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chatwoot_get_captain_faq_stats

Read-only

Track usage and effectiveness statistics for a Captain assistant's FAQ knowledge base. Analyze performance over a chosen period to identify improvement areas.

Instructions

Returns usage and effectiveness statistics for a Captain assistant's knowledge base (FAQ).

Args:
    assistant_id: Assistant ID (use chatwoot_list_captain_assistants).
    range: Analysis period in days or month (7, 30, 90, this_month, last_month).
    output_format: Output format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeNo7
assistant_idYes
output_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
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 safety profile is covered and no contradiction exists. The description adds little behavioral context beyond the read-only nature; it does not describe aggregation behavior or response details, though the output schema can carry part of that 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?

Compact and front-loaded: the purpose sentence comes first, fiollowed by a concise Args block. The output_format line is somewhat redundant, but the rest of the description is eifther informative or a useful cross-reference.

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

Completeness3/5

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

For a read-only stats tool with an output schema, the invocation parameters are mostly covered and assistant_id sourcing is supplied. However, it does not clarify what counts as 'usage and effectiveness' or how this tool differs from neighboring Captain analytics tools, so the agent's selection confidence remains incomplete.

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 0% so the description carries the param semantics burden. It adds useful meaning for assistant_id by pointing to chatwoot_list_captain_assistants, and for range by describing it as an analysis period in days or month. However, output_format is only restated as 'Output format', adding no real meaning beyond the enum.

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?

States a specific action, 'Returns usage and effectiveness statistics', and a specific resource, 'Captain assistant's knowledge base (FAQ)', which is enough to identify its domain among the Captain analytics siblings. It does not explicitly distinguish itself from chatwoot_get_captain_metrics or chatwoot_get_captain_overview, so it misses the top tier of differentiation.

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?

Implied usage is clear: call this when you need FAQ usage and effectiveness stats for a Captain assistant, and the assistant_id hint references chatwoot_list_captain_assistants. However, there is no explicit when-not-to-use guidance or alternative routing among the many Captain analytics tools, leaving selection partially to inference.

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