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

With no annotations at all, the description carries the full burden, and it does disclose the return contract shape (ids for `fetch`), which is the most important behavioral fact here. It says nothing about whether results are ranked, how many come back, whether matching is keyword or semantic, or what happens when nothing matches.

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?

One tightly packed sentence plus one sentence on the return contract; nothing is wasted and the core purpose plus coverage list is front-loaded. The parenthetical topic list earns its space by telling the agent what the corpus contains.

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?

There is no output schema and no annotations, so the description is the only source of truth, and it covers the essentials (purpose, corpus scope, id-based return). It falls short on result cardinality, ranking/matching behavior, and empty-result handling — details an agent would want before relying on it in a loop.

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?

The single `query` parameter has 0% schema description coverage, so the description must compensate. It partially does by listing the documentation topics the query can target, which tells the agent a natural-language query is acceptable, but it gives no format, phrasing, or scope guidance (e.g., one topic per call vs. compound queries).

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?

The description names a specific verb and resource (searches GroundQuote's documentation) and enumerates covered topics — what it is, pricing, install, ownership, pricing format, rules for assistants — so the generic tool name 'search' is disambiguated. It also distinguishes itself from the sibling `fetch` by stating it returns ids to pass along.

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?

The workflow handoff ('Returns ids to pass to fetch') implies the intended two-step pattern, which is genuinely useful guidance. However, it never says when to prefer this over topical siblings like `get_pricing_terms` or `get_install_instructions`, which overlap heavily with the listed coverage areas — that ambiguity is left entirely to the agent.

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