Return LIQAA's load-tested technical capacity and architecture: max participants, real measured load-test results, transport, encryption and latency.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint as true/false. The description adds value by specifying the exact types of information returned (e.g., max participants, latency), but does not disclose additional behavioral traits like rate limits or data freshness.
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 sentence that efficiently packs all relevant information without redundancy. It is front-loaded and every word adds value.
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?
Given the tool has no parameters and no output schema, the description adequately covers what it returns. However, slight additional context like 'returns a single object' or 'no side effects' could increase completeness.
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 zero parameters, and schema coverage is 100%, so no parameter documentation is needed. The description does not need to explain parameters, meeting the baseline expectation.
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 the verb 'Return' and clearly specifies the resource: 'LIQAA's load-tested technical capacity and architecture', listing concrete aspects like max participants, load-test results, transport, encryption, and latency. This distinguishes it from siblings like platform_stats (usage stats) and list_plans (plan listing).
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 implies usage for querying capacity information but does not explicitly state when to use it versus alternatives or note any prerequisites or exclusions. No sibling differentiation is mentioned beyond the implicit purpose.
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 clear, non-overlapping purpose: creating a room, listing plans, and providing platform capacity and usage statistics. There is no ambiguity in their roles.
Two tools follow a verb_noun pattern (create_instant_room, list_plans), but the other two use a noun_verb style (platform_capacity, platform_stats). This mix of conventions reduces consistency.
Four tools feel appropriate for a focused meetings server that emphasizes instant rooms and informational queries. The count is neither too sparse nor overwhelming for the scope.
The set covers room creation and basic informational needs, but lacks operations like joining, listing, or managing rooms, leaving gaps for a full meeting lifecycle.
