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Get Knowledge Import Status

neuron_get_kb_import_status
Read-onlyIdempotent

Progress of a WhatsApp chat import: state (queued/running/done/stopped/failed), messages read, listings created/updated, listings skipped because their date had passed.

Input Schema

NameRequiredDescriptionDefault
kbIdYesKnowledge base the import writes to
importIdYesid returned by neuron_import_whatsapp_chat

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, so the bar is lower. The description goes beyond them by disclosing the exact state values an agent will encounter and the shape of the returned counters (messages read, listings created/updated/skipped), which is genuinely useful operational context not present in annotations.

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?

A single front-loaded sentence that leads with the subject (progress of an import) and then lists the meaningful outputs. No filler, no redundancy, and every clause carries information.

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?

Because no output schema exists, the description usefully enumerates the returned fields, and annotations already carry the safety profile. It is slightly incomplete in not indicating timing (poll cadence) or failure/not-found behavior, but for a two-parameter status read with fully documented params it is close to sufficient.

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 100% and both params are documented there (kbId as target knowledge base, importId as the id from neuron_import_whatsapp_chat). The description mentions no parameters, so it adds nothing over the schema; baseline 3 is appropriate at full coverage.

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 (get) and resource (WhatsApp chat import status) and enumerates the exact return content: state, messages read, listings created/updated/skipped. An agent can tell it reports progress rather than performing the import, but the description never explicitly names the sibling it complements (neuron_import_whatsapp_chat), so differentiation is left implicit.

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?

Usage is only implied: the enumerated state machine (queued/running/done/stopped/failed) signals polling after an import is started, but there is no explicit 'call this after neuron_import_whatsapp_chat' or when-not-to-use guidance. The link to the import tool appears only in the schema description of importId, not in the tool description.

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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