origin_labtalk

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

With no annotations, the description carries the full burden, and it delivers: it explains that `returned` only means parsed/dispatched, not that anything happened; it discloses that scripts stop at the first bad expression and the last captured line indicates progress; and it warns that Origin's own error text cannot be captured. It also explains the Python refusal with the in-flight-command reason.

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 compact relative to the complexity of an escape-hatch tool, and every sentence contributes: purpose, use preference, return-value meaning, failure behavior, and a critical limitation. The first line is a clear summary, and the details are front-loaded in order of importance.

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 covers use guidance, result interpretation, error behavior, and refused script types, which is strong for a general-purpose tool. The one notable gap is explicit handling of the `capture_output` parameter, especially since the schema provides no explanation for it.

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 schema has 0% description coverage, so the description must compensate. It adds meaningful semantics for `script` by explaining execution behavior, failure mode, and Python restriction. However, it never explicitly describes `capture_output` or how it affects the returned result, so the compensation is incomplete.

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 opens with a specific verb and resource: 'Run a LabTalk script inside Origin and return what it printed.' It also positions itself as 'the escape hatch' and tells the agent to prefer dedicated tools, which distinguishes it from the many sibling tools without needing to open their schemas.

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 explicitly says to 'prefer a dedicated tool where one exists' because this tool 'cannot check its own work,' giving clear when-to-use versus when-not-to-use guidance. It also states that Python-starting scripts are refused and why, which further constrains appropriate usage.

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