commit_version

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

With no annotations, the description must disclose behavioral traits. It mentions immutability, auto-increment, and failure on empty working tree. But it omits details like whether the operation is destructive, required permissions, or any side effects. Some behavior is disclosed, but not comprehensively.

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 extremely concise: two sentences that immediately convey the purpose and key behaviors. Every sentence adds value without unnecessary 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?

Despite having an output schema, the description lacks essential completeness: it does not explain the parameters nor provide error conditions beyond the empty tree scenario. Given the presence of nested objects and no annotations, the description falls short of being fully informative.

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%, meaning no parameter descriptions in the schema. The tool description does not explain the parameters (dataset_path, description) beyond the overall action. This leaves the agent unclear about what each parameter means or how to use them properly.

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: 'Snapshot the current working tree as a new immutable dataset version.' It also notes version auto-increment and the failure condition when working tree is empty. This distinguishes it from sibling tools like add_entry or dataset_status, though it doesn't explicitly contrast them.

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 when to use (to create a version) and provides a condition for failure (empty working tree). However, it does not mention when not to use it, prerequisites, or alternatives. The guidance is minimal but adequate.

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