get_model_guidance

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

The description adds meaningful behavior beyond annotations: results may include learned overlay from past research, a research directive, variant-aware overrides, and a fit block that only appears when the GPU cannot hold the model. This helps the agent anticipate dynamic or conditional output content.

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 dense but well organized: core purpose first, then variant-aware usage, then learned/research behavior, then a conditional output note. Every sentence adds new useful information and none is redundant.

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 output schema and strong annotations, the description covers the main behavioral and usage nuances: what the guidance includes, when variant overrides apply, when to research external information, and when the fit block appears. The main gap is that parameter defaults and family semantics are not fully spelled out, but the description is still strong enough for safe invocation.

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 model_filename as a variant override selector, and family is inferable as the model-family identifier. However, it does not specify valid or default values for either parameter, what happens when both are empty, or how family and model_filename interact more precisely.

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 identifies the exact deliverable—tuned settings for a model family—and enumerates its content: sampling settings, resolutions, technique blocks, and prompt style notes. It is clear enough to distinguish from sibling tools like get_node_info or list_models, but it never uses an explicit retrieval verb beyond the name 'get_model_guidance'.

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 gives explicit usage context: pass model_filename so variant-specific overrides apply, and for brand-new models verify online and call record_learning. It lacks explicit comparisons like 'use this instead of X' or 'not for Y', but it gives enough situational guidance for choosing and using the tool.

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