Analyze the drift log built by get_time: reports current offset, drift rate (ms/day), and whether the clock is stable, drifting, or accelerating.
| Name | Required | Description | Default |
|---|---|---|---|
| server | No | Only analyze samples from this NTP server |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It indicates an analysis operation ('analyze') and lists output fields, but does not explicitly state whether the tool is read-only, whether it requires prior calls to get_time, or what happens if the log is empty or missing. This lack of behavioral disclosure for a tool with no annotations is a significant gap.
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, concise sentence that front-loads the purpose and directly states the tool's outputs. There is no redundant or unnecessary information, and it is well-structured for quick comprehension.
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?
The description covers the tool's purpose and output fields (offset, drift rate, status), which is adequate for a simple tool with one optional parameter. It does not mention edge cases like empty logs or error conditions, but given the simplicity and the reference to get_time as the data source, it is reasonably complete.
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?
The schema has full 100% coverage for the single optional parameter 'server' with a descriptive comment. The description does not add any extra meaning about the parameter beyond what the schema already states, so it meets the baseline of 3 for high schema coverage without adding further value.
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 states the tool's function: analyzing the drift log produced by get_time, and explicitly lists the reported outputs (offset, drift rate, stability status). This is a specific verb+resource definition that distinguishes it from the sibling get_time by referencing it as the source of the log.
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 provides clear context by mentioning that the drift log is 'built by get_time', implying this tool is used after get_time has been called. While it doesn't explicitly state exclusions or alternatives, the reference to the prerequisite makes the usage context understandable for the single sibling scenario.
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.
Each tool has a completely distinct purpose: math evaluation, text diffing, UUID generation, time querying, and drift analysis. No overlap or ambiguity between them.
All tool names follow the verb_noun pattern (calculate, diff, generate_uuid, get_drift, get_time), providing a consistent and predictable naming convention.
With 5 tools, the server is well-scoped for a utility toolkit. Each tool serves a clear and distinct function, and the count feels neither sparse nor bloated.
The tool set covers a reasonable range of utility functions (math, text, ID, time), though it could benefit from a few more general-purpose operations (e.g., string handling or encoding) to be fully comprehensive for a utility server.