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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function and return format, including details like 'latest value, average value, trend direction, and number of data points analyzed.' However, it lacks information on potential limitations (e.g., rate limits, data availability, error conditions) or performance characteristics. The description adds value but isn't comprehensive for behavioral 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 well-structured and appropriately sized. It starts with a clear purpose statement, followed by a 'Parameters' section with a concise explanation, and a 'Returns' section detailing the output. Every sentence adds value without redundancy, making it easy for an agent to parse and understand.

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's moderate complexity (1 parameter, no output schema, no annotations), the description is fairly complete. It covers the purpose, parameter semantics, and return format in detail. However, it lacks context on how it differs from sibling tools and doesn't mention potential behavioral aspects like error handling or data sources, leaving some gaps for the 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?

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'days' is 'Number of days to analyze (must be a positive integer),' clarifying the parameter's purpose and constraints. This compensates well for the schema's lack of documentation, though it doesn't cover edge cases like maximum allowed days.

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: 'Analyze trends in Crypto Fear & Greed Index over specified days.' It specifies the verb ('analyze trends'), resource ('Crypto Fear & Greed Index'), and scope ('over specified days'). However, it doesn't explicitly differentiate from sibling tools like 'get_current_fng_tool' or 'get_historical_fng_tool', which likely provide raw data rather than analysis.

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 no guidance on when to use this tool versus its siblings ('get_current_fng_tool' and 'get_historical_fng_tool'). It mentions the parameter 'days' but doesn't explain alternative scenarios or prerequisites. Without explicit when/when-not instructions, the agent must infer usage from the purpose alone.

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 burden of behavioral disclosure. It only states what the tool does without mentioning any behavioral traits such as rate limits, authentication needs, data freshness, or error handling. For a tool with zero annotation coverage, this is a significant gap in 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 and front-loaded in a single sentence: 'Get the current Crypto Fear & Greed Index as a tool.' It efficiently conveys the core purpose without unnecessary details. However, the phrase 'as a tool' is redundant and could be omitted for better clarity.

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's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states the purpose but lacks context on usage guidelines, behavioral traits, or output format. For a tool with no structured data to rely on, the description should provide more completeness to aid the agent effectively.

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 0 parameters, and the schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the absence of parameters. A baseline score of 4 is appropriate as the description doesn't need to compensate for any parameter gaps.

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: 'Get the current Crypto Fear & Greed Index'. It specifies the verb 'Get' and the resource 'Crypto Fear & Greed Index', making the function unambiguous. However, it doesn't explicitly differentiate from its sibling tools (analyze_fng_trend, get_historical_fng_tool), which would require mentioning it retrieves only the current value versus historical data or trend analysis.

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 no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools (analyze_fng_trend, get_historical_fng_tool) or specify contexts like needing real-time data versus historical analysis. Without such distinctions, the agent lacks clear usage instructions.

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 carries full burden but offers minimal behavioral context. It mentions the tool returns historical values as a string, but lacks details on data format, potential rate limits, error handling, or authentication needs. For a data retrieval tool with zero annotation coverage, this is insufficient.

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 appropriately sized and front-loaded, with the core purpose stated first followed by parameter and return details. It avoids redundancy, though the phrase 'as a tool' is slightly verbose and could be omitted for tighter phrasing.

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's complexity (data retrieval with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return format beyond 'str', missing details like data structure (e.g., JSON, CSV), timestamps, or error cases, which are critical for effective tool use.

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 must compensate. It adds meaning by specifying that 'days' must be a positive integer and indicates it determines the retrieval period. However, it doesn't clarify constraints like maximum days, date ranges, or default values, leaving gaps in parameter understanding.

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 historical Fear & Greed Index data for a specified number of days, using specific verbs ('Get', 'retrieve') and identifying the resource. It distinguishes from the sibling 'get_current_fng_tool' by specifying historical data, though it doesn't explicitly differentiate from 'analyze_fng_trend' which might involve analysis rather than retrieval.

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 no guidance on when to use this tool versus its siblings. It doesn't mention alternatives like 'get_current_fng_tool' for current data or 'analyze_fng_trend' for trend analysis, nor does it specify prerequisites or exclusions for usage.

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