Skip to main content
Glama
kubainter

BoteX

by kubainter
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_stats

Returns an analytics summary of executed BoteX tasks (USD costs, token usage, code-line balance). Args: period: 'week' (last 7 days) or 'month' (last 30 days).

Instructions

Returns an analytics summary of executed BoteX tasks (USD costs, token
usage, code-line balance).
Args:
    period: 'week' (last 7 days) or 'month' (last 30 days).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoweek

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose what data is covered (costs, tokens, code-line balance) and that it aggregates executed tasks rather than live state, which is genuinely useful. However, it says nothing about permissions, scope of the aggregation (all-time vs. per-user), or freshness, leaving gaps for an unannotated tool.

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 core purpose is front-loaded in one sentence and the parameter note is short and scoped. The 'Args:' block is slightly boilerplate but carries no wasted words.

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 single-optional-parameter analytics read tool with an output schema present, the description covers the purpose, the metric set, and the parameter's allowed values and meaning. Return-value details are correctly left to the output schema; only aggregation scope and permissions are unaddressed.

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

Parameters4/5

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

Schema description coverage is 0% and the parameter has no enum, so the description must compensate. It does: 'period' is defined as 'week' (last 7 days) or 'month' (last 30 days), supplying both allowed values and their exact semantics, plus the default implied by the schema. This materially exceeds what the schema conveys.

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 verb and resource ('Returns an analytics summary of executed BoteX tasks') and enumerates the metrics returned (USD costs, token usage, code-line balance), which lets an agent distinguish it from get_task_status or check_health. It stops short of explicitly naming or contrasting with those siblings, so it is clear but not fully differentiated.

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

Usage Guidelines2/5

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

There is no when-to-use guidance: no statement of when an agent should call get_stats rather than get_task_status or check_health, no prerequisites, and no exclusions. Usage can only be inferred from the fact that it summarizes completed tasks.

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

Deploy Server

Other Tools