split_inp

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 the input format is deprecated, that generated files are SPECIFICATIONs carrying the old transformation plus optional mean/harmonics/AR/MA, and that the output feeds a downstream univariate modeling loop. It does not say whether files in out_dir are overwritten, whether the directory is created, or how partial failures are handled — significant gaps for a file-writing tool.

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 conversion action is front-loaded in the opening sentence, which is good. But the second paragraph mixes operational guidance with motivational framing ('the univariate models are the seed and the yardstick') and unexplained jargon, so not every sentence earns its place as an invocation aid.

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?

An output schema exists, so return values need not be described, and the description does connect the tool to the downstream univariate workflow. For a 6-parameter file-generating tool with no annotations, though, it omits directory/overwrite semantics and explicit parameter-to-argument mapping, leaving it only partially complete.

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 does explain the intent of mean ('estimated mean'), harmonics ('seasonal harmonics'), and ar/ma ('free regular AR/MA'), and 'if asked' maps to the boolean toggles. But path and out_dir — the two required parameters — get no explicit treatment, leaving a meaningful gap.

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 first sentence names a specific verb and transformation: convert a multivariate drvarma .inp into one fue .inp per series. That distinguishes it from siblings like write_specs or build_univariate. The second paragraph drifts into workflow advice, and terms like 'fue' and 'art' are unexplained jargon, but the core action is identifiable.

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 a sequence — split, then take each file through art to build a univariate model, then return with .pre files — which is genuine usage context. However, it never states when to choose this over alternatives such as write_specs, nor any preconditions or exclusions. Usage is implied rather than spelled out.

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