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chatwoot_get_agent_performance

Read-only

Retrieve an agent's support performance metrics, including open and resolved conversations, average response and resolution times, and CSAT, to assess service quality over a selected period.

Instructions

Returns performance metrics for a specific agent.

Includes: open and resolved conversations, average first response time,
average resolution time, and CSAT.

Args:
    agent_id: Agent ID (use chatwoot_list_agents to get IDs).
    period: Analysis period.
    output_format: Output format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNo30d
agent_idYes
output_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With readOnlyHint=true and destructiveHint=false annotations already establishing a safe read operation, the description adds the metric breakdown but no further behavioral detail such as timezone handling, default-period effects, or empty-result behavior. It is consistent with the annotations and adequate, but not rich.

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 short, front-loaded with the tool's purpose, and uses a compact args list; every line contributes something except the two placeholder parameter lines. It earns a small deduction for those tautological arg descriptions.

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 a three-parameter read-only tool with enums on period and output_format plus an output schema, the key missing piece for correct invocation is agent_id sourcing, which is explicitly covered. The vague period and output_format lines are partly mitigated by schema enums and defaults, leaving only minor ambiguity about what each format produces.

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

Parameters2/5

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

Schema coverage is 0%, so the description needed to carry the parameter-explanation burden. It genuinely helps only for agent_id ('use chatwoot_list_agents to get IDs'); 'period: Analysis period' and 'output_format: Output format' are near-tautological placeholders that add no semantic value beyond the schema's enum lists.

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 opens with a specific verb-resource pair ('Returns performance metrics for a specific agent') and itemizes the metrics, which clearly separates it from sibling performance tools such as team, inbox, and label performance. A selecting agent can identify this as the per-agent metrics tool without opening the schema.

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?

It gives clear context that this tool is for a single agent and points to chatwoot_list_agents as an ID source, but it never says when to prefer this over comparable siblings such as chatwoot_get_team_performance or chatwoot_get_inbox_performance. Usage is implied rather than explicitly scoped against alternatives.

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