Two tools with basic verb-noun naming (get_alerts, get_forecast). Both have descriptions (60-80 chars, below the 194-char baseline) and visible input schemas with typed parameters. However, schemas lack output documentation, parameter descriptions are minimal, and error handling is silent (returns plain strings on failure with no guidance for LLM recovery). No pagination, no structured output, no error classification. Descriptions are functional but sparse, they state WHAT but not WHEN or WHY to use each tool.
Fetches active weather alerts for a given state from the National Weather Service API
Fetches weather forecast for a given latitude and longitude
No output schema documentation. Tools return plain strings; LLMs cannot parse structured data or chain results to downstream tools.
Parameter descriptions are missing or trivial. 'state' and 'latitude'/'longitude' lack format guidance, valid ranges, or constraints. LLMs cannot validate inputs before calling.
Silent error handling. Both tools return plain-text fallback strings on API failure with no guidance for LLM recovery (e.g., 'Unable to fetch alerts'). No error classification or retry hints.
Tool descriptions are 60 - 80 characters, below the 194-char baseline. They state WHAT but omit WHEN to use, prerequisites, or dependencies. 'Fetches weather alerts' does not explain when an LLM should call this vs. get_forecast.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 44 | 2026-07-28+ | v2 |
No pagination or result limits. get_alerts could return hundreds of active alerts; no limit, offset, or total_count field. Large responses blow context windows.