get_usage
Get the plan, credits used and remaining balance of the MESSORA account.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get the plan, credits used and remaining balance of the MESSORA account.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| 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 annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds specificity about the returned data (plan, credits, balance) but discloses no additional behavioral traits such as authentication, rate limits, or side effects. Given the strong annotations, the description provides marginal extra value.
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, clear sentence that front-loads the action and concisely conveys the purpose. There is no redundant information or filler, making it highly efficient.
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 read-only tool with no parameters and an output schema present, the description is complete. It specifies exactly what information is returned (plan, credits used, remaining balance) and does not need to explain output structure since that is covered by the output schema.
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 0 parameters, so the schema trivially covers 100% with nothing to document. Per the baseline rule for 0 params, a score of 4 is appropriate; the description does not need to add parameter semantics since there are none.
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 action ('Get') and resource ('the plan, credits used and remaining balance of the MESSORA account'). It distinguishes itself from sibling tools such as get_job, scrape_url, start_crawl, and start_search, which all have different purposes.
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 no guidance on when to use this tool versus alternatives, no exclusions, and no context on when it is appropriate. It simply states what it does without indicating when an agent should choose it over other options.
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 has a clearly distinct purpose: start_crawl and start_search initiate different async operations, get_job polls their status, scrape_url returns content synchronously, and get_usage handles account details. No two tools overlap in functionality.
All tool names follow a consistent verb_noun pattern: get_job, get_usage, scrape_url, start_crawl, start_search. The verbs (get, scrape, start) clearly indicate the action, and the nouns identify the target resource.
Five tools cover the core workflows of this scraping/search service: two async starters, one poller, one synchronous scraper, and one usage checker. This is well-scoped without unnecessary redundancy.
The core lifecycle is covered: start async jobs, poll for results, retrieve synchronous content, and check account balance. Minor gaps exist, such as no explicit cancel/revoke job tool or a way to list historical jobs, but these are not critical for basic usage.