moldability_check

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

With no annotations, the description carries the full behavioral burden and does so richly: it explains inward-chord wall sampling, the pure-Python grading process, material-driven band/shrinkage/cooling behavior, graceful degradation when corpus fields are missing, nominal_mm fallback logic, and the exact return shape plus escalation behavior.

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 front-loaded and largely free of filler, with each clause adding technical substance. A few parenthetical and run-on constructions make it harder to scan than necessary, but the content is purposeful.

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?

For a complex 9-parameter tool with no annotations, no output schema, and no schema descriptions, the description explains the process, return values, and escalation path well. However, six parameter semantics remain undocumented, so an agent lacks enough information to tune the screen confidently beyond defaults.

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 coverage is 0% and the description only directly explains model, material, and nominal_mm. It vaguely points to 'the same shrinkage/thickness overrides as moldability_screen' but does not define fail_ratio, warn_ratio, sink_factor, alpha_per_k, t_ambient_c, or t_solidify_c, leaving most of the 9 parameters undocumented.

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 a specific verb and resource: a geometry-aware moldability DFx screen that resolves a model solid, samples wall thickness, and grades thickness quality plus CTE shrinkage. It distinguishes itself from siblings by naming the low-fidelity gate, the escalation target molding_fill_submit, and the shared machinery with optics_moldability_check.

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 states that this is a low-fidelity gate and says escalate_to='molding_fill_submit', giving clear context for when to use it versus a higher-fidelity molding fill analysis. It also references moldability_screen and optics_moldability_check, though it does not lay out explicit when-not conditions.

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