dfa_check

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

With no annotations at all, the description carries the full burden and does so: it discloses the scoring formula (theoretical_min/(part_count+fastener_count)), that theoretical_min falls back to 1, that assembly_score is monotone decreasing in part/fastener count, that the result is an ordinal correlation with fidelity='correlation' and band_pct=None, and even enumerates the returned fields. This is unusually rich behavioral disclosure for a metric tool.

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?

It is dense but front-loaded: purpose first, then the formula, then usage caveat, then return shape. Parenthetical formulas are efficient rather than wasteful, though the long single block with stacked em-dashes and parentheticals is harder to scan than it could be.

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?

There is no output schema, so the description assumes the job of describing the return object and does list all nine fields, and it flags the key interpretive caveat (ordinal, not absolute). Remaining gaps — no statement that this is a pure calculator requiring no document handle, and no per-field meaning for handling_difficulty/symmetry_score — are modest given the overall coverage.

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%, so the description must compensate, and it does: it ties unique_part_count to theoretical_min ('or 1' explains the null default), ties insertion_axes and symmetry to the handling penalty, and explains the role of part_count and fastener_count in the denominator. It does not state the numeric defaults for faster/symmetry/symmetric_fraction, leaving a small gap.

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 opens with a specific verb+resource ('Grade an assembly') and immediately names the methodology (Boothroyd-Dewhurst-lite), which is far more precise than most siblings like dfm_check or moldability_check. It never explicitly contrasts itself with those siblings, so it stops short of a 5.

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 gives real usage direction: the score is 'an ordinal index for comparing variants' and the agent is told explicitly 'rank with it, don't gate on the absolute value.' That is a clear when-to-use plus a when-not-to guidance. It names no alternative tool, so it is not a full 5.

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