getMarineConditions
Fetches live observation data for a specific NOAA marine buoy station.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| buoy_id | Yes | 5-character NOAA NDBC buoy identifier |
StatePulse API
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
B3.3/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states 'Fetches live observation data,' implying a read operation, but omits details like data freshness, rate limits, authentication, or error handling. This is insufficient for a tool with no annotations.
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 a single, well-structured sentence that front-loads the action. It is concise with no unnecessary words, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the basic purpose but lacks details about the data returned (e.g., specific measurements). It is adequate but not complete.
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?
Schema coverage is 100% with a clear description of buoy_id. The tool's description adds no extra meaning beyond the schema, meeting the baseline for high coverage but not enhancing understanding.
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 the tool fetches live observation data for a specific NOAA marine buoy station, using specific verbs and resources. It effectively distinguishes from sibling tools like getStreamTemperature or getWaterStreamflow by specifying 'marine buoy station'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description lacks context for optimal usage.
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
B3/5.0
Disambiguation2/5
Many tools have overlapping functionality, e.g., auditNetworkHost combines DNS, SSL, and header checks that have dedicated tools (auditDnsSecurity, checkSslExpiry, auditSecurityHeaders). Multiple weather and blockchain tools also overlap in scope, making it difficult for an agent to choose the right tool.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., getAirQuality, checkDnsPropagation), but a few deviate (agentPreflight, capabilitiesDiff) and some use compound names (depositCoordinationBounty). Overall, the pattern is clear but not perfectly uniform.
Tool Count1/5
With 56 tools, the server is far too large for a coherent MCP surface. The number suggests a collection of many unrelated APIs rather than a focused tool set. A typical well-scoped server has 3-15 tools.
Completeness2/5
While the tool set covers many domains, each domain has shallow coverage. For example, blockchain tools miss basic transaction sending and contract deployment; weather tools lack forecasts. The 'requestMissingData' endpoint acknowledges gaps, but the current surface is severely incomplete for a general-purpose API.