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Glama

Usgs Water

by io.github.pipeworx-io

Daily Values

daily_values
Read-onlyIdempotent

Daily-values time series for a single USGS site + parameter over a date range. Returns one statistic per day (default mean). Useful for trends, hydrographs, and historical comparison. Common statCd: 00003 = mean, 00001 = max, 00002 = min. Common parameter codes: 00060 = discharge (ft³/s), 00065 = gage height (ft), 00010 = water temperature (°C). Keyless.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesA single USGS site number, e.g. "01646500".
end_dateYesEnd date, YYYY-MM-DD.
stat_codeNoDaily statistic code (default "00003" = mean; 00001 = max, 00002 = min).
start_dateYesStart date, YYYY-MM-DD.
parameter_codeNoUSGS parameter code (default "00060" = discharge/streamflow).

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: +[
+  {
+    "end_date": "2024-12-31",
+    "site": "01646500",
+    "start_date": "2024-01-01"
+  },
+  {
+    "end_date": "2023-09-30",
+    "parameter_code": "00010",
+    "site": "01646500",
+    "start_date": "2023-06-01",
+    "stat_code": "00001"
+  }
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false. Description adds that the tool is 'Keyless' (no auth) and returns 'one statistic per day', which aligns with annotations. No contradictions. Could mention rate limits or pagination, but the tool is simple and annotations cover safety.

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?

Three sentences, front-loaded with the core action ('Daily-values time series...'), followed by usage guidance and common codes. Every sentence adds unique value, no redundancy.

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?

Despite no output schema, the description specifies the output ('one statistic per day') and gives examples of what parameters mean. Parameters are well-documented. For a straightforward read-only data retrieval tool, this is comprehensive enough for correct invocation.

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

Parameters5/5

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

Schema provides full coverage (100%) with descriptions for all 5 parameters. Description adds significant value by listing common stat codes (00001, 00002, 00003) and parameter codes (00060, 00010, 00065) with their meanings, which are not in the schema. This helps the agent select correct parameter values.

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 verb ('returns'), resource ('daily-values time series for a single USGS site + parameter'), and scope ('over a date range, one statistic per day'). Distinguishes from sibling tools by specifying a unique data type (daily historical time series) not offered by other tools like 'current_conditions' or 'recent_changes'.

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 states usefulness for 'trends, hydrographs, and historical comparison' and provides common parameter and stat codes. Lacks explicit when-not-to-use or alternative tool mentions, but the sibling list includes relevant alternatives like 'current_conditions' and 'recent_changes', which are implied as non-daily or non-historical.

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

All Usgs Water toolsInspect
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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