NTP time plus clock-drift history: stable vs. accelerating offsets.
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 |
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.
Query an NTP server for current UTC time and this clock's offset, and append the sample to the drift log. Call it periodically to build drift history.
| Name | Required | Description | Default |
|---|---|---|---|
| server | No | NTP server to query | time.cloudflare.com |
| timezone | No | IANA timezone for a 'local' field, e.g. America/New_York. Optional -- the HTTP transport also takes ?tz= in the URL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the side effect (appending to the drift log) and the return of time and offset. This goes beyond basic intent but does not cover failure modes or prerequisites like network access, so it is good but not exhaustive.
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?
Two sentences with no filler. The primary purpose and the call frequency guidance are both front-loaded, making it easy for an agent to grasp the tool quickly.
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 tool with no output schema, the description covers the main behavior and side effect. It implies return values (UTC time and offset) but does not explain timezone handling beyond the schema. It also does not mention failure handling, which is minor for this context. Overall adequate.
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 coverage is 100%, so both parameters are already documented. The description adds no extra meaning about the parameters, so it stays at the baseline of 3.
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 queries an NTP server for UTC time and clock offset, and appends to a drift log. This is a specific verb-resource pair that differentiates it from the sibling get_drift, which likely reads 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 advises calling it periodically to build drift history, which is clear usage context. However, it does not explicitly mention when not to use it or point to get_drift as the alternative for reading the drift log, so it misses the 'when-not' and alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
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get_time and get_drift have clearly distinct purposes: one collects and logs a time sample, the other analyzes the accumulated drift history. There is no overlap or ambiguity between them.
Both tool names follow the same get_<noun> pattern, and the verbs accurately describe their operations. The naming convention is consistent and predictable.
Two tools is slightly under the typical 3-15 range, but the narrow scope of clock-drift monitoring makes this a reasonable, focused set. Each tool has a distinct role and earns its place.
The pair covers the core workflow: collect time samples with get_time and analyze the resulting log with get_drift. Minor gaps such as resetting or explicitly clearing the drift log are not required for the stated purpose.
