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Glama

Usgs Water

by io.github.pipeworx-io

Current Conditions

current_conditions
Read-onlyIdempotent

Latest instantaneous (real-time) readings for one or more USGS gauge sites. Returns the most recent value per site × parameter — e.g. current streamflow and gage height for a river. Common parameter codes: 00060 = discharge/streamflow (ft³/s), 00065 = gage height (ft), 00010 = water temperature (°C), 00045 = precipitation (in), 00095 = specific conductance, 00300 = dissolved oxygen, 63680 = turbidity. Keyless.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sitesYesComma-separated USGS site numbers, e.g. "01646500" (Potomac at Washington DC) or "01646500,01647000".
parameter_codesNoComma-separated USGS parameter codes (default "00060,00065" = streamflow + gage height).

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "sites": "01646500"
+  },
+  {
+    "parameter_codes": "00060,00065,00010",
+    "sites": "01646500,01647000"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by specifying 'Keyless' (no authentication needed) and confirming the return of 'most recent value per site × parameter', which aligns with annotations without contradiction.

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?

The description is four sentences, each serving a purpose: stating purpose, return format, common codes, and access method. No unnecessary information.

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?

The tool has no output schema, but the description clarifies the return structure (most recent value per site × parameter). For a simple read tool, this is sufficient, though a brief note on response format would be slightly more complete.

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

Parameters4/5

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

Schema coverage is 100%, but the description enhances understanding by listing common parameter codes with units and examples, providing context beyond the schema's basic descriptions.

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?

The description clearly states it returns 'latest instantaneous (real-time) readings' for USGS gauge sites, specifying the resource and action. It distinguishes from a sibling tool like 'daily_values' by focusing on real-time data.

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

Usage Guidelines3/5

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

The description implies usage for real-time data but does not explicitly state when to use this tool versus alternatives like 'daily_values' or 'find_sites'. There is no 'when not to use' guidance, only implied context.

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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TDQS

A3.5/5.0
Disambiguation2/5

Several clusters of tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all route/discover questions across the same 5,743 tools, differing mainly in mode or betaness. The polymarket_* family (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) similarly overlaps in prediction-market edge detection. An agent would frequently struggle to pick the right tool from these near-duplicate groups despite verbose descriptions.

Naming Consistency3/5

Snake_case is used throughout, but patterns are mixed: some tools are verb-first (ask_pipeworx, find_sites, recall, forget, subscribe), some are noun phrases (current_conditions, entity_profile, bet_research), and some use a domain prefix (pipeworx_*, polymarket_*). The version-suffixed ask_pipeworx_beta is also a minor deviation from the otherwise clear descriptive style.

Tool Count2/5

34 tools is excessive for a server named 'Usgs Water' since only 3 tools (current_conditions, daily_values, find_sites) actually relate to USGS water data. Even as a general Pipeworx platform server, the count is heavy, with many tools dedicated to niche prediction-market trading and meta-routing that inflate the surface.

Completeness1/5

Against the stated USGS Water purpose, the surface is severely incomplete: it lacks water-quality samples, groundwater data, site metadata details, historical statistics, rating curves, parameter code lookup, and flood/alert data. The remaining 31 tools cover an entirely different domain (SEC filings, drugs, prediction markets, npm scans, memory), so agents using this server for water data will hit dead ends almost immediately.

Resources