lira_import_text_model

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

No annotations are provided, so the description carries the full burden. It discloses the input format structure (numbered documents) and the output file type (.lir), which is useful. But it says nothing about overwrite behavior on save_as, prerequisites such as an open model, or how malformed text is handled, leaving significant behavioral gaps for a mutation 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 core verb and resource are front-loaded, followed by supporting format details. The numbered-document examples earn their place by illustrating the input format. Slightly verbose in the document list, but no sentence is wasted.

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 explained. The description covers the input format and output file well. Gaps remain around prerequisites, overwrite behavior, and error handling, but for a two-parameter import tool the coverage is largely adequate.

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 add meaning for both parameters: it explains the text format's document structure and clarifies that save_as is a .lir file. However, it does not specify path semantics for save_as or constraints on text beyond the format sketch, so compensation is partial.

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 uses a specific verb and resource: 'Create a model from LIRA's text input format and save it as save_as (.lir).' This clearly distinguishes it from lira_create_model (which presumably creates a model without text import) and from lira_export_text (the inverse operation). However, it does not explicitly name the sibling it is not, so an agent still has to infer the boundary with lira_create_model.

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 usage through the phrase 'The best way to learn it is to export a similar model with lira_export_text,' which routes the agent to a learning path but not a when-to-use-this-instead rule. There is no explicit statement of when to choose this over lira_create_model or lira_write_table, so usage guidance is implied rather than stated.

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