query_and_plotly_chart

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

With no annotations, the description must disclose behavioral traits. It explains the two-step process (query then chart) but does not mention side effects, errors, rate limits, or output format details. The description is simple but lacks depth.

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 concise with two sentences, the first clearly stating the main function. The second sentence provides a related tip but is somewhat tangential. It is well-structured and front-loaded.

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 no output schema and no annotations, the description is fairly complete for a combined query-chart tool. It explains the process and mentions a prerequisite. However, it lacks details on output format or error handling, leaving some gaps.

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% with descriptions, so baseline is 3. The description adds context about the overall workflow but does not elaborate on individual parameters beyond the schema. The mention of set_session_db is peripheral.

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 uses SQL query to extract data and then generates a chart with plotly_expr. It distinguishes from siblings like read_query (which only returns data) by explicitly mentioning chart generation. However, it could be more precise by contrasting with other query tools.

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 mentions using set_session_db to set a default database, which is helpful but does not provide guidance on when to use this tool over its siblings (e.g., read_query for data only, analyze_query for analysis). No explicit exclusions or alternatives are given.

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