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update_chat_request_analytics

Idempotent

Update analytics fields on a chat request: summary, tags, answer_type, sentiment, classification_topic_id, or classification_intent_id. Only provided fields are updated. Use this to annotate or reclassify chat interactions after the fact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoList of tags to attach to the chat request.
summaryNoShort summary or annotation for the chat request.
sentimentNoSentiment classification: 'positive', 'negative', or 'neutral'.
answer_typeNoAnswer type classification: 'complete', 'no_knowledge', 'outside_scope', 'small_talk', or 'follow_up_question'.
chat_request_idYes
classification_topic_idNoUUID of the classification topic to assign to this chat request.
classification_intent_idNoUUID of the classification intent to assign to this chat request.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate non-read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by stating 'Only provided fields are updated' (partial-update semantics) and positioning this as a post-hoc annotation/reclassification action. 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.

Conciseness5/5

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

Two sentences with no wasted words. The field list and partial-update behavior are front-loaded, and the intended use case appears in the second sentence. Every clause earns its place.

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 the annotations (idempotent, non-destructive, not read-only), an output schema, and the clear partial-update wording, the description is largely complete for an agent to invoke it correctly. The only meaningful gap is clarifying null-vs-absent behavior for optional fields, and possibly noting that at least one updateable field should be supplied, though the schema already implies the required ID alone might be a no-op.

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 86%, so the schema already documents most parameters. The description lists the updateable field names but adds little semantic meaning beyond what the schema provides. It does clarify partial updates but does not address how null values should be interpreted versus absent fields, which matters for this nullable-default schema.

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 uses a specific verb ('Update') and names the exact resource ('analytics fields on a chat request'), followed by an explicit list of modifiable fields. It is clearly distinguishable from sibling update tools like update_data_source or update_node, which target different entities.

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 instruction 'Use this to annotate or reclassify chat interactions after the fact' gives clear context for when the tool should be invoked. It does not explicitly state when not to use it or name alternatives, but given the sibling tools are mostly reads or updates of other entities, the intended scope is obvious.

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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