Skip to main content
Glama

check_supplemental_status

Read-onlyIdempotent

Check asynchronous market data gathering status and retrieve results once complete. Poll every 5-10 seconds until COMPLETE or FAILED.

Instructions

Check if market data gathering is complete and retrieve the results. Call this after get_supplemental_context — poll every 5-10 seconds until status is COMPLETE or FAILED. (Async supplemental query status poll.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesThe Job ID returned by get_supplemental_context

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.3.3

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover the safety profile (readOnly, idempotent, non-destructive), and the description adds what annotations cannot: the async polling loop, the cadence, and the terminal states COMPLETE/FAILED. It does not say what the response contains beyond "results", but the behavioral workflow is well disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose, then sequencing, then cadence. Efficient overall; the trailing parenthetical "(Async supplemental query status poll.)" is slightly redundant with the first sentence but harmless.

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?

No output schema exists, so the description must carry return-value burden; it says results are retrieved on COMPLETE and that FAILED is possible, which covers the essential lifecycle. It stops short of describing the result shape or what to do on FAILED, leaving a modest gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema itself already states job_id is "The Job ID returned by get_supplemental_context". The description repeats that linkage ("Call this after get_supplemental_context") without adding format, validation, or failure-mode detail, so baseline 3 is correct.

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?

States a specific verb (check/retrieve) and resource (supplemental market data gathering results), and explicitly distinguishes itself from get_supplemental_context by naming that sibling as the prerequisite. An agent can tell this is the polling/completion leg of an async workflow.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit sequencing ("Call this after get_supplemental_context"), explicit cadence ("poll every 5-10 seconds"), and explicit termination condition ("until status is COMPLETE or FAILED"). This is about as prescriptive as usage guidance gets.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.