80% Silver Melt Calculator

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

With no annotations provided, the description carries the full behavioral burden. It discloses that the calculation uses the current silver spot price and returns total ASW in troy oz and grams plus melt value in both USD and CAD. It does not discuss error cases or spot-price sourcing, but the core behavior and outputs are clearly described.

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 long but earns its length: the coin-type enumeration is redundant with the schema yet strengthens purpose clarity, and the usage and return paragraphs are tightly written. It is well-structured and front-loads the core action, though it could trim the repeated coin list slightly.

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 correctly explains the return values (ASW in troy oz/grams, melt value in USD/CAD) and the input pattern (coin_type + quantity OR face_value). It lacks an explicit statement about what happens if both quantity and face_value are provided, but for a tool this size the description is substantially complete.

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 100% with detailed per-preset ASW values, so the baseline is 3. The description adds meaningful usage semantics beyond the schema: it clarifies that quantity and face_value are alternatives ('either... or'), gives a concrete example ('face_value 2.50 for a roll of dimes'), and explains that coin_type selects the preset. This elevates the score to 4.

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 clearly states the verb 'Calculate' and the resource 'melt value of junk silver coins', listing all supported coin types with their composition and date ranges. It is specific enough to be distinguished from the more generic sibling names, but it does not explicitly name or differentiate from 'calculate_melt_value', so it falls short of the strict 'distinguishes from siblings' bar.

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 gives concrete usage context: it scopes the tool to junk/constitutional silver presets and instructs the agent to provide 'the coin type plus either a quantity of coins or a total face value', with an example. It does not explicitly exclude alternatives or say when NOT to use this tool, but the domain is clearly bounded.

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, the description carries the behavioral burden. It discloses the output format (USD and CAD amounts plus fine metal weight) and clarifies ambiguous semantics like 'oz = avoirdupois ounces — postal-scale ounces' and purity fraction meanings. It does not mention reliance on live spot prices or rounding behavior, but for a calculator this is adequate.

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?

Three sentences with no filler: the first states purpose, the second states what is returned, the third clarifies parameter semantics. The most critical information is front-loaded and every sentence contributes.

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 simple 4-parameter calculator with no output schema, the description is nearly complete: it explains the purpose, all parameter meanings, example purities, and output values. The only missing elements are an explicit pointer to calculate_coin_melt for coin-specific cases and a note on the spot-price source, but these are minor for a competent agent.

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 100%, so the baseline is 3. The description adds meaningful value beyond the schema by giving concrete purity examples (0.925 sterling, 0.999 fine, 0.9 US coin silver) and disambiguating the unit 'oz' as avoirdupois postal-scale ounces, which is not evident from the enum alone.

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 and resource: 'Calculate the melt value (intrinsic bullion value) of silver or gold from weight and purity.' The examples (sterling silver flatware, .999 rounds, scrap gold) further clarify scope and distinguish it from siblings like calculate_coin_melt (coin-specific) and get_spot_price (price lookup).

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 establishes clear applicability: use when you have weight and purity for silver or gold, with concrete item examples. However, it does not explicitly mention when not to use it or point to the alternatives (e.g., calculate_coin_melt for coin-specific valuations), so it stops short of full routing guidance.

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, the description carries the full burden, and it discloses that prices are live, cached up to 15 minutes, and quoted per troy ounce in USD and CAD. This gives the agent useful behavioral expectations, though it does not describe the exact response shape or field names since no output schema is provided.

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?

Three sentences, all informative and front-loaded with the core purpose, followed by usage guidance and key caveats. No fluff or 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?

For a zero-parameter getter, the description covers the subject metals, currencies, unit of measure, and data freshness. It is slightly incomplete because it does not hint at the output structure or field names, but the lack of parameters and the simplicity of the tool make this a minor gap.

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 tool has zero parameters, so the baseline is 4. There is nothing for the description to clarify about parameter semantics, and the schema coverage is effectively complete because no parameters exist.

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 states a specific verb ('Get'), a precise resource (current spot price), and scopes it to silver and gold in USD and CAD per troy ounce. This clearly differentiates it from the sibling calculate_coin_melt and calculate_melt_value tools, which perform calculations rather than retrieve live prices.

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 explicitly says to use this tool for questions about silver spot price, gold spot price, or the USD→CAD exchange rate used in melt value calculations. It provides clear context for when the tool is appropriate, though it does not explicitly state when not to use it or name a preferred alternative.

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