get_health
Check the health status of the PNLCS installation to identify potential issues or confirm all systems are operational.
Instructions
Health of the PNLCS install itself.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Check the health status of the PNLCS installation to identify potential issues or confirm all systems are operational.
Health of the PNLCS install itself.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.4Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure, but it only states the domain (PNLCS health). It does not mention that this is a read-only check, what fields or statuses are returned, or any operational behavior.
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?
A single sentence with no filler or repetition. The essential scope is front-loaded and every word contributes.
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 zero-parameter health endpoint, the description is minimally viable, but without an output schema it leaves the return format unspecified. The agent can invoke it correctly, yet has no knowledge of what the health response will contain.
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?
There are zero parameters and the schema already documents an empty input object, so the description does not need to explain parameters. Baseline 4 applies because there is nothing to clarify.
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 clearly identifies the resource (the PNLCS install) and the subject (its health), and 'itself' distinguishes it from the data-focused sibling tools. It lacks an explicit verb such as 'get' or 'retrieve', so it misses the top criterion.
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?
No guidance is given about when to choose this tool over siblings like get_stats, nor any conditions or exclusions. The phrase 'install itself' weakly implies a health-check use case, but that is not enough to guide tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Panelica/pnlcs-mcp'
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