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kadam-official

@kadam-net/mcp-server

Official

kadam_adv_get_bulk_job

Read-only

Retrieve status and row-level results for a bulk creative job, covering staged or refused uploads and per-row outcomes, so you can verify success before reporting completion.

Instructions

State of a bulk creative batch, for both steps: staged images and what staging refused for an upload job, the per-row outcome for a creation job. Status done only means the worker finished — individual rows can still have failed, so read the counters before reporting success.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesJob ID returned by the upload or create call

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.1

TDQS

A4.1/5.0
Behavior5/5

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

Adds genuinely non-obvious behavioral context beyond the readOnlyHint annotation: 'done' means the worker finished, not that rows succeeded, and callers must inspect counters. This is exactly the kind of outcome-semantics disclosure the annotation cannot provide, and it is critical given there is no output schema.

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?

Two dense sentences with no filler; the critical caveat about 'done' is front-loaded in the second sentence. The opening clause is slightly compressed to the point of being terse, but nothing wastes space.

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?

With no output schema, the description carries the burden of explaining what comes back (counters, staging refusals, per-row outcomes) and does so well. Remaining gaps are minor: no indication of polling behavior or how long results persist.

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 sole jobId parameter is already documented as 'Job ID returned by the upload or create call.' The description reinforces that origin story implicitly but adds no format, validation, or lifecycle detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('State of a bulk creative batch') and goes further by distinguishing the two job flavors it covers — staged/refused images for an upload job vs. per-row outcomes for a creation job. It is clearly separable from siblings, though it never names the producer tools (upload_bulk_images / create_bulk_creatives) that generate the jobId.

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

Usage Guidelines4/5

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

The description makes the use context clear: this is the status-check step for a bulk upload or creation batch, and it warns to read counters before declaring success. It lacks explicit when-not-to-use guidance or polling/cadence advice, so it stops short of a 5.

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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