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Gillby

by io.github.OneWave-AI
OverviewDiscussionsAdmin

California lake catalog

list_california_lakes
Read-onlyIdempotent

List California lake IDs, model point coordinates and gauge references. Lake centers are approximate, not surveyed launches. Use get_california_lake for weather and gauge data.

Units: ft, kt, s, F, mi; directions FROM. Returns data and source/freshness metadata.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_california_lakes"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations cover safety (readOnly, idempotent, destructive=false), so the description adds genuinely new context: lake centers are 'approximate, not surveyed launches,' plus units, the FROM direction convention, and that source/freshness metadata is returned. These are useful caveats not present in structured fields.

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?

Two well front-loaded sentences plus a compact units line; every element carries information. Slightly terse but no waste.

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?

With no output schema, the description adequately signals return shape (IDs, coordinates, gauge refs, source/freshness metadata) and units. The remaining gap is the unexplained query parameter, which limits completeness modestly.

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

Parameters2/5

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

There is one nested 'query.q' parameter at 0% schema coverage, and the description never mentions it or explains filtering/search syntax. Unlike a zero-param tool, the single opaque nested param leaves the agent guessing how to constrain the listing.

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?

States a specific verb and resource ('List California lake IDs, model point coordinates and gauge references') and enumerates exactly what is returned, which clearly separates it from the single-lake get_california_lake detail tool and from list_california_places/rivers.

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?

Explicitly routes the agent: 'Use get_california_lake for weather and gauge data,' making clear this tool is for discovery of lake IDs/coordinates rather than conditions. No explicit when-not beyond that single alternative, but the context is unambiguous.

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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