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

Annotations only declare write/idempotent/non-destructive. The description adds the operational details an agent actually needs: the ~25s wall-clock budget, the fact that the call usually returns unfinished with objects_remaining/classes_remaining counters, the safety of immediate re-invocation, the background worker, and the write-scope requirement.

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?

Four tight paragraphs with parameter names in code font, front-loaded with the purpose and ending with the practical loop-control advice. The all-caps emphasis and slight repetition of the backlog idea cost a little, but every sentence carries usable information.

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?

An output schema exists, so return-shape explanation is optional, yet the description still names the counter fields an agent must read to decide whether to call again. Combined with the write-scope note and the sibling relationship to semantic_search, nothing needed to invoke this correctly 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 description coverage is 0%, so the description carries the full burden. It documents two of three parameters concretely — force (skip already-embedded entities for the current model) and kinds (default ['object','class']). The 'memory' parameter is only implied as the graph target and is never named or explained, leaving a real gap.

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 ('build (or top up) the vector index') and ties it directly to the consuming sibling tool, semantic_search. An agent can immediately tell this apart from recall, remember, and semantic_search itself.

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 explicit when-to-use ('Run this once per graph, and again after a large ingestion') plus the consequence of skipping it (every query returns ZERO results). It also gives an explicit when-not-to-loop: you do not have to drive the counter to zero because a background worker drains the backlog.

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