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

Goes well beyond annotations with rich behavioral context: asynchronous execution with a polling path, AI-credit cost, plan gating, a hard read cap of the newest 1,000 messages within sinceDays, one import per organization at a time, and the guarantee that the source file is never stored. These are exactly the traits an agent needs to set expectations correctly.

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

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

The core action is front-loaded and every clause carries distinct operational information (background, poll, plan, cost, limits, no-storage, concurrency). The dense semi-colon-packed style is efficient though slightly telegraphic, keeping it just short of a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex asynchronous import with no output schema, the description covers everything an agent needs: what it does, that it is async and how to check status, cost/plan requirements, read limits, storage behavior, and concurrency. Nothing material is missing.

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

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

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: the interaction between sinceDays and the 1,000-message cap, and that entries expire on their own date (relating to keepDays). This is useful semantic context beyond the field descriptions.

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

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

States a specific verb+resource: read a WhatsApp 'Export chat' .txt and save the listings (trips, items for sale, services, jobs) as KB entries that expire on their own date. It clearly establishes the source format (no media) and destination, distinguishing it from generic ingest tools like neuron_ingest_knowledge.

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

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

Gives clear operational context: it runs in the background so you poll neuron_get_kb_import_status, and it requires Pro plan and up, charged to AI credits. It lacks an explicit when-to-use-vs-siblings comparison against neuron_ingest_knowledge or neuron_create_kb_entry, 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.