branchly

read_sessions

Read-only

List sessions for application. Filter by interaction types (chat, search, navigation, form_submission, voice), embed types, answer types, tool IDs, or a full-text search query. Each session includes its full history, but document chunks and tool calls are returned as references (IDs + titles) rather than full content.Returns paginated results ordered by start time descending.

Input Schema

TableJSON Schema

Name	Required	Description
`page`	No
`limit`	No
`tool_ids`	No	Filter sessions that involved specific tool UUID(s). Only exists for chat sessions.
`embed_types`	No	Filter by embed type(s) through which sessions were initiated.
`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).
`answer_types`	No	Filter by answer type(s) returned to users. Only exists for chat sessions.
`interactions`	No	'chat', 'search', 'navigation', 'form_submission', or 'voice'.
`search_query`	No	Full-text search across session content. Returns all when omitted.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already establish readOnlyHint=true, and the description adds meaningful behavioral detail: sessions include full history, document chunks and tool calls are returned as references (IDs + titles) rather than full content, and results are paginated and ordered by start time descending. No contradiction with annotations.

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 concise and front-loaded with the core action and resource. The second sentence is dense but valuable; a minor formatting typo ('content.Returns') slightly detracts from polish.

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

Completeness4/5

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

Given 8 parameters, high schema coverage, an output schema, and readOnly annotations, the description covers the important behavioral gaps: reference-only content, pagination, and ordering. It could mention default time_filter or page/limit behavior, but these are already in the schema.

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?

Schema description coverage is 75%, so the schema already documents most parameters, including time_filter formats and enum values. The description restates filters in prose but adds little semantic detail beyond what the schema provides.

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 states a specific verb and resource: 'List sessions for application.' It then enumerates the available filters (interactions, embed types, answer types, tool IDs, full-text search), making the tool's scope immediately clear and distinguishing it from siblings such as read_session_detail.

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

Usage Guidelines3/5

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

The description clearly conveys when to use this listing tool and what filtering capabilities it offers, but it does not explicitly contrast it with read_session_detail or other analytics siblings, nor does it state when not to use it. Usage context is implied rather than spelled out.

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

A3.7/5.0

Disambiguation5/5

Each tool targets a distinct resource or metric. The many get_top_* endpoints are differentiated by the specific dimension measured, and read_* / list_* / get_* verbs consistently separate detail retrieval from aggregation and paginated listings. Explicit distinctions like get_top_languages vs get_top_locales and get_top_interaction_sources vs get_top_clicked_urls remove ambiguity.

Naming Consistency5/5

Tool names follow a predictable verb_noun pattern: create_* for mutations that add, update_* for edits, list_* for paginated collections, read_* for detailed record access, and get_* for aggregate analytics. Even with 33 tools the naming convention is uniform and readable.

Tool Count2/5

33 tools exceeds the 25+ threshold for 'too many' and is heavy for a single server surface. While the analytics getters are individually focused, the set is larger than typical for an MCP server and could be consolidated or grouped more tightly.

Completeness3/5

Analytics coverage is thorough, and nodes/prompts have create/read/update lifecycles. However, there are no delete operations anywhere, and data sources and tools support update but not create or delete, leaving notable lifecycle gaps for administrative tasks.

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