Moldability Check

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

Annotations already declare readOnlyHint=true, and the description adds substantial non-obvious behavior: local wall-thickness sampling via inward chords, the pure-Python screening logic, graceful degradation when corpus fields are missing, and the exact returned verdict plus sample counts. Nothing contradicts the read-only annotation.

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 every sentence earns its place: purpose, method, fidelity level, key parameter effects, and return shape. It front-loads the core behavior and uses code formatting for parameter names and output keys, making it easy to scan.

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 no output schema, the description compensates by spelling out the return structure. It covers the main behavior, key parameters, fidelity, escalation, and degradation. Minor gaps remain around the threshold/override parameters, but overall an agent can call and interpret this tool correctly without outside documentation.

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 `material` (drives wall band, CTE shrinkage, cooling) and `nominal_mm` (anchors range check), and references 'same shrinkage/thickness overrides as moldability_screen apply.' However, it does not explain fail_ratio, warn_ratio, alpha_per_k, sink_factor, t_ambient_c, or t_solidify_c, leaving meaningful gaps for a 9-parameter tool.

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 states a precise verb-resource pair: it resolves the model handle's solid, samples wall thickness, and grades it through the moldability screen. It also distinguishes itself from nearby siblings by explicitly invoking optics_moldability_check machinery, returnable moldability_screen verdict fields, and escalation to molding_fill_submit.

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 clearly positions this as a 'Geometry-aware moldability DFx screen' and 'Low-fidelity gate' with an explicit escalate_to='molding_fill_submit' path. It gives clear context for when to use it, though it stops short of explicitly enumerating when to prefer moldability_screen or optics_moldability_check instead.

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