Skip to main content
Glama

Tesla Monthly Report

tesla_monthly_report

Generate a monthly Tesla driving report with key stats and month-over-month comparison, optionally filtered by vehicle.

Instructions

Monthly driving report with stats and comparison to previous month.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesYear (e.g., 2026)
monthYesMonth (1-12)
car_idNoFilter by vehicle ID (default: TESLA_CAR_ID env or first car)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only aggregation but never states permissions, cost of the call, whether data is live or cached, or what timezone/aggregation boundaries apply; with an output schema present the return content is partly covered, but call-time behavior is not.

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?

A single front-loaded sentence with no filler or repetition. It is efficient, though its brevity is partly under-specification rather than deliberate compression.

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?

With an output schema the return shape needn't be explained, and the schema documents all three parameters. What is missing is the disambiguation against near-identical monthly siblings and any behavioral context, which the description leaves entirely to the agent to infer.

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 100%, including the car_id fallback to TESLA_CAR_ID or the first car, so the schema already does the heavy lifting. The description adds no extra meaning about year/month handling or the car_id default, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (monthly driving report) and its contents (stats plus month-over-month comparison), which is better than a tautology. However, it does nothing to distinguish itself from very close siblings like tesla_monthly_summary and generate_monthly_driving_report, leaving an agent unable to choose between them from the description alone.

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 guidance about when to use this tool versus the many overlapping siblings (monthly summary, monthly driving report generator, savings, efficiency breakdowns). The only implied usage is 'when you want a monthly report,' which is circular.

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