get_section_excerpts

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

The description discloses key behaviors: batch operation, per-id error reporting, and token savings aggregation. Although no annotations exist, the description provides sufficient transparency for a read operation.

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 waste. It front-loads version and purpose, then provides key details. Every sentence contributes useful information.

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 is adequate but lacks details about return values (no output schema). It mentions _meta.tokens_saved but does not describe the full response structure. For a batch tool, more completeness would help.

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%. The description adds meaning beyond schema: for section_ids it notes order preservation and requested_id correlation; for max_bytes it specifies 'soft cap in UTF-8 bytes'. This adds valuable context.

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 is a batch counterpart to get_section_excerpt, resolves N previews in one call, and provides error handling and token savings. This distinguishes it from the sibling get_section_excerpt.

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 implies batch usage ('batch counterpart', 'resolves N previews') but does not explicitly state when to use this tool vs alternatives or when not to use it. No exclusions or alternative comparisons are provided.

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