Skip to main content
Glama

chatwoot_get_csat_responses

Read-only

Retrieve customer satisfaction survey responses to evaluate support quality. Filter by period, score, inbox, or team to analyze feedback trends.

Instructions

Returns customer satisfaction survey (CSAT) responses.

Enables qualitative analysis of support quality based on customer feedback.

Args:
    period: Analysis period.
    rating: Filter by score (1 to 5). None = all scores.
    inbox_id: Filter by a specific inbox.
    team_id: Filter by a specific team.
    page: Results page.
    output_format: Output format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
periodNo30d
ratingNo
team_idNo
inbox_idNo
output_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to restate safety. It adds no further behavioral context such as pagination semantics, rate limits, or auth requirements, but the output schema and read-only annotation reduce the burden.

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 front-loads the purpose in the first sentence and then presents parameters in a compact list. It is appropriately sized for a simple read tool, though the second sentence and several parameter lines add little beyond the first sentence and schema titles.

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?

For an optional-parameter, read-only tool with an output schema, the description covers the product and all six filters at a usable level. It does not explicitly distinguish itself from chatwoot_get_csat_metrics, but the response-vs-metric distinction is inferable and the schema fills in enum/default details.

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?

With 0% schema description coverage, the description is the only source of parameter meaning. It adds genuine semantics for rating ('1 to 5', 'None = all scores') and clarifies inbox_id/team_id as filters, but period/page/output_format descriptions remain largely tautological and depend on schema enums/defaults.

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?

Description uses a specific verb ('Returns') with a concrete resource ('customer satisfaction survey (CSAT) responses'), making the core purpose clear. It is implicitly distinct from sibling chatwoot_get_csat_metrics (responses vs metrics) but does not explicitly name that alternative, so it misses the sibling-differentiation bar for a 5.

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 phrase 'Enables qualitative analysis of support quality' implies the tool is for inspecting individual feedback rather than aggregates, giving some use context. However, it never states when to prefer this tool over sibling chatwoot_get_csat_metrics, nor provides any exclusions or alternative conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.