summarize_resource

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

Beyond the annotations (readOnlyHint, openWorldHint), the description adds specific behavioral traits: downloads file up to 100 MB, runs DuckDB COUNT/DISTINCT/AGG queries per column, returns one compact dict per column, and omits top_values for columns with many distinct values. This transparency helps the agent understand constraints and output characteristics.

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 four sentences. The first sentence front-loads the core purpose. Each subsequent sentence adds necessary detail (process, return format, usage context, omission behavior) without redundancy. No wasted words.

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 (3 parameters, output schema present), the description adequately covers the primary behavior, constraints (file size limit, omission policy), and context (use for decision-making). It does not detail the output schema (unnecessary since it exists separately) or mention format-specific handling, but overall it provides sufficient completeness for an AI agent.

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?

The input schema already provides descriptions for all three parameters (100% coverage). The description adds some context about the behavior of max_categorical_top_n (implicitly via top_values omission) but does not significantly enhance understanding of url or format beyond the schema. Per calibration, baseline 3 is appropriate when schema coverage is high.

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's purpose: 'Auto-generated profile: row count, types, nulls, distinct, min/max/mean, top values.' It also explains the process (downloads file, runs DuckDB queries) and the output format (compact dict per column). This distinguishes it from sibling tools like aggregate_resource or filter_resource, which perform different operations.

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 that 'The model uses this to decide which filters and aggregations to apply next,' implying it's a preliminary analysis step. However, it does not explicitly state when to use this tool versus alternatives like aggregate_resource or query_resource, nor does it provide when-not-to-use guidance. The context is helpful but lacks explicit directives.

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