read/update but no delete, and data sources/tools lack create/delete operations. Agents can work around some gaps, but content deletion is a clear dead end for a knowledge-base management surface.

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