Read this workspace's current billing period: requests used, plan, monthly limit, and any metered overage. Call this to see how close you are to the quota before a big import.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description aligns by saying 'Read'. It adds valuable context by specifying the returned information (requests used, plan, monthly limit, metered overage) and frames the tool as a quota check, which goes beyond the annotation baseline.
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 first sentence is front-loaded with the essential action and returns, the second provides a practical use case. Every word earns its place.
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 parameterless read tool with no output schema, the description fully covers what it returns, when to use it, and its read-only nature. There are no gaps in context.
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, so the baseline is 4. The description correctly omits parameter details and instead clarifies the semantic scope ('this workspace's current billing period'), which is sufficient.
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 opens with a specific verb ('Read') and a clear resource ('this workspace's current billing period'), then enumerates the exact data components (requests used, plan, monthly limit, overage). This distinguishes it from sibling tools, none of which focus on usage/quota inspection.
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?
It gives a concrete use case: 'Call this to see how close you are to the quota before a big import.' This is clear context, though it doesn't explicitly mention when not to use it or name alternatives.
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.
Every tool targets a distinct resource-action pair (e.g., create_automation, create_pipeline, create_template), and potential overlaps like batch vs create or log_activity vs create are clearly differentiated in descriptions. No two tools appear to do the same thing.
All 41 tools follow the relm_<verb>_<noun> pattern in snake_case, with conventional verbs like create, get, list, delete, manage, and restore. Minor plural/singular differences (list_automations vs get_automation) follow standard resource-naming practices and do not break consistency.
At 41 tools, the set is far beyond the 25+ threshold and feels heavy for an agent to navigate. While the CRM domain is broad, many tools could be consolidated (e.g., generic get/list by resource type) without losing clarity.
The tool set covers the full record lifecycle (CRUD, restore, batch, search) plus schema management, pipelines, stages, automations, sequences, templates, webhooks, channels, and usage. However, automations, sequences, and templates lack update operations—requiring delete-and-recreate workarounds—which is a minor but notable gap.
