Skip to main content
Glama

Generate Travel Narrative Context

generate_travel_narrative_context

Extracts drive and stop data within a time window to build travel narrative timelines for LLM blogging and Vlog scripts.

Instructions

Generate a travel narrative timeline for LLM-powered travel blogging.

Extracts structured drive and stop data within a time window for generating travel narratives or Vlog scripts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
car_idNoFilter by vehicle ID (default: TESLA_CAR_ID env or first car)
end_timeYesISO8601 end time (e.g. "2026-03-03T23:59:59" or "2026-03-03")
start_timeYesISO8601 start time (e.g. "2026-03-01T00:00:00" or "2026-03-01")

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 does not indicate whether the operation is read-only, the granularity of extracted data, pagination behavior, or any constraints. It does say it extracts structured drive and stop data, which is a small behavioral hint, but overall leaves significant gaps for a data-extraction 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 description is two short sentences, front-loaded with the core purpose and followed by a clarifying detail. It is efficient with no wasted words, though the second sentence is slightly redundant with the first.

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?

The tool has an output schema, so the return format need not be explained, and the schema fully covers parameters. However, with no annotations and no usage guidance, the description is only minimally adequate for an agent to confidently select and invoke this tool among many similar siblings.

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%, so the schema already documents all three parameters including the default behavior for car_id. The description adds little parameter-level detail beyond 'within a time window', so the baseline of 3 for high schema coverage 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 states the tool generates a travel narrative timeline and extracts drive and stop data within a time window, which is specific enough. However, it does not distinguish this from siblings like tesla_drives or generate_monthly_driving_report, leaving the agent to infer when this narrative-focused aggregation is preferred.

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 explicit when-to-use guidance, no exclusions, and no named alternatives. The phrase 'for LLM-powered travel blogging' hints at the use case but does not tell the agent when to select this over tesla_drives or other trip tools.

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