Coin IRA Crypto Calculators

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

The annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond that: it uses 'cached daily closing market prices' and returns 'Coin IRA attribution, source links, price dates, results, and disclosures,' which helps set expectations about data freshness and output contents.

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 two tightly written sentences. The first states the tool's core function and inputs, and the second discloses the data source and return contents. Every sentence earns its place with no repetition of title or schema.

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 return fields: attribution, source links, price dates, results, and disclosures. It is largely complete for a read-only calculator, though it does not address edge cases like unavailable price data for a requested date or the exact value format returned.

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?

With 50% schema description coverage, the description compensates by clarifying that 'amount' is a USD investment, 'start' is the purchase date, and 'end' is a later valuation date. It also names the supported assets that the schema's enum lists, adding semantic meaning beyond the raw parameter definitions.

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 uses a specific verb and resource: 'Calculate what a past USD investment in BTC, ETH, XRP, or SOL would be worth on a later date.' It clearly states the assets, the investment amount, and the date-span behavior, making the tool's purpose unambiguous and distinct from the sibling retirement-projection tool.

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 provides clear context for when to use the tool: when a user wants historical crypto investment growth over a date range. However, it does not explicitly exclude alternative tools or mention the sibling calculate_retirement_projection, so an agent gets no explicit when-not-to-use 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?

Annotations already declare readOnlyHint and idempotentHint, and the description adds meaningful behavioral context: it relies on a caller-supplied constant return, ignores market prices, and returns attribution, source links, results, and disclosures. This goes beyond what the annotations expose.

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?

Four short, front-loaded sentences clearly state the action, the key input assumption, the key exclusion, and the returned content. Every sentence adds distinct information with no filler or repetition.

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?

The description captures the tool's purpose and return categories, which is decent for a read-only calculator. However, with five required parameters and no output schema, it leaves critical invocation details undocumented, such as parameter meaning, units, and enum interpretation.

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 carries the burden of explaining parameters, but it only indirectly references annual_return via 'caller's constant annual return.' It does not explain starting_balance, monthly_contribution, years, or asset semantics, nor units like whether annual_return is a percentage or decimal.

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 hypothetical compound growth for a supported crypto retirement account.' It also distinguishes itself from the historical sibling by stating 'Does not use market prices or predict an asset's return,' making the tool's role clear.

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 context: call this when the caller wants a projection based on their own constant annual return rather than market data. However, it never explicitly names the alternative or states when NOT to use this tool, so guidance remains implicit rather than directive.

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