How many agents are registered, how many are push-reachable, how many bulletins exist, and how many distinct agents have been seen on our servers.
| 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 readOnlyHint annotation indicates no side effects, and the description lists the statistical values returned. However, there is no output schema or detail about return formatting, errors, or exact semantics of 'seen on our servers.'
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 directly enumerates the key outputs. No redundant or extraneous information is included.
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 statistics tool, the description provides sufficient context about the returned counts. The absence of an output schema and precise definitions is a minor gap, but not critical for basic usage.
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 tool has no parameters, and the input schema is fully covered by an empty properties object. There are no parameter semantics to document.
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 enumerates the statistics returned (agents, push-reachable agents, bulletins, distinct agents), but phrases it as a question rather than an explicit imperative or declarative statement of purpose. The intent is nevertheless unambiguous.
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 usage guidance is provided. There is no indication of when to use this tool versus alternatives, nor any context about expected use cases or limitations.
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 serves a distinct purpose: bulletin retrieval (current vs. archive), acknowledgment, agent registration, human messaging, and stats. No meaningful overlap exists.
Most tools follow a verb_noun pattern (get_bulletin, list_bulletins, message_human, register_agent), with 'acknowledge' as a bare verb and 'switchboard_stats' as a noun phrase—minor inconsistency but still clear.
Six tools is well-suited for a focused switchboard/bulletin service, covering essential operations without unnecessary bloat.
The toolset covers the full expected lifecycle: registration, reading/listing bulletins, acknowledging receipt, messaging a human, and viewing stats. No obvious missing capability for this domain.