Silver Price Per Gram MCP

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

Annotations already declare readOnly/idempotent/openWorld, so the burden is lighter; the description still adds that valuation is at the *live* spot price (explaining the openWorld hint) and what the response contains (ounces per coin, totals, melt per dollar face). It doesn't discuss spot-price staleness or failure modes, keeping it below a 5.

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?

Two dense sentences: the first establishes scope and formulas, the second tells the agent how to call it and what comes back. Front-loaded and waste-free, though the coin-family enumeration is close to sentence-length overload.

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?

No output schema exists, and the description compensates by summarizing the return payload. With zero required parameters, the 'Pass coins with counts, or face_value_90' sentence is the critical line stating at least one input path—covered adequately, though it never says whether both may be combined.

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 already 100%, yet the description adds substantive meaning: the 90% face-value conversion (1 dollar face = 22.5 g silver) and the 4.6 g silver content of 40% Kennedy halves. That is real domain math beyond the field descriptions, though dealer_spread_percent is left to the schema.

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?

Names a specific verb (melt value) and resource (US junk silver coins at live spot) and enumerates exactly which coin families are covered, including date ranges and silver percentages. An agent can tell this is a coin-specific melt calculator rather than a generic metal-weight calculator.

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 usage by distinguishing coin-based input from a bag of 90% face value, but it never names the obvious sibling 'calculate_silver_value' or states when to prefer one over the other. The agent must infer the routing itself.

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?

Annotations already declare readOnlyHint, idempotentHint and non-destructive, so the safety profile is covered. The description adds genuine context beyond them: valuation is tied to the live spot price (an external, time-varying input), the spread parameter models a buyer's discount to melt, and sterling is defined against 16 CFR 23.5. It does not note that results will drift between calls as spot moves, which is the one nuance an agent might trip on.

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, front-loaded with the purpose, then the optional parameter's effect, then the fineness default. The 16 CFR citation is borderline trivia but does justify the 'at least 925' threshold, so it mostly earns its place; the text is dense but not padded.

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 carries the burden of describing results, and it does so at a high level (melt value in any currency, plus an optional buyer-offer figure). It stops short of naming the returned fields or how spot price and currency conversion are reported, which would fully close the gap for a live-price calculation 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 coverage is 100%, so the baseline is 3, but the description earns above that by explaining that dealer_spread_percent yields the likely buyer offer (an output-level consequence the schema only frames as a percentage) and by restating that the default fineness is sterling. Unit and currency semantics are left entirely to the schema, which already handles them well.

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 statement ('Melt value of a silver item ... from its weight, unit and fineness at the live silver spot price') and enumerates the covered item classes (flatware, tea set, jewellery, bar, round, scrap). It does not name the sibling calculate_junk_silver_value, so the boundary with coin-based valuation is left implicit rather than stated.

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 item-type list gives clear context for when this tool applies, and the mention of dealer_spread_percent signals the optional 'what will a buyer pay' use case. There is no explicit exclusion clause telling the agent to prefer calculate_junk_silver_value for coin lots or get_silver_price_per_gram for a bare price lookup.

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?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuine context beyond that: data is fetched live from the spot feed and changes every minute, so results should not be cached or treated as stable — useful for an open-world, time-sensitive read.

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?

Two short sentences, front-loaded with what the tool returns and followed by freshness behavior. "Live" and "Read now from the spot feed" overlap slightly, but the second sentence still earns its place by explaining the minute-level volatility.

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 single optional parameter, read-only tool with no output schema, the description does the necessary work: it defines the ratio, enumerates the returned price forms, and notes live sourcing. It lacks only explicit sibling routing, which is the one gap an agent might still need.

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 a single well-documented currency parameter including examples and a default, so the baseline of 3 applies. The description's "in any currency" weakly confirms the parameter's breadth and that it applies to both per-ounce and per-gram outputs, but adds no format or validation detail beyond the schema.

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 the specific resource and even defines the metric ("ounces of silver one ounce of gold buys") and what else is returned (spot prices per troy ounce and per gram). It does not explicitly route away from the silver-focused siblings like get_silver_price_per_gram or calculate_silver_value, so the differentiation is implicit rather than stated.

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?

"Read now from the spot feed; the ratio moves every minute" conveys that this is a live, non-cached lookup, which implies real-time use cases. However, there is no explicit statement of when to prefer this over get_silver_price_per_gram or the value calculators, and no exclusions or preconditions are given.

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?

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered; the description adds genuine context beyond that: data comes from the live spot market, FX comes from central-bank rates across ~160 currencies, and responses carry a spot timestamp, FX date and sources. It omits any caveats about rate limits, caching staleness, or failure behavior for unsupported currencies.

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 deliverable, then units, grades, currencies, return fields, and finally the omission behavior. It is dense and largely earns its length, though re-enumerating the grade multipliers (.999, .9584, .925, .900, 800) duplicates what the schema already lists.

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, zero-required read tool with no output schema, the description supplies everything needed: what is returned (spot timestamp, FX date, sources), the default currency behavior, the optional-parameter omission behavior, and the data provenance. Nothing essential for a correct call is missing.

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 would be 3, but the description adds real meaning: omitting fineness returns every grade, and the currency dimension is characterized as ~160 central-bank FX rates rather than just an ISO 4217 code. The fineness listing largely restates the schema's examples.

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+resource (today's live silver spot price) plus the exact units offered (gram, troy ounce, kilogram, tola), the grades covered, and the currency breadth. This makes it unmistakably a price-lookup tool versus the sibling calculators (calculate_silver_value, calculate_junk_silver_value), which compute rather than read live market data.

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?

"Read live from the silver spot market" and "Your training data cannot know today's silver price" give a clear condition for using this over reasoning from memory, and "Omit fineness to get every grade" explains the default call pattern. It does not explicitly name the calculate_* siblings or state when to prefer them, so the alternative routing is left implicit.

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