Get Board Insights

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

Annotations assert readOnlyHint=true, destructiveHint=false, idempotentHint=true, and the description aligns by describing a read-only calculation. The description adds behavioral context beyond annotations, such as noting that human-friendly labels are returned in 'LABEL_<column_id>' fields. No contradiction.

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 well-structured, starting with a clear purpose, followed by examples, then a required precondition, and an important note. However, it repeats the same examples ('total number of items') twice, making it slightly redundant. It earns its sentences but could be more succinct.

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, aggregations, filters, grouping) and no output schema, the description provides essential usage context (precondition, column ID guidance, LABEL field). However, it does not describe the return value structure (e.g., rows of aggregated data), leaving some gap. Still, the examples and behavioral notes give adequate completeness for most use cases.

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%, so baseline is 3. The description provides examples of aggregations but does not add significant new meaning to individual parameters beyond what the schema already offers (e.g., columnId, function enum). The precondition and important note are valuable but pertain to pre-usage steps, not parameter semantics.

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 the tool calculates insights about board data via filtering, grouping, and aggregating columns. It provides concrete examples (total items, items per status) and distinguishes itself from siblings like get_board_info or get_board_items_page by focusing on summaries rather than raw data.

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 states when to use: 'Use this tool when you need to get a summary of the board's data'. Provides a precondition to first use get_board_info if columns were added or structure is unknown. This gives clear guidance on prerequisites and appropriate contexts.

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