request_status
Read-onlyIdempotent
Check the status of a pending ask() job.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Job id returned by a prior ask() call that went async. |
Ezoic Setup Assistant
by com.ezoic
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety traits. Description adds no further behavioral context beyond 'check status', which is consistent but not additive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no unnecessary words. Information is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple status-check tool with one parameter and no output schema, the description is adequate. Could optionally mention polling behavior or possible statuses, but not required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with description. Description adds context that job_id comes from a prior async ask() call, which clarifies the parameter's origin beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'check' and resource 'status of a pending ask() job', distinguishing it from sibling tools like 'ask' (creates jobs) and 'read_response' (retrieves final results).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage after an async ask() call but does not explicitly state when to use this tool versus alternatives like 'read_response' for final results. No usage exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
A4.2/5.0
Disambiguation5/5
Each tool has a clear, distinct purpose: ask initiates a query job, help provides orientation, read_response streams job output, and request_status checks job progress. No overlap or ambiguity.
Naming Consistency5/5
All tool names follow a consistent pattern: single verbs (ask, help) and verb_noun combinations (read_response, request_status), all lowercase with underscores for multi-word names.
Tool Count5/5
With 4 tools covering the core workflow of asking questions and retrieving responses asynchronously, the count is well-scoped and appropriate for the server's purpose.
Completeness5/5
The tool surface fully covers the expected lifecycle: initiate a job (ask), check its status (request_status), and retrieve the result (read_response), plus help. No obvious gaps given the domain.