stationsList all NOAA Tides & Currents monitoring stations; filter by type (waterlevels, currents, physical, or meteorological). Returns station IDs, names, and geographic coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | waterlevels (default) | currents | physical | meteorological | |
| format | No | json (default) |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering the safety profile. The description adds value by specifying return contents (station IDs, names, coordinates) and the filter behavior (by type). It does not mention pagination or potential performance characteristics, but given the strong annotation coverage, the added details are sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that communicates purpose, filtering, and return values with no wasted words. It is concise, efficient, and well structured for quick parsing by an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with two optional parameters, complete schema descriptions, an output schema present, and strong annotations, the description fully covers the essential context: what the tool does, what it returns, and how to filter. No significant gaps remain; the output schema handles return structure details, so the description need not repeat them.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%—both 'type' and 'format' have descriptions in the schema. The description repeats the filter options and says 'List all', which adds little beyond the schema. Since the schema fully documents the parameters, a baseline of 3 is appropriate; the description does not introduce new semantic details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('NOAA Tides & Currents monitoring stations'), and clearly distinguishes from siblings like currents, water_level, and station_metadata by focusing on station discovery. It also names the filter types (waterlevels, currents, physical, meteorological) and return content (IDs, names, coordinates), making the tool's role unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as a discovery tool ('List all stations; filter by type') and mentions 'Returns station IDs, names, and geographic coordinates', which suggests a precursor to data-retrieval tools. However, it does not explicitly mention alternatives or when to prefer station_metadata or current/water-level tools. No exclusions or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The 7 NOAA-specific tools (stations, station_metadata, water_level, currents, met_obs, predictions, datums) are clearly distinct, but they are buried among ~31 Pipeworx platform tools with heavy internal overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route factual queries, while polymarket_edges, polymarket_edge_tracker, polymarket_arbitrage, polymarket_fill_risk, and polymarket_kalshi_spread all analyze prediction-market opportunities. An agent cannot easily tell whether the generic question-answering or prediction-market tools are the right choice without reading long descriptions.
Most tools use snake_case, but the naming conventions are inconsistent: some use descriptive nouns (stations, datums, predictions), some use noun_verb pairs (water_level, met_obs), and the Pipeworx batch mixes vendor-prefixed names (pipeworx_feedback, pipeworx_trending), bare verbs (remember, forget, recall, subscribe, unsubscribe), and multi-word verbs (generate_llms_txt, scan_competitor_ai_presence, ask_pipeworx_grounded). No predictable pattern unifies the set.
38 tools is far too many for a server named 'Noaa Tides' — only 7 tools relate to NOAA tide/current data, and the other 31 are an unrelated general-purpose data platform (SEC filings, prediction markets, npm packages, AI visibility scanning, memory storage). The overwhelming majority of the surface has nothing to do with the server's stated purpose, making the count and composition a severe mismatch.
For the nominal NOAA tides domain, the surface is reasonably complete: station listing, metadata, observed water levels, currents, meteorological observations, tide predictions, and datums cover the core workflows. Minor gaps exist (e.g., no harmonic constituents or extreme water-level statistics tool), but the essential operations are present. The unrelated tools do not fill gaps in the NOAA domain — they are clutter rather than coverage.