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

Despite having no annotations, the description fully discloses behavioral traits: returns ordered [timestamp_ms, price] pairs, automatic granularity adjustment based on days, retry with 5-second backoff on rate limits, and accepts common symbols or CoinGecko IDs. No contradictions with annotations.

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 well-structured and concise: front-loaded with purpose, followed by output format, use cases, granularity details, usage guidance, and fallback behavior. Every sentence provides necessary information without redundancy.

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?

Given no annotations and an output schema present, the description covers all critical aspects: purpose, parameters, behavior, error handling (retry), and differentiation from siblings. It is sufficiently detailed for correct tool invocation.

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%, but the description compensates by explaining the days parameter's effect on granularity (5-min, hourly, daily), default value (7), valid range, and that symbol accepts common symbols or CoinGecko IDs. It does not detail the currency parameter beyond default, but adds substantial meaning overall.

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 tool's purpose: retrieving historical price data for a cryptocurrency over a specified number of days. It distinguishes itself from sibling tools by explicitly contrasting with get_price for single current prices and mentioning use cases like charting and backtesting.

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?

Provides explicit guidance on when to use this tool ('when you need a price series rather than a single current price') and points to the sibling tool get_price as the alternative. Also specifies valid range (1-365 days) and data granularity variations, enabling correct decision-making.

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?

Describes returns in detail, mentions data sources (CoinGecko, Alternative.me), and notes it takes no parameters. No destructive effects implied. Lacks mention of data freshness or rate limits, but for a read-only no-param tool this is sufficient.

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?

Concise yet informative. Purpose stated first, then returns, usage guidance, and data source. Every sentence adds value with no redundancy.

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?

Provides enough context for an agent to decide when to use it. Since output schema exists, agent can see structured return details. Could mention the output schema explicitly, but not necessary.

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?

No parameters exist, so no additional semantics needed beyond noting 'takes no parameters.' Schema coverage is 100%. Baseline for 0 params is 4, and the description meets that.

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?

Clearly states it gets a broad snapshot of the entire cryptocurrency market and lists specific data returned (market cap, volume, dominance, etc.). Distinguishes well from sibling tools that focus on individual tokens or 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?

Explicitly says when to use: for macro context before individual analysis or when user asks about market sentiment. Does not explicitly state when not to use, but the sibling list implies it is not for single token queries.

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 provided, the description fully carries the burden. It discloses server-side caching (60-second update), error return on missing token or API unavailability, and implicitly indicates it is a read-only, non-destructive operation. No contradictions.

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 four sentences, front-loading the main action. Every sentence adds value—purpose, when to use, accepted formats, caching behavior, error handling. No redundancy or fluff.

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?

Given the tool has an output schema, the description covers key return fields (price, 24h change, market cap, volume) and error behavior. It addresses all relevant aspects for a simple single-token price tool, making it complete in context.

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 description must compensate. It explains symbol accepts common symbols or full CoinGecko IDs, adding valuable context. However, it does not elaborate on the 'currency' parameter beyond what the schema (title and default) provides, leaving a gap in compensation.

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 tool retrieves current price, 24h change, market cap, and volume for a single token. It distinguishes from sibling 'get_prices' by explicitly noting it's for one token while get_prices is for multiple. Acceptable symbol formats are specified, making purpose unambiguous.

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 when to use ('need live market data for one token') and when not to ('for multiple tokens, prefer get_prices'). It also mentions caching and error handling, providing clear context for invocation.

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 discloses important behaviors: same fields as get_price, graceful omission of unresolved symbols, acceptance of multiple symbol formats, and error conditions. However, it could mention rate limits or authentication requirements for fuller transparency.

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 concise at six sentences, each adding essential information. It is well-structured: purpose, usage guide, efficiency claim, field consistency, error handling, and input format. No redundant text.

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?

Given two parameters, no enums, an output schema, and sibling tools, the description covers purpose, usage, error behavior, and input constraints. It omits the list of supported currencies for the 'currency' parameter, but the default and context of cryptocurrency pricing mitigate this gap. Overall comprehensive.

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 input schema has 0% description coverage, so the description must compensate. It adds meaning for 'symbols' (accepts common symbols or CoinGecko IDs) but does not clarify valid values for 'currency' beyond the default 'usd'. The added value is partial.

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 tool gets current prices for up to 50 cryptocurrency tokens, using a specific verb ('get') and resource ('prices'), with constraints on batch size. It explicitly distinguishes itself from sibling 'get_price' by noting efficiency for multiple tokens.

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 explicit guidance: 'Always prefer this over multiple get_price calls when you need data for two or more tokens.' It also explains error handling (empty list or exceeding 50 tokens) and acceptable input types, providing clear when-to-use context.

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 provided, so the description carries the full burden. It discloses that project descriptions are truncated to 500 characters, and that it accepts both symbols and IDs. It does not explicitly state read-only nature or any other behaviors like data freshness, but the truncation detail and input flexibility add 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?

The description is a single focused paragraph that front-loads the main purpose. Every sentence contributes useful information, with no wasted words. It is appropriately sized for the tool's complexity.

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?

Given one required parameter and an existing output schema, the description provides a thorough summary of returned data (market cap rank, ATH/ATL, supply, price changes, etc.). It also mentions the truncation limit, covering all necessary context for agent usage.

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% with no parameter description. The description compensates by stating 'Accepts common symbols (BTC, ETH) or CoinGecko IDs,' which adds meaningful guidance beyond the schema's simple 'Symbol' title.

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 'Get detailed fundamental information about a cryptocurrency token' and lists specific data points like project description, market cap rank, ATH/ATL, supply, etc. It distinguishes from siblings by explicitly mentioning 'For just the current price or market cap, use get_price instead.'

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?

Provides explicit when-to-use context: 'when you need more than just a current price, for example for fundamental analysis, understanding a token history, or answering questions about supply dynamics.' Also tells when not to use it, naming the alternative tool get_price, and specifies accepted input formats (common symbols or CoinGecko IDs).

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