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

With no annotations, the description carries the full burden; it does disclose the three computed outputs and the underlying theory, which implies linear-elastic limits. It does not state the assumed beam support condition, the units of the returned values, or the validity range of the closed-form solution — significant omissions for an engineering calculator where those assumptions determine correctness.

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?

A single dense sentence that front-loads the computation and enumerates the outputs; there is no filler or restatement.

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, and the description does list the three return values, which covers most of the gap. Still missing are the output units and the assumed support/loading configuration needed to trust the result, which matters for a formula-based tool.

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 100%, with each of the four parameters documented with units and examples (e.g. '200 for structural steel'). The description adds no parameter meaning beyond the schema, so the baseline of 3 applies.

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?

States a specific calculation ('Euler-Bernoulli elastic beam maximum center deflection') plus the two derived outputs (L/d ratio, maximum bending moment). Combined with the parameter names this leaves no ambiguity about what the tool computes, and the siblings are unrelated domains so no differentiation is needed.

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?

Naming 'Euler-Bernoulli' and 'elastic' implicitly bounds the tool to linear-elastic, small-deflection analysis, which is mild applicability guidance. However, there is no statement of which boundary condition/load case the formula assumes (simply supported vs. cantilever) or when an agent should prefer a different approach, so usage must be inferred.

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

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

No annotations are provided, so the description carries the full behavioral burden. It does signal that this is a pure computation (inputs in, derived values out) with no implied side effects, which is the key behavioral fact. However, it does not disclose what happens if neither karat nor purity_pct is supplied, which wins when both are given, the default metal, or rounding/currency conventions for the returned values.

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?

A single well-formed sentence with the output list front-loaded and zero filler. Every clause contributes either an output or an input, and there is no redundant restatement of the tool name.

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?

With no output schema, annotations, or title, the description does well to enumerate the three returned quantities. But for a five-parameter calculator it omits the default metal, the karat/purity_pct resolution rule, and the fact that there is no fallback when both purity inputs are absent. An agent can call it, but not confidently predict behavior at the edges.

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 100%, so each parameter is already documented, making 3 the baseline. The description adds only that these inputs feed fine-content and melt-value computation, restating the field groupings rather than clarifying semantics. It notably leaves the karat-versus-purity_pct precedence unexplained, which is the one piece of parameter meaning the schema does not supply.

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 ("Calculate") and enumerates exactly what is produced: fine pure metal content, troy ounces, and total intrinsic melt value. It also names the required inputs (weight, karat/purity, spot price), so an agent can tell at a glance this is a valuation calculator rather than a data lookup. Its purpose is unambiguous and does not overlap with the unrelated math siblings.

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 implies the usage context (valuing a precious-metal item from weight and spot price) but never states when to use it versus alternatives, nor any preconditions. Critically, it gives no guidance on choosing between the two overlapping purity inputs, karat and purity_pct, which is the main usage decision an agent faces here. Guidance is implied rather than stated.

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

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

With no annotations at all, the description carries the full behavioral burden. It discloses the core semantics (overlap of concurrent range zones, expressed in millions of years), which is the key trait, but says nothing about the result when taxa ranges do not overlap, how unknown or misspelled taxon names are handled, the intended stratigraphic timescale, or the shape and type of the returned value.

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?

One sentence, front-loaded with the verb and containing the output unit and input domain with zero filler. Every clause carries information an agent needs.

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 and no annotations, so the description is the only behavioral source, and while it states the unit of the result it does not specify the return type or edge-case results. For a one-parameter calculation tool this is close to adequate, but the heavy jargon ("Concurrent Range Zone") is left undefined and failure modes go unmentioned.

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?

The single parameter has 100% schema description coverage including example values, so the baseline is 3. The description does add one piece of meaning not in the schema: the minimum of two taxa, which signals that a single entry is invalid input. It still does not clarify name-matching behavior (synonyms, case, taxa absent from the underlying dataset).

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 pairs a specific verb ("calculate") with a precisely named output ("chronostratigraphic Concurrent Range Zone overlap duration in millions of years") and its input domain (2+ index fossil taxa). Nothing about the operation is ambiguous, and the sibling tools (bullion_melt, specific_gravity, watch_beat_math, beam_deflection) are unrelated domains, so no disambiguation is required.

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 only implied by the domain framing: an agent can infer this is for stratigraphic range-overlap analysis on index fossils, and the description supplies the "2 or more" minimum as a hard condition. There is no explicit statement of when to prefer this over an alternative, no prerequisites, and no note on what to do with a single taxon or non-overlapping ranges.

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

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

With zero annotations, the description carries the full burden. It discloses the Archimedean method and that alloy matching occurs, but says nothing about failure modes (e.g., submerged weight ≥ dry weight), precision/rounded output, or what the alloy result actually contains. A calculator tool with an inference step needs more disclosure than this.

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?

A single front-loaded sentence with no filler. Minor deduction because the phrase 'displacement volume' implies a parameter that doesn't exist, which could momentarily mislead an agent scanning the inputs.

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 two-parameter computational tool with no output schema, the description should say what comes back (SG value, matched alloy set, confidence) and how invalid inputs behave. It hints at alloy output but leaves the return shape and edge-case behavior 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 100% and both parameters already document units ('grams') and meaning, so the description correctly relies on the schema. It adds no further meaning such as expected ranges or the physical constraint linking the two weights, so baseline 3 applies.

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+resource ('Compute Archimedean specific gravity') and enumerates the derivation chain (dry and submerged weights → displacement volume → alloy identification). It is clearly distinguishable from siblings like bullion_melt and watch_beat_math, though the mention of 'displacement volume' as an input-ish noun is slightly ambiguous since no volume parameter exists.

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 implied use case is clear: you have weight_air and weight_water and want SG plus an alloy guess. However there is no explicit when-to-use versus when-not guidance, no note that weight_water must be less than weight_air for a valid result, and no statement about whether the alloy matching is optional or unconditional.

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

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

No annotations are supplied, so the description carries the full disclosure burden. It identifies the computed quantities but never states that this is a pure, side-effect-free calculation with no external data or permissions required, nor does it note that lift_angle influences the result. For a low-risk calculator this is acceptable, but it leaves the behavioral profile to inference.

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?

A single front-loaded sentence with the outputs enumerated compactly. No filler, no repetition of the tool name, nothing that could be cut without losing information.

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?

With no output schema, the description usefully enumerates the return values (Hertz, ticks per second, daily rate deviation), which is exactly what an agent needs. The remaining shortfall is that lift_angle's effect and the expected units/range of rate_sec_day are not clarified beyond the schema.

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 100%, so bph, lift_angle, and rate_sec_day are already documented with examples and a default. The description adds only the framing that rate_sec_day relates to the daily rate deviation output; it does not explain how lift_angle changes the computation or how the parameters interact. Baseline 3 is appropriate.

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?

States a specific verb (Calculate) plus a precise domain resource (mechanical watch movement escapement frequency) and names the exact outputs (Hertz, ticks per second, daily rate deviation). The sibling tools are all unrelated calculators (bullion_melt, specific_gravity, beam_deflection, fossil_age_overlap), 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 only implied: an agent can infer it applies when converting a beat rate (BPH) into frequency/rate figures. There is no explicit statement of when to use it, no preconditions, and no mention of whether bph must be a standard value. With no sibling in the same domain, the lack of routing guidance is a minor but real gap.

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