wear_estimate

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

With no annotations, the description carries the full burden and does so well: it discloses the empirical fallback for wear_coef (order-of-magnitude lookup from the material_pair category), the Tabor-derived hardness default, the depth gating by max_depth_mm, and even exposes basis/provenance fields (coef_basis, hardness_basis, pass). It stops short of stating units for all inputs or failure behavior when the material lookup misses.

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 definition is compact and front-loaded, leading with the operation and governing equation before parameter behavior and returns. The em-dash-heavy run-on style compresses several facts per sentence, which is efficient but slightly harder to parse than discrete clauses.

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 7-parameter tool with no annotations and no output schema, the description does strong work: it enumerates the returned object so the agent knows what comes back, and covers every optional input's role. Remaining gaps are minor — the expected shape/type of material_pair and lookup-failure behavior are unspecified.

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 and largely does: it explains wear_coef (empirical, user-supplied or looked up), hardness_mpa (defaults to Tabor 3·σ_y of the softer member), material_pair (category-pair lookup), apparent_area_mm2, and max_depth_mm. Only load_n and sliding_dist_m go unexplained, though their meaning is evident from the formula.

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 names a specific verb and resource ("Estimate sliding wear") and anchors it with the exact model used (Archard: V = k·F·s/H), so an agent knows precisely what computation this performs. No sibling tool offers wear estimation, so there is no ambiguity to resolve.

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 is implied through the parameter narrative (pass wear_coef or let it be looked up via material_pair; hardness defaults to Tabor 3·σ_y), which tells the agent how to drive the tool but not explicitly when to prefer it over a full analysis. No when-not conditions or named alternatives are given.

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