opensolr_ai_answer

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

With no annotations available, the description carries the full burden and does so thoroughly: it explains that retrieval runs through a tuned hybrid pipeline, saved Search Tuning applies automatically, the top rag_docs hits are used as context, and it details tuning knobs including the subtle distinction between freshness_boost and fresh_bias. This goes well beyond a bare function statement.

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 front-loaded with the core purpose and uses clear separators for parameter explanations. The exhaustive tuning list is justified because the tuning schema is a generic object, but the meta sentence 'That list is the whole set, not a sample...' adds unnecessary narrative and could be trimmed without losing value.

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 the tool's complexity — 7 parameters, no annotations, and a generic tuning object — the description covers all essential operational context: what the answer is grounded in, how retrieval works, how parameters affect behavior, and which tuning options are supported. Since an output schema exists, omission of return-value details is acceptable.

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 must compensate for all 7 parameters. It explains query as a question, index as the target index, rag_docs and rag_words as retrieval context sizing, filter_query as a raw Solr fq expression, instruction as a prompt replacement, and tuning as an override mechanism with the complete list of supported knobs. This is strong compensation.

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 action: 'Ask a question and get a grounded RAG answer generated ONLY from the content already indexed in the given Opensolr index.' It identifies the tool's resource (the index) and distinguishes it from raw search or management tools by emphasizing the RAG answer and grounded retrieval pipeline.

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 gives clear context for when to use the tool: for grounded question answering over already-indexed Opensolr content, with the same retrieval pipeline as the hosted search UI. It does not explicitly contrast this with sibling tools like opensolr_search or describe when not to use it, so it falls short of a 5.

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