add_entry

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

With no annotations, the description carries the full burden. It discloses that entries are not versioned and that dataset_path must be initialized, but does not describe error conditions, side effects, or return behavior. Adequate but could be more detailed.

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, front-loading the action. However, it could be slightly more efficient by integrating parameter hints without adding verbosity.

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 rich input schema with multiple optional fields and an output schema, the description is insufficient. It does not mention the output or explain how optional parameters affect behavior, leaving gaps for an 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?

Schema description coverage is 0%, so the description must compensate. It only mentions question and answer, ignoring optional fields like contexts, ground_truth, tags, and metadata. This omission limits understanding of the tool's full capability.

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 adds a question-answer pair to the working tree of a golden dataset, which is specific and distinguishes it from sibling tools like commit_version or delete_entry.

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?

It mentions that entries are not yet versioned and that commit_version should be used to snapshot them, and that dataset_path must be initialized. This provides clear context for use, though it does not explicitly exclude other scenarios or mention when to use alternatives like update_entry.

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