deep_search

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

Annotations indicate readOnlyHint=true, so the tool is safe. The description adds behavioral detail: it runs adaptive_search, traverses up to max_hops from top-3 results, and returns specific graph data. No contradictions; description enriches understanding.

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?

Two sentences front-load the core purpose and process, then list return fields. Every word adds value; no redundancy or filler. Excellent efficiency.

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?

Given 2 parameters, annotations, and an output schema (though not shown), the description covers the algorithm, input roles, and output structure. No gaps for the tool's complexity.

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 100%, but the description adds meaning by explaining how parameters are used: query is the search input, max_hops controls traversal depth, and it relates to the process (top-3 results). This goes beyond the schema's bare 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?

The description clearly states a specific verb and resource ('Multi-hop knowledge search') and explains the process (adaptive_search then graph traversal) and return fields. It distinguishes from sibling tools like search_knowledge by emphasizing connected results beyond flat search.

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 implies when to use: for deep connected results that flat search would miss. However, it does not explicitly state alternatives or when not to use, but the sibling tools list provides context. Clear usage context but lacks explicit exclusions.

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