Search Avalanche documentation

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral detail: it returns 'ranked snippets with title, heading, url and path' and explains that it is a search (not a full-text retrieval) with a follow-up call to avax_get_doc. It also mentions the default limit and source filter behavior, which goes beyond annotations. No contradiction found.

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 description is detailed but efficiently structured: an opening purpose sentence, a usage guideline, and a bulleted argument list with examples. It avoids redundancy and keeps each sentence informative. It is slightly long, but the density of information justifies the length. The layout makes key points scannable.

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 search tool with no output schema, the description covers all essential aspects: the scope of sources, when to use it, what each parameter does, and the expected return (ranked snippets with metadata). It also closes the loop by directing the agent to avax_get_doc for full content. There is no critical missing information that an agent would need to call the tool correctly.

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 of parameter explanation. It thoroughly details each argument: query with natural-language examples, source with an enumerated list and descriptions (e.g., 'integrations (234 ecosystem integrations: oracles, bridges, indexers, wallets, RPC providers…)'), path_prefix with concrete examples, and limit with its default and range. This adds significant meaning beyond the raw schema types.

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 clearly states it is a 'Full-text search over the official Avalanche knowledge base' and enumerates the specific sources (docs, Academy, integrations, etc.). It also frames its role as the first-stop for 'how do I…' and 'which precompile/config/command…' questions, distinguishing it from other tools like avax_get_doc or avax_list_docs. The verb ('search') and resource ('Avalanche knowledge base') are explicit, and the scope is narrowed with a clear boundary.

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 description explicitly instructs 'Use this FIRST for any…' and lists example question types, providing clear when-to-use guidance. It also points to avax_get_doc as the follow-up for reading full pages, which gives a workflow. However, it does not explicitly state when NOT to use this tool (e.g., when a more specialized search like avax_search_integrations would be better), so it falls just short of a perfect score.

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