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Get Top Ten / Peak Water Levels

noaa_get_top_ten_water_levels
Read-onlyIdempotent

Get a station's highest recorded water levels: analysis "toptenwaterlevels" returns the ten highest events on record (with date, height, causal event name like "Great New England Hurricane", and category); "peakwaterlevels" returns peak event records (optionally filtered by year).

Heights are relative to the requested datum (MHHW is typical for flood comparisons). Use for "what's the worst flooding ever recorded at X?".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoFor peakwaterlevels: filter to one year.
datumNoReference datum for reported heights (MHHW is standard for flood context).MHHW
unitsNoUnit system. english: feet, °F, knots (wind AND currents), nautical miles. metric: meters, °C, m/s for wind but cm/s for currents, kilometers. Air pressure is millibars and salinity is PSU in BOTH systems.english
stationYesStation ID. Water-level/met stations use 7-digit numeric IDs (e.g. "9414290" San Francisco); current stations use alphanumeric IDs (e.g. "cb0102"). Find stations with noaa_search_stations or noaa_find_nearest_stations.
analysisNo"toptenwaterlevels" = ten highest on record; "peakwaterlevels" = peak event records.toptenwaterlevels
response_formatNoOutput format: "markdown" for a readable summary table, "json" for the complete structured payload.markdown

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Discloses that heights are relative to datum, analysis types, and optional year filter. Annotations already indicate readOnly and idempotent, so no contradictions. Missing details like data availability limitations but acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with key purpose, efficient with no redundant words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given rich annotations, detailed schema, and no output schema, the description covers return content and datum interpretation thoroughly. It explains the practical meaning of the data (flood context) and is sufficient for an agent.

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?

Input schema already describes all 6 parameters with 100% coverage. Description adds context about datum for flood comparisons and output content (causal event names), but not essential given schema richness.

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?

Description clearly states it retrieves highest recorded water levels with two analysis types. It distinguishes from sibling tools like noaa_get_water_levels or noaa_get_sea_level_trends by focusing on peak/record events.

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

Usage Guidelines4/5

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

Provides a concrete use case ('what's the worst flooding ever recorded at X?') and explains when to use top ten vs peak. Could be more explicit about when not to use (e.g., for trends), but overall clear.

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

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