rag_query

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

With no annotations provided, the description carries the behavioral disclosure burden. It does this well by revealing the data source ('local SQLite index'), the intended domain (RAG chunks, metadata discovery), limitations ('not evidence of current live data, permissions, or report output'), and a failure pathway ('Inspect rag_diagnostic if search returns no useful result'). This is meaningful context beyond the schema.

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 three sentences with no filler. It front-loads the core purpose, then adds usage boundaries and a fallback note. Every sentence earns its place, though the structure is compact rather than explicitly sectioned.

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?

The description covers purpose, limitations, and fallback behavior, and an output schema exists, so return-value documentation is not the description's job. However, with four parameters and 0% schema coverage, it leaves snapshot and session_id semantics unexplained, making the description incomplete for nuanced invocations.

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 parameter meaning, but it only implies the purpose of 'query' through the phrase 'Search business terms...' It does not explain 'limit', 'snapshot', or 'session_id', which could be important for invoking the tool correctly in different contexts.

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 opens with a specific verb and resource: 'Search business terms and full-text RAG chunks in the local SQLite index.' It clearly identifies this as a search/discovery tool and implicitly separates it from RAG source-management siblings like rag_source_add and rag_index_build, though it does not explicitly name a sibling to distinguish from.

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 concrete guidance on when to use it: 'Use RAG to discover metadata names, fields, forms, and base/extension layers.' It also gives exclusions by stating it is 'not evidence of current live data, permissions, or report output,' and provides a fallback action via rag_diagnostic. It does not name a specific alternative tool, but the when/when-not guidance is clear.

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