Search AI Framework Docs

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

The annotations already mark readOnlyHint, idempotentHint, and openWorldHint=false, and the description reinforces and extends this: it is a local index search, never live-crawls, returns compact chunks, and uses hitCount 0 to signal no match. It also discloses the per-call cost, adding practical behavioral context beyond annotations.

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 compact and front-loaded with the tool's essential behavior, then covers usage boundaries, common failure recovery, and cost. Every sentence earns its place; there is no filler or repetition of schema content.

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 a rich output schema and detailed parameter documentation, the description covers what it searches, how it behaves, when to use it, which siblings to prefer instead, and cost. No practical gap remains for an agent deciding whether and how to invoke it.

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% and the schema already documents both parameters well. The description adds extra value by framing queries as 'concepts, symbols, or questions' and by advising to shorten the query when hitCount is 0, which helps the agent craft an effective query parameter.

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 ('search'), a precise resource ('local Markdown index for langchain, llamaindex, ollama, or xrpl'), and disambiguating traits ('returns compact chunks and never live-crawls'). This clearly distinguishes it from siblings like diagnose_framework_error, resolve_symbol, and fetch_latest_syntax.

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?

Explicitly says when to use it ('concepts, symbols, or questions') and when not to, naming the exact sibling alternatives for stack traces, import/package lookup, and current syntax. It also gives a concrete recovery action when no results are found: shorten the query.

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