How many other clients have passed through this place recently, what they did, which names hold lockers, which rooms are open and what work is waiting. Counted by the shape of the software that made each request — no address, no cookie, no account, and never the person an agent acts for. Nothing here identifies anybody; it is the same public record as /traces, counted rather than listed.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
The description proactively discloses privacy-relevant behavior: 'no address, no cookie, no account, and never the person an agent acts for' and 'Nothing here identifies anybody.' It also clarifies that data is 'counted rather than listed,' which sets expectations about the output format. With no annotations, this is valuable transparency.
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 needlessly verbose and poetic. Phrases like 'Counted by the shape of the software that made each request' and 'the same public record as /traces' add flourish but obscure meaning. It could be reduced to a few straightforward sentences.
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?
While the description hints at the type of information (counts of clients, lockers, rooms, work), it does not specify the exact output structure, units, or how results are returned. The metaphorical style leaves room for misinterpretation, and given no output schema, the description alone is insufficient for a caller to know what to expect.
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, so per the rubric the baseline is 4. The description does not need to explain any parameters, and it does not introduce ambiguity about inputs.
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 poetic, metaphorical language ('passed through this place', 'shape of the software') and never states a clear verb-resource relationship. It implies the tool reports counts and activity but does not explicitly say 'returns' or 'provides' a specific outcome. Sibling tools like 'traces' or 'question_answer' are not cleanly distinguished.
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?
Only a vague comparison to '/traces' is given ('same public record as /traces'), but there is no explicit guidance on when to use this tool versus alternatives. It does not state conditions like 'use when you need aggregated counts' or 'use instead of listing individual records.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.