avl.mesh_sensitivity

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

With annotations only covering the safety profile (readOnly=false, destructive=false, idempotent=false), the description adds substantial behavior: work happens on staged copies rather than the source model, every mesh is preflighted against the vortex budget, one total timeout bounds the whole run, and artifacts (JSON, CSV, Markdown) are written. It also bounds the interpretation of results — tolerances apply only to the final adjacent pair, and no Richardson extrapolation or geometry suitability proof is produced.

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?

Front-loaded with the core operation in sentence one and zero filler; the trailing caveat sentence is dense but earns its place by preventing a false convergence claim. Slight cost in readability from cramming four distinct facts into the final sentence.

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, file-writing study tool with six parameters, no output schema, and no annotation coverage, the description does well on outputs and runtime semantics (artifact formats, single total timeout, tolerance scope). Gaps remain around required inputs (model_path), where artifacts land, behavior on preflight failure, and the what-happens-next story if a mesh exceeds the vortex budget.

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 carry the load, and it does for the highest-risk parameters: 'factors' gains an implicit starting-at-1/increasing constraint (tighter than the schema's minItems 2/maxItems 8) and 'absolute_tolerances' is characterized as assessing only the final adjacent difference. It says nothing about model_path, references/References, length_unit, case_name, or the metrics selection, leaving a meaningful share of the six parameters unexplained.

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 resource (compare a fixed flight condition across 2-8 increasing mesh factors) and states the scope constraint (starting at 1). The following sentences sharpen the mechanism — chord/span refinement on staged copies with fixed body discretization — so the agent knows exactly what operation this is, well beyond the bare tool name.

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?

Usage context is implied by the study framing (mesh sensitivity/convergence work) and by the explicit disclaimer that no convergence claim is made, but there is no statement of when to prefer this over siblings like avl.sweep or avl.run, nor prerequisites such as the vortex budget configuration being mandatory.

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