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ignytehq

plunk-mcp

Official
by ignytehq

Import status

plunk_get_import_status
Read-onlyIdempotent

Check a Plunk contact import job's progress, state, and errors to confirm it finished and see what failed.

Instructions

Purpose: Check how an import job started by plunk_import_contacts is progressing.

Not for: Bulk subscribe, unsubscribe or delete jobs — those are polled with plunk_get_bulk_job_status.

Returns: The job's state, progress and any errors.

Use when: After starting an import, to confirm it finished and see what failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, so safety is covered. The description adds value by disclosing what the call returns (state, progress, errors) — meaningful for a polling tool with no output schema — and by delineating the job-type boundary. It stops short of noting anything about polling cadence or terminal states.

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?

Four short labeled lines, each earning its place: purpose, exclusion, return shape, trigger. Front-loaded purpose with zero filler.

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, and the description compensates by summarizing the return payload (state, progress, errors). Combined with the explicit routing to the sibling status tool, this is nearly complete; only the parameter's origin/format remains implicit.

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 description coverage is 0% and there is one required parameter, so the description carries the burden. It implies jobId is the identifier returned by plunk_import_contacts, which is useful, but never names or describes the parameter explicitly, leaving a gap.

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+resource ('check how an import job ... is progressing') and explicitly ties the tool to its producer, plunk_import_contacts. It distinguishes itself from the nearest sibling (plunk_get_bulk_job_status) in the same breath.

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 'Not for' clause naming the alternative polling tool with its job types, plus a clear 'Use when' trigger. An agent can route between import-status and bulk-status polling without inspecting either schema.

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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