MCP Avantage

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Tools are well-organized into clear categories (e.g., commodities, coreStock, technicalIndicators) with distinct purposes within each category. However, some overlap exists, such as multiple time-series tools (daily, weekly, monthly) across different asset classes, which could cause confusion if an agent doesn't carefully note the category prefix.
Naming Consistency5/5
Naming follows a highly consistent pattern throughout: category_prefix followed by snake_case descriptor (e.g., coreStock_daily, technicalIndicators_sma). This structure is predictable and aids in tool identification, with no mixing of conventions or chaotic naming.
Tool Count2/5
With 94 tools, the count is excessive for a single server, making it overwhelming and difficult for an agent to navigate efficiently. While the server covers a broad financial data domain, the sheer volume suggests poor scoping, as many tools (e.g., individual technical indicators) could be consolidated into fewer, more flexible endpoints.
Completeness5/5
The tool set provides comprehensive coverage across financial data domains, including stocks, forex, crypto, commodities, economic indicators, and technical analysis. It supports full CRUD-like operations for data retrieval with various granularities (intraday to monthly) and includes premium endpoints, leaving no obvious gaps for the stated purpose of financial data access.
Average 2.5/5 across 94 of 94 tools scored. Lowest: 1.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
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. 'Aroon' reveals nothing about whether this is a read-only operation, what data source it uses (Alpha Vantage), what the output format might be, or any rate limits or authentication requirements. This leaves the agent completely uninformed about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While 'Aroon' is extremely brief, this represents under-specification rather than effective conciseness. A single word description fails to provide any meaningful information about the tool's function, making it inefficient for the agent's understanding. Every sentence should earn its place, but here there's essentially no sentence at all.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what Aroon calculates, what the output represents, or how to interpret results. The agent would struggle to use this tool correctly without significant external knowledge about technical analysis.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are documented in the input schema. The description adds zero information about parameters beyond what's already in the schema. According to the scoring rules, when schema coverage is high (>80%), the baseline score is 3 even with no parameter information in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Aroon' is a tautology that merely restates the tool name without explaining what the tool does. It provides no verb, no resource specification, and no indication that this calculates a technical indicator for stock data. This fails to distinguish it from sibling tools like technicalIndicators_aroonosc or other technical indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It doesn't mention what Aroon measures (trend strength and direction), when it's appropriate compared to other indicators like SMA or RSI, or any prerequisites. With many sibling technical indicators available, this lack of differentiation is problematic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. However, it offers no information about what the tool does operationally (e.g., whether it calculates, fetches, or processes data), its effects (e.g., read-only vs. mutative), performance characteristics, or error handling. This leaves the agent with no understanding of the tool's behavior beyond its name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely concise (a single phrase), it is under-specified rather than efficiently informative. It lacks essential details about the tool's purpose and usage, making it ineffective. Conciseness should not come at the cost of clarity, and this description fails to provide meaningful content in its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is severely incomplete. It does not explain what the tool returns, how it processes inputs, or its role within the broader set of sibling tools. This inadequacy leaves critical gaps for an agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear documentation for all 5 parameters. The description adds no additional parameter semantics beyond what the schema already specifies. According to the rules, with high schema coverage (>80%), the baseline score is 3 even without parameter info in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Minus Directional Indicator (-DI)' is a tautology that merely restates the tool name without explaining what the tool does. It provides no verb indicating action (e.g., 'calculate', 'retrieve', 'analyze') and offers no context about the resource or operation involved. This fails to distinguish it from sibling tools or clarify its function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 does not mention any specific use cases, prerequisites, or comparisons with sibling tools like 'technicalIndicators_plusDI' or other technical indicators. Without such context, an agent cannot determine appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description reveals nothing about what the tool actually does - whether it calculates, retrieves, or analyzes data; what the output format is; whether it's a read-only operation; or any rate limits or authentication requirements. It's completely opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (just 4 words), this is a case of harmful under-specification rather than effective brevity. The description fails to provide any meaningful information that would help an AI agent understand or use the tool. Every word should earn its place, but here the words don't earn their place by adding value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what +DM is, what it calculates, what the output contains, or how to interpret results. The agent would have no idea what this tool actually does beyond its name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are documented in the input schema. The description adds zero semantic information about what the parameters mean in the context of +DM calculation. However, with complete schema coverage, the baseline is 3 even without additional parameter explanation in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Plus Directional Movement (+DM)' is a tautology that merely restates the tool name without explaining what the tool does. It provides no verb or action, doesn't specify what resource it operates on, and fails to distinguish this technical indicator from its many sibling tools in the technicalIndicators_* family.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. With numerous sibling technical indicators available (like minusDM, plusDI, adx, etc.), there's no indication of what +DM measures, what market conditions it's useful for, or how it differs from related indicators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Chaikin A/D Line' reveals nothing about whether this is a read-only operation, what data source it uses (Alpha Vantage), whether it requires authentication, rate limits, or what the output format looks like. For a financial data tool with no annotation coverage, this is completely inadequate 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just three words, this represents under-specification rather than effective conciseness. The description fails to front-load essential information and doesn't provide the minimal context needed for tool selection. Every sentence should earn its place, but here the single phrase doesn't earn its place by providing meaningful guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a technical indicator calculation tool with no annotations, no output schema, and a completely inadequate description, the contextual completeness is severely lacking. The description fails to explain what the tool returns, how it differs from other technical indicators, or provide any meaningful context for an AI agent to understand when and how to use it appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description adds zero parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Chaikin A/D Line' is essentially a tautology that restates the tool name without explaining what the tool does. It doesn't specify the verb (e.g., 'calculate', 'retrieve', 'analyze') or clarify that this is a technical indicator calculation tool. While it hints at the financial domain, it fails to provide a clear purpose statement that distinguishes it from sibling technical indicator tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. With numerous sibling technical indicator tools (adosc, aroon, atr, etc.), there's no indication of what makes the Chaikin A/D Line unique, when it's appropriate versus other indicators, or what analytical context it serves. The description offers zero usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. The description reveals nothing about what this tool actually does - whether it calculates values, retrieves historical data, requires authentication, has rate limits, or what format/scope of results to expect. For a technical indicator tool with no annotation coverage, this complete lack of behavioral information is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just three words, this represents under-specification rather than effective conciseness. The description fails to provide the essential information an agent needs to understand and use the tool. Every sentence should earn its place, but here the single 'sentence' (really just a label) doesn't fulfill its purpose of explaining the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 6 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what the tool returns, how to interpret results, what the Chaikin A/D Oscillator measures, or any context about its financial analysis application. For a tool that presumably calculates a specific technical indicator, this minimal description leaves the agent with insufficient information to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all 6 parameters well-documented in the input schema. The description adds no parameter information beyond what's already in the structured schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description. The description doesn't compensate but doesn't need to given the comprehensive schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Chaikin A/D Oscillator' is a tautology that restates the tool name without explaining what it does. It doesn't specify the verb (e.g., 'calculate' or 'retrieve') or clarify that this is a technical indicator for financial analysis. While the name suggests it's related to technical indicators, the description adds no meaningful clarification beyond the name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. With 70+ sibling tools including many other technical indicators (like technicalIndicators_ad, technicalIndicators_aroon, technicalIndicators_bbands), there's no indication of what distinguishes the Chaikin A/D Oscillator from other momentum or volume-based indicators. No context about appropriate use cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'Aroon Oscillator' reveals nothing about whether this is a read or write operation, what data source it accesses, what permissions might be required, rate limits, or what the output looks like. For a financial data tool with no annotation coverage, this is completely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just two words, this represents under-specification rather than effective brevity. The description fails to provide any useful information that would help an AI agent understand or use the tool. Every sentence should earn its place, but here there's essentially no meaningful content to evaluate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a financial data tool with 5 parameters, no annotations, and no output schema, the description is completely inadequate. It provides no context about what the Aroon Oscillator measures, how it's calculated, what the output represents, or why someone would use this specific technical indicator. The description fails to compensate for the lack of structured metadata.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are documented in the input schema. The description adds no additional information about parameter meaning, constraints, or relationships. The baseline score of 3 reflects that the schema does the heavy lifting, but the description provides zero value beyond what's already in structured data.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Aroon Oscillator' is essentially a tautology of the tool name 'technicalIndicators_aroonosc' and provides no meaningful information about what the tool actually does. It doesn't specify any action verb or resource, nor does it distinguish this technical indicator from the many other technical indicator tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. With 60+ sibling tools including many other technical indicators (AROON, ADOSC, BBANDS, etc.), there is no indication of what makes the Aroon Oscillator unique or when it should be selected over other technical analysis tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. 'Average True Range (ATR)' gives no information about the tool's behavior—it doesn't mention whether it's a read-only operation, what data source it uses (e.g., Alpha Vantage), potential rate limits, error conditions, or the format of returned data. This is inadequate for a tool with parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with a single phrase, the description is under-specified rather than efficiently structured. It fails to front-load critical information like the tool's action or purpose, making it unhelpful for quick understanding. Conciseness should not come at the cost of clarity, and here it results in a lack of substantive content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no annotations, no output schema), the description is severely incomplete. It doesn't explain what the tool does, how to use it, what it returns, or any behavioral aspects. With no output schema to describe return values, the description should compensate but fails to do so, leaving the agent with insufficient information for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with all parameters well-documented in the input schema (e.g., symbol, interval, time_period). The description adds no additional meaning about parameters beyond what's in the schema, such as explaining how ATR calculation uses these inputs. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema carries the burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Average True Range (ATR)' is essentially a tautology that restates the tool name with minimal expansion. It doesn't specify what action the tool performs (e.g., 'retrieves', 'calculates', or 'returns' ATR values) or what resource it operates on. While it identifies the technical indicator, it lacks a clear verb+resource combination that would make the purpose specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With many sibling tools in the technicalIndicators category (e.g., sma, ema, bbands), there's no indication of ATR's specific use case, such as volatility measurement, or when it might be preferred over other indicators. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 fails to describe any behavioral traits such as data source (Alpha Vantage), rate limits, authentication needs, output format, or whether this is a read-only operation. The description is completely inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with only three words, the description is under-specified rather than efficiently structured. It lacks any meaningful content that would help an agent understand or use the tool, making this brevity detrimental rather than helpful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 6 parameters, no annotations, and no output schema, the description is completely inadequate. It provides no context about what the tool returns, how it behaves, or when to use it, failing to compensate for the missing structured information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with all parameters well-documented in the input schema. The description adds no parameter information beyond what's already in the schema, so it meets the baseline score of 3 for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Bollinger Bands (BBANDS)' is a tautology that restates the tool name without explaining what it does. It doesn't specify the verb (e.g., 'calculate' or 'retrieve') or the resource (e.g., 'technical indicator data'), nor does it distinguish this from sibling technical indicator tools like SMA or EMA.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 Bollinger Bands' specific use cases (e.g., volatility analysis, overbought/oversold signals) or differentiate it from other technical indicators in the sibling list, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but adds nothing beyond the name. It doesn't indicate if this is a read-only query, a calculation, requires authentication, has rate limits, or what the output entails, making it completely inadequate for behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise, the description is under-specified—it's a single phrase that fails to convey necessary information. Conciseness should not come at the cost of clarity; here, the brevity results in insufficient content, not efficient communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no annotations, and no output schema, the description is severely incomplete. It doesn't explain the tool's function, usage, behavior, or output, failing to compensate for the lack of structured data and leaving the agent with minimal actionable information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no additional meaning or context about the parameters, such as typical values for 'time_period' or how 'month' interacts with 'interval'. Baseline 3 is appropriate when the schema handles all parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Directional Movement Index (DX)' restates the tool name with minimal expansion, making it tautological. It doesn't specify what the tool does (e.g., calculate, retrieve, or analyze the DX indicator) or what resource it operates on, leaving the purpose vague beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the many sibling technical indicators (e.g., ad, aroon, sma) or other tools in the server. The description lacks any context, prerequisites, or alternatives, leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 offers no information about what the tool returns (e.g., phase values, timestamps), whether it's a read-only operation, potential rate limits, authentication needs, or data sources. The description is purely a label with no behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise (one phrase), the description is under-specified rather than efficiently structured. It fails to front-load essential information about the tool's purpose or behavior. The single phrase doesn't earn its place by adding value beyond the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (technical indicator with 5 parameters), no annotations, and no output schema, the description is completely inadequate. It doesn't explain what the tool does, when to use it, what it returns, or any behavioral traits. The description fails to compensate for the lack of structured information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hilbert Transform - Dominant Cycle Phase' restates the tool name/function without explaining what it does. It doesn't specify the action (e.g., 'calculate', 'retrieve', 'analyze') or the resource (e.g., 'stock data', 'technical indicator values'). While it hints at a technical indicator, the purpose remains vague and tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With many sibling tools in the technicalIndicators category (e.g., htDcperiod, htPhasor, htSine), there's no indication of how this specific Hilbert Transform indicator differs or when it's appropriate. No context or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'Money Flow Index (MFI)' reveals nothing about the tool's behavior: it doesn't indicate whether this is a read-only operation, what data source it uses (e.g., Alpha Vantage API), potential rate limits, error conditions, or output format. For a tool with 5 parameters and no output schema, this lack of behavioral context is critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with a single phrase, the description is under-specified rather than efficiently informative. It lacks any structuring or front-loading of key information, failing to convey purpose or usage in a meaningful way. Conciseness should not come at the cost of clarity, and this description sacrifices essential details for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no annotations, no output schema, and many sibling tools), the description is woefully incomplete. It doesn't explain what MFI is, how it's calculated, what the output contains, or when to use it over other indicators. Without annotations or output schema, the description fails to provide the necessary context for effective tool invocation, leaving significant gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all parameters documented in the input schema. The description adds no parameter information beyond what's already in the schema, so it doesn't enhance understanding of parameter meanings or usage. However, the high schema coverage justifies the baseline score of 3, as the schema adequately handles parameter documentation without needing description support.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Money Flow Index (MFI)' is a tautology that merely restates the tool name with its acronym expansion. It doesn't specify what action the tool performs (e.g., 'calculate', 'retrieve', or 'analyze'), what resource it operates on, or what distinguishes it from sibling technical indicators like OBV or VWAP. While MFI is a known financial indicator, the description fails to articulate the tool's function beyond naming it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With numerous sibling tools for technical indicators (e.g., SMA, EMA, RSI-like indicators such as AROON or ULTOSC), there's no indication of MFI's specific use case, prerequisites, or comparative context. This leaves the agent without direction for tool selection among similar financial analysis functions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but provides none. It doesn't indicate whether this is a read-only operation, what data source is used (Alpha Vantage), what the output format looks like, whether there are rate limits, or any other behavioral characteristics. The description fails to disclose even basic operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with only three words, this represents under-specification rather than effective conciseness. The description doesn't front-load essential information and fails to provide the minimal context needed for tool selection. Every word should earn its place, but here the words don't provide meaningful value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a technical indicator calculation tool with 6 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what 'midpoint' means in financial terms, what the tool returns, how it differs from similar indicators, or any usage context. The description fails to compensate for the lack of structured metadata.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly with descriptions and enums. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Midpoint over period' is a tautology that essentially restates the tool name 'technicalIndicators_midpoint' without providing meaningful context. It doesn't specify what resource is being acted upon (stock data), what calculation is performed, or how this differs from sibling tools like 'technicalIndicators_midprice' which appears to be a similar technical indicator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides zero guidance about when to use this tool versus alternatives. There's no mention of what problem this indicator solves, when it's appropriate versus other technical indicators like SMA or EMA, or any prerequisites for usage. The agent must infer everything from the parameter schema alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers none. It doesn't indicate whether this is a read-only operation, what data source it uses (e.g., Alpha Vantage), potential rate limits, error conditions, or the format of the response. The description fails to describe any behavioral traits beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is concise, it is under-specified rather than efficiently structured. A single phrase ('Normalized Average True Range (NATR)') fails to convey necessary information, making it ineffective. Conciseness should not come at the cost of clarity; here, the brevity results in a lack of useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 5 parameters and no output schema or annotations, the description is severely incomplete. It doesn't explain what NATR is, how it's used, what the output contains, or any behavioral aspects. For a tool that likely returns financial data, this minimal description is inadequate to guide an AI agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional meaning about parameters, such as explaining the purpose of 'time_period' in the context of NATR or providing examples beyond what's in the schema. However, with high schema coverage, the baseline score is 3, as the schema adequately handles parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Normalized Average True Range (NATR)' is essentially a tautology that restates the tool name without explaining what the tool does. It doesn't specify the action (e.g., 'calculate', 'retrieve', or 'analyze') or the resource involved (e.g., financial data for a symbol). While it identifies the technical indicator, it fails to articulate the tool's function beyond naming it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 sibling tools (e.g., other technical indicators like ATR or BBANDS) or suggest contexts where NATR is appropriate (e.g., for volatility analysis). There's a complete absence of usage instructions, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description provides zero information about what this tool actually does behaviorally - whether it fetches data, calculates indicators, requires authentication, has rate limits, returns time series data, or has any operational characteristics. It's completely opaque about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (just 3 words), this is under-specification rather than effective conciseness. The description fails to provide any meaningful information that would help an AI agent understand or use the tool. Every word should earn its place, but here the words don't provide operational value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial data tools, no annotations, no output schema, and a description that provides only the tool's name, this is completely inadequate. The description fails to explain what OBV is, what it returns, how it differs from other indicators, or any context needed for proper tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'On Balance Volume (OBV)' is a tautology that merely restates the tool name without specifying what the tool does. It doesn't provide a verb or action, doesn't indicate this calculates or retrieves technical indicator data, and doesn't distinguish it from the many other technical indicator siblings in the list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. With 60+ sibling tools including many other technical indicators, there's no indication of what makes OBV different from other volume-based indicators like AD or MFI, or when an agent should choose this particular technical analysis tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but provides none. It doesn't indicate whether this is a read-only operation, whether it makes external API calls, what the response format might be, or any rate limits or authentication requirements. The description is purely a label with zero behavioral information, which is inadequate for a tool that presumably calculates financial indicators.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just three words, this is a case of under-specification rather than effective brevity. The description fails to provide any meaningful information about the tool's function or usage. Every word should earn its place, but here the minimal content doesn't fulfill the description's purpose of helping an AI agent understand and use the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial technical indicators and the complete lack of annotations and output schema, the description is woefully incomplete. It doesn't explain what the Plus Directional Indicator is, what it measures, what the output represents, or how to interpret results. For a tool with 5 parameters that calculates a specialized financial metric, this description provides essentially no contextual information to guide proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the input schema itself. The description adds no parameter information whatsoever - it doesn't explain what the Plus Directional Indicator calculation requires, how parameters like 'time_period' affect the indicator, or what the 'month' parameter does for intraday intervals. Since the schema does all the parameter documentation work, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Plus Directional Indicator (+DI)' is essentially a tautology that restates the tool name with minimal additional information. It identifies the technical indicator but doesn't specify what action the tool performs (e.g., 'calculates,' 'retrieves,' 'computes') or what resource it operates on. While it distinguishes this from non-technical indicator siblings, it doesn't differentiate from similar technical indicator tools like 'technicalIndicators_minusDI' or 'technicalIndicators_dx' which are clearly related directional movement indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. There's no mention of what the Plus Directional Indicator measures, its typical applications in technical analysis, or when it would be preferred over other technical indicators. With numerous sibling tools including 'technicalIndicators_minusDI' and 'technicalIndicators_dx' (Directional Movement Index), the lack of any comparative context leaves the agent with no basis for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description offers no information about what the tool does operationally (e.g., fetches data from Alpha Vantage API, calculates ROCR values, returns time series), performance characteristics, error conditions, or authentication requirements. It's a bare acronym with zero behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (just 3 words), this is under-specification rather than effective conciseness. The description fails to provide essential information that would help an AI agent understand and use the tool. Every sentence should earn its place, but this single phrase doesn't earn its place by adding meaningful value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (technical indicator calculation with 6 parameters), lack of annotations, and no output schema, the description is completely inadequate. It doesn't explain what ROCR is, what it calculates, what the output looks like, or how it relates to financial analysis. For a specialized tool in a crowded namespace, this minimal description fails to provide necessary context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly with descriptions, enums, and defaults. The description adds no parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Rate of change ratio (ROCR)' is a tautology that restates the tool name with minimal expansion. It doesn't specify what the tool actually does (e.g., calculates a technical indicator for financial data), what resource it operates on, or how it differs from sibling tools like technicalIndicators_ema or technicalIndicators_sma. The purpose remains vague beyond the acronym.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With many sibling technical indicator tools available (e.g., technicalIndicators_ema, technicalIndicators_sma, technicalIndicators_aroon), there's no indication of what ROCR is best for, when it's appropriate, or what distinguishes it from other indicators. Usage context is completely absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'Parabolic SAR' gives no information about what the tool actually does, whether it performs calculations, retrieves data, requires authentication, has rate limits, or what format/scope the output might have. This leaves the agent completely in the dark about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just two words, this is a case of harmful under-specification rather than effective brevity. The description fails to provide any meaningful information that would help an agent understand or use the tool, making it structurally deficient despite its short length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a technical indicator tool with no annotations, no output schema, and numerous similar sibling tools, the description 'Parabolic SAR' is completely inadequate. It doesn't explain what the tool calculates/returns, when to use it, or how it differs from other indicators, leaving critical gaps in understanding for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already fully documents all 4 parameters. The description adds zero additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Parabolic SAR' is a tautology that merely restates the tool name without explaining what it does. It doesn't specify the action (e.g., 'calculate', 'retrieve', 'analyze') or the resource involved, nor does it differentiate this technical indicator from the many sibling technical indicator tools listed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. With over 40 sibling technical indicator tools (e.g., technicalIndicators_sma, technicalIndicators_ema, technicalIndicators_bbands), there's no indication of what makes Parabolic SAR unique or when it's appropriate to select it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Simple Moving Average (SMA)' reveals nothing about what the tool returns (e.g., time series data, single value), whether it makes external API calls, rate limits, authentication needs, or error behavior. For a financial data tool with no annotation coverage, this is completely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (three words), this is under-specification rather than effective conciseness. The description fails to convey essential information about the tool's function and usage. Every sentence should earn its place, but this single phrase doesn't provide enough value to justify its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial technical indicators, 6 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what the tool returns, how results are structured, when to use it, or behavioral characteristics. For a tool with this level of complexity and no structured support, the description fails to provide necessary context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Simple Moving Average (SMA)' is essentially a tautology that restates the tool name without adding meaningful context. It doesn't specify what the tool actually does (e.g., calculate SMA for a given stock symbol) or distinguish it from sibling technical indicators like EMA or WMA. The purpose remains vague beyond the acronym expansion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With numerous sibling technical indicators (e.g., EMA, WMA, BBANDS), there's no indication of when SMA is appropriate versus other moving averages or technical indicators. No context about use cases, prerequisites, or comparisons is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It fails to mention what the tool returns (e.g., time series data, indicator values), any rate limits, authentication needs, or computational characteristics. The description offers no behavioral information beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise, the description is under-specified—it's a single phrase that doesn't convey purpose or usage. Conciseness should not come at the cost of clarity; here, brevity results in insufficient information, making it ineffective rather than efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a technical indicator tool with 6 parameters, no annotations, and no output schema), the description is severely incomplete. It lacks purpose, usage guidelines, behavioral details, and output information, failing to provide the necessary context for an AI agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no parameter semantics beyond what the schema provides (e.g., it doesn't explain how 'time_period' relates to T3 calculation or typical values). Baseline score of 3 is appropriate since the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Triple Exponential Moving Average (T3)' merely restates the tool name 'technicalIndicators_t3' in expanded form, making it tautological. It doesn't specify what the tool actually does (e.g., calculate T3 values for a given stock symbol) or distinguish it from sibling technical indicator tools like 'technicalIndicators_ema' or 'technicalIndicators_tema'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention any context, prerequisites, or comparisons with sibling tools (e.g., other moving average indicators like EMA or TEMA), leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, it offers no information about what the tool does (e.g., calculates or retrieves TEMA values), its output format, rate limits, authentication needs, or any side effects. This leaves the agent completely uninformed about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with a single phrase, the description is under-specified rather than efficiently structured. It fails to front-load essential information (e.g., purpose or action), making it ineffective despite its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 6 parameters, no annotations, and no output schema, the description is severely incomplete. It doesn't explain what the tool returns, how to interpret results, or any behavioral context, making it inadequate for agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing detailed descriptions for all 6 parameters. The description adds no parameter information beyond what the schema already documents, so it meets the baseline of 3 where the schema handles the heavy lifting without compensating for gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Triple Exponential Moving Average (TEMA)' is a tautology that merely restates the tool name without specifying what the tool does. It lacks a clear verb (e.g., 'calculate' or 'retrieve') and doesn't distinguish this technical indicator tool from its many siblings (e.g., sma, ema, dema) beyond the specific indicator name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 context (e.g., technical analysis for stocks), prerequisites, or comparisons to sibling tools like 'sma' or 'ema', leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'True Range' gives no information about what the tool actually does operationally - whether it fetches historical data, calculates values, requires authentication, has rate limits, returns specific data formats, or has any side effects. This leaves the agent completely in the dark about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just two words, this represents under-specification rather than effective conciseness. The description fails to provide any meaningful information about the tool's purpose or usage, making it inefficient for the agent to understand and use the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a technical indicator tool with 4 parameters, no annotations, and no output schema, the description is completely inadequate. It provides no information about what True Range is, how it's calculated, what the output contains, or how it differs from similar indicators. The agent would need to guess or have external knowledge to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents all 4 parameters (symbol, interval, datatype, month). The description adds zero additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'True Range' is essentially a tautology that restates the tool name without specifying what action the tool performs. It doesn't indicate whether this calculates, retrieves, or analyzes True Range data, nor does it distinguish this from sibling technical indicator tools like 'atr' (Average True Range) or other similar indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. With numerous sibling technical indicator tools available (like atr, bbands, sma, etc.), there's no indication of what distinguishes True Range from other volatility or range-based indicators, nor any context about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. It doesn't indicate whether this is a read-only operation, what data source it queries (e.g., Alpha Vantage), potential rate limits, authentication needs, or what the output looks like. For a financial data tool with 6 parameters, this lack of behavioral context is critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just one phrase, this is a case of under-specification rather than effective brevity. The description fails to provide necessary information about the tool's function, making it inefficient for the agent's understanding. Every word should earn its place, but here the single phrase doesn't fulfill the description's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 6 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what the tool does, how it behaves, what it returns, or when to use it. The 100% schema coverage helps with parameters but doesn't compensate for the missing operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no parameter information beyond what's already in the schema, so it doesn't compensate but also doesn't detract. This meets the baseline of 3 for high schema coverage without additional parameter context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Triangular Moving Average (TRIMA)' is essentially a tautology that restates the tool name with minimal expansion. It identifies the technical indicator but doesn't specify what action the tool performs (e.g., calculates, retrieves, or analyzes TRIMA values). Compared to sibling tools like 'technicalIndicators_sma' or 'technicalIndicators_ema', there's no differentiation in purpose beyond the indicator name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides zero guidance on when to use this tool versus alternatives. There's no mention of use cases, prerequisites, or comparisons with sibling technical indicator tools (e.g., when TRIMA is preferred over SMA or EMA). This leaves the agent with no contextual information for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'Ultimate Oscillator' reveals nothing about whether this is a read-only operation, what data source it uses (Alpha Vantage), what permissions are required, rate limits, or what the output looks like. For a financial data tool with no annotation coverage, this is completely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just two words, this is a case of under-specification rather than effective conciseness. The description fails to provide any meaningful information that would help an AI agent understand or use the tool. Every sentence should earn its place, but here there's essentially no useful content to evaluate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial technical indicators, no annotations, no output schema, and a completely inadequate description, this is severely incomplete. The description doesn't explain what the Ultimate Oscillator is, how it's calculated, what it measures, or what the output represents. For a tool that presumably returns complex financial analysis data, this description is completely inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no parameter information beyond what's already in the structured schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Ultimate Oscillator' is a tautology that restates the tool name without explaining what it does. It doesn't specify the action (e.g., 'calculate', 'retrieve', or 'analyze') or clarify that this is a technical indicator for financial analysis. While the name suggests it's related to technical indicators, the description adds no meaningful clarification beyond the name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With many sibling tools in the technicalIndicators category (like sma, ema, bbands, etc.), there's no indication of what makes the Ultimate Oscillator unique or when it should be preferred over other technical indicators. The description offers zero usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. The description offers no information on what the tool does (e.g., calculates a technical indicator), its output format, rate limits, authentication needs, or any side effects. It fails to compensate for the lack of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase that is overly concise to the point of under-specification. It does not front-load essential information and lacks any structure, failing to provide meaningful content beyond the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 6 parameters, no annotations, and no output schema, the description is completely inadequate. It does not explain the tool's purpose, behavior, or output, leaving significant gaps in understanding for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, documenting all 6 parameters clearly. The description adds no parameter information beyond what the schema provides, so it meets the baseline score of 3, as the schema carries the full burden of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Weighted Moving Average (WMA)' is a tautology that merely restates the tool name without specifying what the tool does. It does not mention the action (e.g., 'calculate' or 'retrieve') or the resource (e.g., 'stock data'), nor does it differentiate from sibling tools like 'technicalIndicators_sma' or 'technicalIndicators_ema', which are also moving average indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 does not mention any context, prerequisites, or comparisons to sibling tools (e.g., other technical indicators like SMA or EMA), leaving the agent with no usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but provides none. It doesn't indicate whether this is a read-only operation, what data source it queries (Alpha Vantage), what the response format might be, whether there are rate limits, or any other behavioral characteristics. The description is completely silent on how the tool behaves when invoked.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (just the name expanded), this is under-specification rather than effective conciseness. The single phrase doesn't provide enough information to be helpful. Good conciseness balances brevity with completeness, but here the description is so minimal it fails to communicate basic purpose or usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a technical indicator tool with 6 parameters (4 required) and no annotations or output schema, the description is completely inadequate. It doesn't explain what DEMA is, what it's used for, what data it returns, or how it differs from other technical indicators. The context signals show this is a moderately complex tool (6 parameters), but the description provides almost no contextual information to help an agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no parameter information beyond what's already in the structured schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Double Exponential Moving Average (DEMA)' is essentially a tautology that restates the tool name without specifying what the tool actually does. It doesn't state that this calculates or retrieves DEMA values, nor does it mention that this is a technical indicator for financial data analysis. While the name suggests it's related to technical indicators, the description adds no meaningful clarification about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus alternatives. There are many sibling technical indicator tools (ema, sma, tema, etc.), but the description doesn't help an agent understand when DEMA is appropriate versus other moving averages or technical indicators. No context about use cases, prerequisites, or comparisons is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, it offers no information on what the tool does behaviorally—such as whether it performs calculations, retrieves data, requires authentication, has rate limits, or returns specific formats. The description is purely a label with no operational details, failing to compensate for the lack of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase that is overly concise to the point of under-specification. It lacks structure (e.g., no introductory sentence explaining the tool's function) and does not front-load key information, making it inefficient for quick comprehension. While brief, it fails to convey necessary details, so it scores low for not earning its place with useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It does not explain what the tool returns (e.g., numerical values, charts, or time-series data), how results should be interpreted, or any dependencies on external data sources. The description alone is insufficient for an agent to understand the tool's full context and usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional meaning or context for parameters beyond what the schema provides (e.g., it does not explain how parameters like 'symbol' or 'interval' relate to the Hilbert Transform calculation). With high schema coverage, the baseline score is 3, as the description does not enhance parameter understanding but also does not detract from it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hilbert Transform - Dominant Cycle Period' restates the tool name with minimal elaboration, making it a tautology. It lacks a clear verb or action (e.g., 'calculate' or 'retrieve'), and does not specify what resource or data it operates on (e.g., stock data). While it hints at a technical indicator, it fails to distinguish this from sibling tools like 'technicalIndicators_htDcphase' or 'technicalIndicators_htSine', which are also Hilbert Transform-based indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 does not mention any context, prerequisites, or comparisons to sibling tools (e.g., other technical indicators like 'technicalIndicators_sma' or 'technicalIndicators_bbands'), leaving the agent with no information to make an informed selection among similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers no behavioral details. It does not disclose whether this is a read-only operation, what data sources it uses (e.g., Alpha Vantage), potential rate limits, authentication needs, or output characteristics (e.g., returns sine and lead sine values). The agent is left guessing about critical operational traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase 'Hilbert Transform - Sine Wave', which is overly concise to the point of under-specification. It lacks structure (e.g., no verb or context) and fails to front-load key information, making it inefficient rather than succinct. Every word earns its place, but too few words are used to be helpful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It does not explain what the tool returns (e.g., sine wave values for trend analysis), how it behaves, or when to use it, leaving significant gaps for an AI agent to infer functionality from the name and schema alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters (symbol, interval, datatype, month, series_type) with descriptions and enums. The description adds no parameter semantics beyond the schema, not even hinting at how parameters relate to the Hilbert Transform calculation. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hilbert Transform - Sine Wave' restates the tool name with minimal elaboration, providing only the technical indicator name without specifying what it does (e.g., calculates sine wave components for trend analysis) or what resource it operates on (e.g., stock data). It fails to distinguish from sibling tools like 'technicalIndicators_htPhasor' or 'technicalIndicators_htTrendline', leaving the purpose vague beyond the indicator category.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as other Hilbert Transform indicators (e.g., htPhasor, htTrendline) or general technical indicators. The description lacks context about its application (e.g., for cyclical analysis), prerequisites, or exclusions, offering no help in tool selection among the many siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description offers no behavioral information. It doesn't disclose whether this is a read-only operation, its computational complexity, rate limits, or what the output entails (e.g., time-series data). For a tool with no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is overly concise to the point of under-specification. A single phrase without sentence structure fails to convey essential information, making it inefficient rather than appropriately brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with no annotations and no output schema, the description is incomplete. It doesn't explain the tool's purpose, usage, or output, leaving the agent with insufficient context to invoke it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no parameter semantics beyond what's in the schema, meeting the baseline score of 3 where the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Minus Directional Movement (-DM)' restates the tool name with minimal elaboration, making it a tautology. It doesn't specify what the tool actually does (e.g., calculates a technical indicator for a given stock symbol) or distinguish it from sibling tools like 'technicalIndicators_plusDM' or 'technicalIndicators_minusDI'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about its application in technical analysis, prerequisites, or comparisons to sibling tools (e.g., 'technicalIndicators_plusDM' for positive directional movement).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description says nothing about what the tool actually does operationally (e.g., fetches data, performs calculations, returns values), what permissions or authentication might be required, rate limits, or what the output looks like. For a technical analysis tool with no annotation coverage, this is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - just 4 words. While this could be seen as efficient, it's arguably under-specified rather than appropriately concise. However, it's front-loaded with the core concept and contains no redundant information, earning a 4 rather than a 5 due to the borderline between conciseness and insufficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how the indicator is calculated or used, or provide any context beyond the indicator name. For a tool in this category, users need more guidance about output format and analytical purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds no parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hilbert Transform - Instantaneous Trendline' restates the tool name with minimal clarification. It identifies the technical indicator but doesn't specify what the tool actually does (e.g., calculates, retrieves, or analyzes this indicator). Compared to sibling tools like 'technicalIndicators_sma' or 'technicalIndicators_ema' that have similar naming patterns, it fails to distinguish its function beyond the indicator name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With many sibling technical indicator tools (e.g., technicalIndicators_sma, technicalIndicators_ema, technicalIndicators_bbands), there's no indication of what makes the Hilbert Transform Trendline unique or in what analytical contexts it should be preferred. No prerequisites, limitations, or comparison points are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers none. It doesn't indicate whether this is a read-only operation, what data source it queries (Alpha Vantage), potential rate limits, authentication requirements, or what the response contains. The description merely names the indicator without explaining its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (just 3 words) but this brevity comes at the cost of being under-specified rather than efficient. While it's front-loaded with the essential term, it lacks the necessary explanatory content that would make it genuinely helpful for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a technical indicator tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how the EMA calculation works, typical use cases in financial analysis, or how this differs from similar indicators. The description fails to compensate for the lack of structured metadata about the tool's behavior and output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly with descriptions and enums. The description adds no parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Exponential Moving Average (EMA)' is a tautology that restates the tool name with minimal expansion. It doesn't specify what the tool actually does (e.g., 'calculates the Exponential Moving Average for a given stock symbol'), nor does it distinguish this tool from sibling technical indicators like 'sma' or 'wma' beyond the different acronym.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 when EMA is appropriate compared to other technical indicators, what financial analysis contexts it's used for, or any prerequisites for usage. The sibling tool list shows many similar technical indicators, but the description offers no differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but fails entirely. It does not indicate whether this is a read-only operation, if it requires authentication, has rate limits, or what the output format or structure might be (e.g., time-series data). The description offers no behavioral traits beyond the name, making it inadequate for informed tool invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single phrase—with no wasted words. It is front-loaded and directly states the tool's focus, though this brevity comes at the cost of clarity and completeness. Every word earns its place by identifying the technical indicator, but the structure lacks elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is insufficiently complete. It does not explain what the tool returns (e.g., phasor components like in-phase and quadrature), how results are interpreted, or any dependencies on external data sources (e.g., Alpha Vantage). The description fails to provide enough context for effective use, especially compared to richer sibling tools in the list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the input schema itself. The description adds no additional meaning or context for parameters beyond what the schema provides (e.g., it does not explain how 'symbol' or 'interval' relate to the Hilbert Transform calculation). Since the schema handles parameter documentation adequately, the baseline score of 3 is appropriate, as the description neither compensates nor detracts.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hilbert Transform - Phasor Components' is tautological, essentially restating the tool name 'technicalIndicators_htPhasor' (where 'ht' likely stands for Hilbert Transform). It lacks a clear verb-action statement (e.g., 'calculate' or 'retrieve') and does not specify what resource or data it operates on (e.g., stock price data). While it hints at a financial technical indicator, the purpose remains vague without explicit functional context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 does not mention any specific use cases, prerequisites, or comparisons to sibling tools (e.g., other technical indicators like 'technicalIndicators_htSine' or 'technicalIndicators_htDcphase'), leaving the agent with no contextual clues for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 fails to describe what the tool does (e.g., returns calculated values, requires API keys, has rate limits, or outputs time-series data). The description only names the indicator, offering no insight into its operational behavior or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single phrase—which is efficient and front-loaded. However, it is overly terse to the point of under-specification, lacking necessary details for tool understanding. While not verbose, it fails to provide essential context, slightly reducing its effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It does not explain the tool's function, output format, or usage context, leaving significant gaps. The schema handles parameters well, but the description fails to address behavioral and contextual aspects, making it inadequate for agent guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing detailed parameter documentation. The description adds no parameter information beyond what the schema already specifies, such as explaining how parameters like 'time_period' or 'series_type' specifically apply to KAMA calculations. With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Kaufman Adaptive Moving Average (KAMA)' restates the tool name with minimal expansion, making it tautological. It does not specify the action (e.g., 'calculate' or 'retrieve') or distinguish this technical indicator tool from its many siblings (e.g., sma, ema, wma), which are all technical indicators with similar purposes. This lack of differentiation and verb specificity hinders clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With numerous sibling tools for technical indicators (e.g., sma, ema, bbands), there is no indication of KAMA's specific use cases, prerequisites, or comparisons, leaving the agent without direction for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but fails completely. It doesn't indicate whether this is a read-only operation, what data it returns, potential rate limits, or any side effects. For a financial data tool with 5 parameters, this lack of behavioral information is a critical gap that leaves the agent guessing about the tool's operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just 5 words, making it front-loaded and efficient. There's no wasted language or unnecessary elaboration. Every word serves to identify the technical indicator, though this brevity comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how to interpret the 'Trend vs Cycle Mode' output, or provide any context about the Hilbert Transform methodology. The agent would need to rely heavily on external knowledge to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional parameter information beyond what's already in the schema. According to the scoring rules, when schema coverage is high (>80%), the baseline score is 3 even with no parameter details in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hilbert Transform - Trend vs Cycle Mode' identifies the technical indicator but is vague about what the tool actually does. It names the indicator but doesn't specify the action (e.g., 'calculate', 'retrieve', or 'analyze') or what resource it operates on. Among sibling tools like 'technicalIndicators_sma' and 'technicalIndicators_ema', it doesn't clearly differentiate its specific purpose beyond the indicator name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 any context, prerequisites, or comparisons to sibling tools like 'technicalIndicators_htTrendline' or other trend indicators. There's no indication of when this specific Hilbert Transform mode is appropriate, leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description adds no behavioral context beyond the name. It doesn't disclose whether this is a read-only operation, its data source (e.g., Alpha Vantage), rate limits, authentication needs, or output format, which is critical for a tool with parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient phrase with no wasted words, making it front-loaded and easy to parse. It's appropriately sized for its limited content, though this conciseness comes at the cost of detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, no output schema, and no annotations), the description is incomplete. It lacks context on what the tool returns, how results are structured, or any behavioral traits, making it inadequate for effective agent use despite the detailed input schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents all 7 parameters. The description adds no additional meaning about parameters, such as explaining 'MAMA' specifics or parameter interactions, but the schema provides adequate details, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'MESA Adaptive Moving Average (MAMA)' states what the tool does by naming the specific technical indicator, but it's vague about the action (e.g., 'calculate' or 'retrieve') and doesn't distinguish it from sibling tools like 'technicalIndicators_sma' or 'technicalIndicators_ema'. It provides the indicator name but lacks a clear verb-resource pairing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives, such as other technical indicators in the sibling list. There's no mention of use cases, prerequisites, or comparisons, leaving the agent with no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'Midpoint price over period' gives no information about whether this is a read-only operation, what data source it uses (Alpha Vantage), rate limits, authentication requirements, or what the output looks like. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words. Every word earns its place by conveying the core function. There's no wasted language or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a technical indicator tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, how the midpoint is calculated, or provide context about the Alpha Vantage API. The description alone is insufficient for proper tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds no additional meaning about parameters beyond what's in the schema. The baseline of 3 is appropriate when the schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Midpoint price over period' states what the tool does (calculates midpoint price) but is vague about the specific resource and lacks differentiation from siblings. It doesn't specify this is a technical indicator for financial data or mention the Alpha Vantage context, making it less clear than it could be.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools in the technicalIndicators category (e.g., sma, ema, bbands), there's no indication of when midprice is appropriate or what distinguishes it from other indicators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. 'Retrieves' implies a read-only operation, but it doesn't specify critical behaviors such as data source, update frequency, rate limits, authentication requirements, or error handling. For a data retrieval tool with zero annotation coverage, this lack of behavioral context is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence ('Retrieves wheat prices.') that is front-loaded and wastes no words. It directly conveys the core purpose without unnecessary elaboration, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a data retrieval tool with no annotations and no output schema, the description is incomplete. It lacks details on return values (e.g., price units, timestamps), data freshness, and potential limitations. While the schema covers parameters well, the overall context for effective tool use is insufficient, especially without behavioral transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear enum values for 'interval' and 'datatype'. The description adds no parameter semantics beyond what the schema provides—it doesn't explain default values, implications of choosing 'json' vs. 'csv', or how the interval affects the data retrieved. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieves wheat prices' clearly states the verb ('retrieves') and resource ('wheat prices'), making the purpose immediately understandable. It distinguishes itself from sibling tools like commodities_corn or commodities_coffee by specifying wheat. However, it doesn't specify what kind of wheat prices (e.g., futures, spot, historical) or from which source, leaving some ambiguity compared to a perfect 5 score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like commodities_globalIndex or other commodities, nor does it specify use cases (e.g., for historical analysis vs. real-time data). Without any context on alternatives or prerequisites, the agent must infer usage solely from the tool name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Fetches' implies a read-only operation, but it doesn't disclose rate limits, authentication needs, error conditions, or what format/profile details are returned. For a data-fetching tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence with zero wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple single-parameter input, the description is incomplete. It doesn't explain what 'ETF profile details' include, how results are structured, or any behavioral traits like pagination or error handling. For a data-fetching tool, this leaves too much undefined for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage (the 'symbol' parameter is well-documented in the schema), so the baseline is 3. The description adds no parameter-specific information beyond what the schema already provides—it doesn't clarify if 'symbol' refers to ETF tickers specifically or any stock symbol, nor does it provide examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetches ETF profile details' states a clear verb ('fetches') and resource ('ETF profile details'), but it's somewhat vague about what specific details are included. It distinguishes from many siblings by focusing on ETFs rather than stocks, commodities, or other data types, but doesn't clearly differentiate from other fundamentalData tools like companyOverview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, when this tool is appropriate versus other ETF-related tools (none listed in siblings), or any contextual constraints. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'fetches' implies a read operation, it doesn't disclose important behavioral traits like whether this requires authentication, rate limits, what time period the data covers, whether it's real-time or historical, or what format the aggregated information takes. The description is too minimal for a tool that presumably returns complex financial data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a single-parameter tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a financial data tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'aggregated insider trading information' includes, the data format, time coverage, or any limitations. Given the complexity of insider trading data and the lack of structured output documentation, the description should provide more context about what the tool actually returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the single 'symbol' parameter well-documented in the schema. The description adds no additional parameter information beyond what's already in the schema ('for a given symbol'), so it meets the baseline score of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('aggregated insider trading information for a given symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'alphaIntelligence_newsSentiments' or 'alphaIntelligence_topGainersLosers' which are also Alpha Intelligence tools, so it misses the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (including other Alpha Intelligence tools and various financial data tools), there's no indication of when insider trading data is appropriate versus other data types like news sentiments or technical indicators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states what the tool does but doesn't describe how it behaves: there's no information about rate limits, authentication requirements, error handling, response format, or whether it's a read-only operation (though 'fetches' implies reading). For a tool with no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently communicates the core functionality without unnecessary words. It's appropriately sized and front-loaded, with every word earning its place. There's no redundancy or structural issues.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema, no annotations), the description is insufficiently complete. It doesn't explain what the output looks like (news articles with sentiment scores?), how results are structured, or any limitations (e.g., data freshness, source reliability). With no output schema and no annotations, the description should provide more context about the tool's behavior and results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with all parameters well-documented in the input schema. The description doesn't add any parameter-specific information beyond what's already in the schema (e.g., it doesn't explain relationships between parameters like 'tickersList' and 'topics'). According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('market news and sentiment data from Alpha Vantage'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from its many siblings (e.g., other Alpha Intelligence tools like 'insiderTransactions' or 'topGainersLosers'), which would require a 5. The description is specific but lacks sibling comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With numerous sibling tools available (e.g., for commodities, forex, technical indicators), there's no indication of when news and sentiment data is appropriate versus other data types. It mentions the data source but not the use case context, leaving the agent to infer usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Retrieves' implies a read-only operation, but it doesn't disclose important behavioral aspects: whether this requires API keys/authentication, rate limits, data sources, historical depth, or what the output looks like (structure, units, timestamps). For a financial data 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is inadequate. It doesn't explain what 'prices' means (e.g., spot prices, futures, averages), time coverage, data freshness, or response format. Given the complexity of financial data and lack of structured metadata, more context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters (interval, datatype) fully documented with enums and descriptions. The description adds no parameter information beyond what the schema provides, but since the schema does the heavy lifting, the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieves aluminum prices' clearly states the action (retrieves) and resource (aluminum prices), making the purpose immediately understandable. However, it doesn't differentiate from sibling commodity tools like commodities_copper or commodities_brentCrudeOil beyond specifying aluminum, which are similar price retrieval tools for different commodities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for different commodities and data types (e.g., commodities_copper, coreStock_daily), there's no indication of whether this is for historical prices, real-time data, or how it differs from other commodity tools beyond the specific metal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'retrieves' implies a read-only operation, the description doesn't mention authentication requirements, rate limits, data freshness, error conditions, or what the response looks like (structure, units, etc.). For a data retrieval tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple data retrieval tool and front-loads the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what format the prices are returned in (numerical values, time series, etc.), what time periods are available, whether it's real-time or historical data, or any limitations. The agent would need to guess or trial-and-error to understand the full behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with clear enum values and descriptions for both parameters. The description adds no parameter information beyond what's in the schema, which is acceptable given the high schema coverage. The baseline score of 3 reflects that the schema does the heavy lifting for parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieves Brent crude oil prices' clearly states the verb ('retrieves') and resource ('Brent crude oil prices'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'commodities_wtiCrudeOil' (which presumably retrieves WTI crude oil prices), nor does it mention the time interval or data format capabilities that differentiate it from other commodity tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'commodities_wtiCrudeOil' for comparison, nor does it indicate whether this is for historical or current prices, or any prerequisites for use. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Retrieves' implies a read-only operation, but it doesn't specify whether this is a real-time or historical query, if there are rate limits, authentication requirements, or what the output format looks like (beyond the datatype parameter). The description is minimal and misses key behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single three-word sentence that directly states the tool's purpose. There is no wasted language, and it's front-loaded with the essential information. Every word earns its place, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., price data structure, time series), behavioral aspects like error handling or data freshness, or how it fits within the broader commodity data context. For a tool with two parameters and no structured output documentation, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear enum values and descriptions for both parameters (interval and datatype). The description adds no additional parameter information beyond what's in the schema, so it meets the baseline of 3 for adequate coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieves copper prices' clearly states the verb ('retrieves') and resource ('copper prices'), making the purpose immediately understandable. It distinguishes from siblings like 'commodities_aluminum' by specifying the commodity type, though it doesn't explicitly contrast with other copper-related tools (none exist in the sibling list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. While the name implies it's for copper prices specifically, there's no mention of how it differs from other commodity tools (e.g., frequency, data source, or use cases). The description lacks any context about prerequisites or typical scenarios for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Retrieves' implies a read-only operation, but the description doesn't disclose important behavioral traits like whether this requires authentication, rate limits, data freshness, error conditions, or what format the prices come in (historical, current, futures). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, front-loading the essential purpose with zero wasted language. Every word earns its place, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what kind of corn prices are retrieved (spot, futures, historical), the data source, time ranges available, or what the return structure looks like. Given the complexity implied by the parameter enums and sibling tools, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters (interval and datatype) well-documented with enum values and descriptions. The description doesn't add any parameter information beyond what the schema provides, which is acceptable given the high schema coverage. The baseline of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieves corn prices' clearly states the verb ('retrieves') and resource ('corn prices'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like commodities_wheat or commodities_sugar, which likely have similar retrieval patterns for different commodities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for different commodities (wheat, sugar, coffee, etc.) and data types (coreStock, forex, crypto), there's no indication of when corn price retrieval is appropriate versus other commodity or financial data tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Retrieves' implies a read-only operation, but the description doesn't disclose important behavioral aspects like whether authentication is required, rate limits, data sources, freshness of prices, or what format/scope the returned prices cover (e.g., historical, current, regional).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just three words, front-loading the essential purpose without any wasted text. Every word earns its place, making it highly efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a data retrieval tool. It doesn't explain what the returned prices look like (e.g., time series, single value), units, or data quality aspects. While concise, it leaves too many contextual gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters (interval and datatype) with enums and descriptions. The description adds no parameter information beyond what's in the schema, maintaining the baseline score of 3 for adequate schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Retrieves') and resource ('cotton prices'), making it immediately understandable. It distinguishes itself from other commodity tools by specifying cotton, but doesn't explicitly differentiate from siblings like 'commodities_coffee' or 'commodities_wheat' beyond the commodity type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for different commodities and data types (e.g., 'commodities_coffee', 'coreStock_daily'), there's no indication of when cotton price retrieval is appropriate versus other commodity or financial data tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states this is a retrieval operation, implying read-only behavior, but doesn't disclose any behavioral traits like authentication requirements, rate limits, data freshness, or what the global index actually contains. For a financial data tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without any wasted words. It's perfectly front-loaded with the essential information, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the global commodity index represents, what data it returns, or how it differs from the many specific commodity tools. Given the complexity of financial data and the rich sibling tool ecosystem, more context is needed for proper tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with clear enum values and descriptions for both parameters. The description doesn't add any parameter semantics beyond what's already in the schema, but with complete schema coverage, the baseline score of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieves') and the resource ('global commodity index'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its many sibling commodity tools (like commodities_aluminum, commodities_brentCrudeOil, etc.), which all appear to retrieve specific commodity data rather than a global index.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With numerous sibling tools for specific commodities and other data types, there's no indication of when a global index is preferable to individual commodity data or how this relates to other economic indicators in the server.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Retrieves' implies a read-only operation, but it doesn't disclose behavioral traits like whether this requires authentication, rate limits, data freshness, error handling, or what the output looks like (since no output schema exists). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose ('Retrieves natural gas prices'), making it immediately clear. Every word earns its place, and there's no unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a data retrieval tool with no annotations and no output schema), the description is incomplete. It doesn't explain what the tool returns (e.g., price values, timestamps, units), any prerequisites, or how it fits within the broader commodity data context. With 100% schema coverage but missing behavioral and output details, it falls short.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('interval' and 'datatype') fully documented in the schema with enums and descriptions. The description adds no parameter semantics beyond what the schema provides, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'retrieves' and the resource 'natural gas prices', making the purpose immediately understandable. It distinguishes itself from siblings like 'commodities_aluminum' or 'commodities_coffee' by specifying the commodity type. However, it doesn't specify what kind of prices (e.g., spot, futures, historical) or from which source, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for different commodities (e.g., 'commodities_brentCrudeOil', 'commodities_copper'), there's no indication of whether this is for current prices, historical data, or how it differs from other commodity tools. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Retrieves' implies a read-only operation, but it doesn't disclose important behavioral traits like whether this requires authentication, rate limits, data freshness, source of the prices, or what format/scope the returned prices cover. The description is too minimal for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, with zero wasted language. It's front-loaded with the core purpose and contains no unnecessary elaboration, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'sugar prices' means (e.g., spot prices, futures, geographic scope), the data source, or what the return structure looks like. For a data retrieval tool with no structured output documentation, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('interval' and 'datatype') well-documented with enums and descriptions. The description adds no parameter information beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieves sugar prices' clearly states the verb ('Retrieves') and resource ('sugar prices'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'commodities_coffee' or 'commodities_corn' beyond specifying the commodity type, which is somewhat inherent in the tool name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for different commodities and data types, there's no indication of whether this is for historical prices, real-time data, or how it differs from other commodity tools in the server.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool retrieves data, implying a read-only operation, but does not specify details like data sources, update frequency, rate limits, authentication needs, or error handling. This lack of information leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not cover behavioral aspects like data retrieval specifics, potential limitations, or return value details, which are crucial for a data-fetching tool. The high schema coverage helps with parameters, but overall context is insufficient for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear enum values for 'interval' and 'datatype'. The description does not add any parameter semantics beyond what the schema provides, such as explaining the implications of choosing different intervals or formats. Since schema coverage is high, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('West Texas Intermediate (WTI) crude oil prices'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'commodities_brentCrudeOil', which retrieves a different type of crude oil price, leaving some ambiguity in sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as other commodity tools or data formats. There is no mention of use cases, prerequisites, or comparisons with siblings like 'commodities_brentCrudeOil' or tools with different intervals, leaving the agent without contextual usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'fetches' implies a read operation, it doesn't mention rate limits, authentication requirements, data freshness, error conditions, or response format details. For a data-fetching tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple data-fetching tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the returned time series data contains (e.g., OHLC values, volume), how it's structured, or any limitations. The agent would need to guess about the response format and data completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents all three parameters. The description doesn't add any parameter-specific information beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('daily time series data for a stock symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like coreStock_intraday or coreStock_weekly, which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like coreStock_intraday, coreStock_weekly, or coreStock_dailyAdjusted. It doesn't mention prerequisites, limitations, or typical use cases for daily data versus other frequencies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 insight. It states it 'fetches' data (implies read-only) but doesn't mention rate limits, authentication requirements, data freshness, or what 'adjusted' entails (e.g., splits/dividends). For a data-fetching tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is insufficient for a data-fetching tool. It doesn't explain what 'adjusted' means, the structure of returned data, potential errors, or usage constraints. With rich sibling tools and no structured support, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds no parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('daily adjusted time series data for a stock symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from siblings like 'coreStock_daily' (unadjusted) or 'coreStock_weeklyAdjusted', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'coreStock_daily' (unadjusted daily data) or other frequency-adjusted tools (e.g., 'coreStock_weeklyAdjusted'). The description lacks any context about use cases, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states it 'fetches' data, implying a read-only operation, but doesn't mention any behavioral traits like rate limits, authentication requirements, data freshness, error conditions, or pagination. For a data-fetching tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for its function, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the output looks like (e.g., time series format, data points), any usage constraints, or how it relates to sibling tools. For a data-fetching tool with rich parameters but no structured output or behavioral annotations, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 7 parameters with descriptions, enums, defaults, and requirements. The description adds no additional parameter semantics beyond what's in the schema, but since the schema is comprehensive, the baseline score of 3 is appropriate as the description doesn't need to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('intraday time series data for a stock symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'coreStock_daily' or 'crypto_intraday', which would require mentioning it's specifically for stocks (not crypto) and intraday (not daily/weekly/monthly).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools available (e.g., coreStock_daily, crypto_intraday, forex_intraday), the description doesn't indicate this is for stock-specific intraday data or suggest when to choose it over other timeframes or asset classes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions fetching data but lacks details on behavioral traits such as rate limits, authentication requirements, data freshness, error handling, or pagination. This leaves significant gaps for an agent to understand operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste. It is front-loaded and efficiently conveys the core purpose without unnecessary elaboration, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial data tools and lack of annotations or output schema, the description is incomplete. It doesn't address key contextual aspects like data format details, potential errors, or how this tool fits among siblings, leaving the agent with insufficient information for robust use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters ('symbol' and 'datatype'). The description adds no additional meaning beyond what the schema provides, such as examples for 'symbol' beyond 'IBM' or implications of choosing 'csv' over 'json'. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('monthly time series data for a stock symbol'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'coreStock_daily' or 'coreStock_monthlyAdjusted', which would require mentioning the time granularity or adjustment differences to achieve a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (e.g., 'coreStock_daily', 'coreStock_monthlyAdjusted', 'coreStock_weekly'), there is no mention of context, prerequisites, or comparisons to help an agent choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('fetches') but doesn't mention whether this requires authentication, has rate limits, returns real-time or delayed data, what the quote includes (price, volume, etc.), or potential error conditions. For a financial data tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized for a simple data-fetching tool and front-loads the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what a 'global quote' contains, the data source, latency considerations, or error handling. Given the financial context and many sibling alternatives, more contextual information would help an agent use this tool appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for both parameters ('symbol' and 'datatype'). The description doesn't add any meaningful parameter semantics beyond what's already in the schema (e.g., it doesn't explain symbol format requirements or datatype implications). This meets the baseline expectation when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('fetches') and resource ('global quote for a single stock symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'coreStock_bulkQuotes' (which handles multiple symbols) or 'coreStock_daily' (which provides time series data), missing an opportunity for sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (e.g., 'coreStock_bulkQuotes' for multiple symbols, 'coreStock_daily' for historical data, 'coreStock_search' for symbol lookup), there's no indication of appropriate contexts, prerequisites, or exclusions for this specific quote-fetching tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool 'searches for stock symbols,' which implies a read-only operation, but doesn't disclose behavioral traits like whether it requires authentication, rate limits, pagination, error handling, or the format/scope of results (e.g., partial matches, case sensitivity). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core purpose, making it easy to parse quickly. Every word earns its place, achieving optimal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a search tool with no output schema and no annotations), the description is incomplete. It doesn't explain what the search returns (e.g., symbol names, companies, match criteria), potential limitations, or how it fits among the many stock-related sibling tools. For a tool without structured output or behavioral annotations, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (keywords and datatype) with descriptions and enum values. The description adds no additional meaning beyond what's in the schema, such as examples of keyword usage or implications of the datatype choice. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('searches for') and resource ('stock symbols matching keywords'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like coreStock_bulkQuotes or coreStock_quote, which might also involve stock data retrieval, but the search functionality is distinct enough for basic clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for stock data (e.g., coreStock_quote, coreStock_daily), there's no indication that this is specifically for symbol lookup by keywords rather than price or time-series data. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'fetches' which implies a read operation, but doesn't disclose any behavioral traits like rate limits, authentication requirements, data freshness, error handling, or response format details beyond what's in the input schema. This leaves significant gaps for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without any wasted words. It's appropriately sized for a straightforward data retrieval tool and is front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the weekly time series data includes (e.g., OHLC values, volume), how far back data goes, whether it's adjusted, or what the response structure looks like. For a data retrieval tool with no structured output documentation, this leaves too many unanswered questions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters (symbol and datatype). The description doesn't add any meaningful parameter semantics beyond what's in the schema, such as symbol validation rules or datatype implications. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('weekly time series data for a stock symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'coreStock_daily' or 'coreStock_weeklyAdjusted', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools available (e.g., coreStock_daily, coreStock_weeklyAdjusted, coreStock_monthly), the description offers no context about frequency selection, data adjustments, or specific use cases for weekly data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it 'fetches' data (implying read-only), but doesn't disclose behavioral traits like rate limits, authentication requirements, data freshness, error conditions, or response format details beyond the datatype parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose with zero wasted words. It's appropriately sized for a simple data-fetching tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'adjusted' means (e.g., for splits/dividends), the time range covered, response structure, or error handling. For a financial data tool with many similar siblings, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters (symbol and datatype). The description adds no additional parameter semantics beyond what's already in the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('weekly adjusted time series data for a stock symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'coreStock_weekly' (unadjusted) or 'coreStock_dailyAdjusted', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for stock data (e.g., daily, monthly, adjusted vs. unadjusted), there's no indication of appropriate contexts, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'fetches' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, what happens with invalid inputs, or the format of the returned data. The mention of 'realtime' is helpful but vague without context on latency or update frequency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality. Every word contributes meaning, with no wasted text or redundancy. The example in parentheses is appropriately brief and illustrative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is incomplete. It doesn't address key contextual aspects like authentication requirements, error handling, rate limits, or the structure of the returned exchange rate data. Given the complexity of financial data tools and the lack of structured metadata, more behavioral and operational context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear parameter descriptions in the input schema. The description adds minimal value beyond the schema by providing an example ('e.g., BTC to USD'), but doesn't explain parameter semantics like valid currency symbols, case sensitivity, or format requirements. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('fetches') and resource ('realtime exchange rate for a cryptocurrency pair'), and provides an example ('e.g., BTC to USD'). However, it doesn't explicitly differentiate from sibling tools like 'crypto_daily' or 'crypto_intraday', which might also provide exchange rate data but with different timeframes or formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (e.g., 'crypto_daily', 'crypto_intraday', 'forex_exchangeRates'), there's no indication of whether this is the preferred tool for realtime rates, what distinguishes it from other crypto tools, or any prerequisites for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the action ('fetches') but doesn't disclose behavioral traits like rate limits, authentication requirements, data freshness, error handling, or response format details. For a data-fetching tool with no annotation coverage, this leaves significant gaps in understanding its operational characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded with the core purpose, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial data tools and the absence of both annotations and output schema, the description is insufficient. It doesn't explain what the returned time series data looks like, how historical data is handled, or any limitations. For a tool with 5 parameters and no structured output documentation, more contextual information would be needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema descriptions (e.g., explaining what 'symbol' or 'interval' mean in practice). Baseline 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('fetches') and resource ('intraday time series data for a cryptocurrency'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'crypto_daily' or 'forex_intraday', which would require mentioning the time granularity or asset class distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools for different timeframes (e.g., crypto_daily, crypto_weekly) and asset classes (e.g., forex_intraday), there's no indication of appropriate contexts, prerequisites, or exclusions for this intraday crypto data tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states 'fetches' which implies a read operation, but doesn't cover important aspects like rate limits, authentication requirements, data freshness, error handling, or response format details. For a data-fetching tool with no annotation support, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a straightforward data-fetching tool and front-loads the core functionality without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the weekly time series data contains (e.g., OHLC values, volume), how results are structured, or any behavioral constraints. Given the complexity of financial data and the lack of structured metadata, the description should provide more context about the operation and its results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain what 'weekly time series' includes or provide examples beyond the basic fetch action). This meets the baseline expectation when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('weekly time series data for a cryptocurrency'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this tool from its sibling crypto tools (like crypto_daily, crypto_weeklyAdjusted, or crypto_monthly), which would require mentioning what makes 'weekly' data unique or when to prefer it over other timeframes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (e.g., crypto_daily, crypto_weeklyAdjusted, forex_weekly), there's no indication of when weekly crypto data is appropriate compared to daily, adjusted, or other asset classes. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Retrieves' implies a read-only operation, but it doesn't disclose any behavioral traits like rate limits, authentication requirements, data freshness, or potential errors. For a data-fetching tool with no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple data retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a data retrieval tool with no annotations and no output schema), the description is incomplete. It doesn't explain what the returned CPI data includes (e.g., time series, values, metadata), how it's structured, or any usage constraints. For a tool fetching economic data, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters (interval and datatype) with enums and defaults. The description adds no parameter information beyond what's in the schema, meeting the baseline of 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('US Consumer Price Index (CPI) data'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'economicIndicators_inflation' or 'economicIndicators_realGDP', which is why it doesn't reach a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools in the economicIndicators category (e.g., inflation, realGDP, unemploymentRate), there's no indication of when CPI data is specifically needed or how it differs from other economic indicators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'Retrieves' implies a read operation, it doesn't mention important aspects like data sources, update frequency, rate limits, authentication requirements, or error handling. This leaves significant gaps for an AI agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple data retrieval tool and is perfectly front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the inflation data includes (e.g., time periods, metrics like CPI), how it's formatted, or what the response looks like. Given the complexity of economic data and lack of structured information, more context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'datatype' fully documented in the schema (including enum values and default). The description adds no additional parameter information beyond what the schema provides, which is acceptable given the high schema coverage, resulting in the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('US inflation rate data'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'economicIndicators_cpi' (which might retrieve similar data), so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools in the economicIndicators category (e.g., cpi, unemploymentRate, realGDP), the description offers no context about what makes this tool distinct or when it should be preferred over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Retrieves' which implies a read operation, but doesn't disclose any behavioral traits like data freshness, source, rate limits, authentication requirements, or what the response contains. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a simple data retrieval tool and front-loads the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what data is returned, in what format, with what granularity, or from what time period. While concise, it leaves too many unanswered questions about what the tool actually provides.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, fully documenting the single 'datatype' parameter with enum values and default. The description adds no parameter information beyond what's in the schema, so it meets the baseline score of 3 where schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('US nonfarm payroll data'), making the purpose immediately understandable. It distinguishes from many siblings by specifying the economic indicator type, though it doesn't explicitly differentiate from other economicIndicators_* tools like 'economicIndicators_unemploymentRate' or 'economicIndicators_cpi' beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With multiple economic indicator tools available (e.g., economicIndicators_cpi, economicIndicators_unemploymentRate), there's no indication of what makes nonfarm payroll data distinct or when it's most appropriate to retrieve this specific dataset.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Retrieves' implies a read-only operation, the description doesn't mention any behavioral traits like data freshness, source, rate limits, authentication requirements, or what format the data comes in beyond the parameter schema. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise - a single sentence that states exactly what the tool does with zero wasted words. It's front-loaded with the core functionality and doesn't include any unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is inadequate. It doesn't explain what the returned data looks like, what time periods are covered, data granularity, or any limitations. With 100% schema coverage but no output schema, the description should compensate by explaining the response format and content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'datatype' fully documented in the schema with enum values and default. The description adds no parameter information beyond what's already in the structured schema, so it meets the baseline expectation but doesn't provide additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('US Real GDP per Capita data'), making the purpose immediately understandable. However, it doesn't distinguish this tool from similar economic indicator tools like 'economicIndicators_realGDP' or 'economicIndicators_cpi', which would require sibling differentiation for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (including other economic indicators like 'economicIndicators_realGDP'), there's no indication of what makes this specific per capita data unique or when it should be preferred over other GDP or economic metrics.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the retrieval action without disclosing behavioral traits like data freshness, source, rate limits, authentication needs, or error handling. For a data-fetching tool, this lack of operational context is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the retrieved data includes (e.g., time series, metrics), how it's structured, or any prerequisites. For a tool in a complex server with many siblings, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'datatype' fully documented in the schema. The description adds no parameter-specific information beyond what the schema provides, so it meets the baseline of 3 without compensating or adding extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieves') and resource ('US retail sales data'), providing a specific purpose. However, it doesn't differentiate from sibling tools like 'economicIndicators_cpi' or 'economicIndicators_durableGoodsOrders' that also retrieve economic data, leaving room for confusion about when to choose this specific indicator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. With many sibling tools for economic indicators (e.g., CPI, GDP, unemployment), there's no indication of what makes retail sales data unique or when it's preferred, leaving the agent to guess based on context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that data is retrieved, implying a read-only operation, but fails to mention any behavioral traits like rate limits, authentication requirements, data freshness, or error handling. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial data retrieval, no annotations, and no output schema, the description is incomplete. It lacks details on return format, data structure, potential errors, or usage constraints, leaving significant gaps for an agent to understand how to effectively use this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with clear enums and defaults for all parameters (interval, maturity, datatype). The description adds no additional semantic context beyond implying 'various maturities,' which is already covered by the schema's enum. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieves') and resource ('US Treasury yield curve data for various maturities'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'economicIndicators_federalFundsRate' or 'economicIndicators_realGDP', which might also retrieve economic data, though the specific focus on Treasury yields is reasonably distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as other economic indicators or financial data tools in the sibling list. It lacks any mention of context, prerequisites, or exclusions, leaving the agent to infer usage based solely on the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'Retrieves' implies a read-only operation, it doesn't specify data sources, update frequency, historical range, rate limits, authentication needs, or error conditions. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple data retrieval tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what data is returned (e.g., time series, latest value, metadata), format details beyond the parameter, or how to interpret results. Given the complexity of economic data and lack of structured guidance, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the single 'datatype' parameter with enum values and default. The description adds no parameter information beyond what's in the schema, so it meets the baseline of 3 for adequate coverage without adding value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Retrieves') and resource ('US unemployment rate data'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'economicIndicators_cpi' or 'economicIndicators_realGDP' beyond specifying the unemployment rate, leaving some ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools in the economicIndicators category (e.g., CPI, GDP, inflation), there's no indication of when unemployment rate data is appropriate versus other economic metrics, nor any mention of prerequisites or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 insight. It states 'Fetches' implying a read operation, but doesn't disclose critical traits like rate limits, authentication needs, data latency, or error handling. For a data-fetching 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core purpose, making it easy to parse quickly, and every part of the sentence contributes essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (fetching financial time series data), lack of annotations, and no output schema, the description is insufficient. It doesn't explain the return format (e.g., time series structure), data granularity, or potential limitations, leaving the agent under-informed for proper invocation and result interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters (from_symbol, to_symbol, outputsize, datatype) with clear descriptions and enums. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline score of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetches') and resource ('daily time series data for a Forex pair'), making the purpose immediately understandable. It distinguishes from siblings like forex_intraday or forex_weekly by specifying 'daily' frequency, though it doesn't explicitly contrast with forex_exchangeRates which might serve different data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools (e.g., forex_intraday for higher frequency, forex_exchangeRates for spot rates) or contextual factors like data freshness or use cases, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions 'realtime exchange rate', which implies current data, but doesn't specify data sources, accuracy, rate limits, authentication needs, or error handling. For a data-fetching tool with zero annotation coverage, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes a helpful example, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of financial data tools and the lack of annotations and output schema, the description is incomplete. It doesn't address return values, error cases, data freshness, or how it differs from sibling tools. This leaves the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear parameter descriptions in the input schema. The description adds minimal value beyond the schema by implying currency pair usage with an example, but doesn't provide additional syntax, format details, or constraints. This meets the baseline score when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Fetches') and resource ('realtime exchange rate for a currency pair'), and provides an example ('e.g., EUR to USD'). However, it doesn't explicitly distinguish this tool from sibling tools like 'crypto_exchangeRates' or other forex tools (e.g., 'forex_daily'), which might offer similar functionality with different timeframes or data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'forex_daily' or 'crypto_exchangeRates', nor does it specify prerequisites, constraints, or typical use cases. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'fetches' implies a read-only operation, the description doesn't address important behavioral aspects like rate limits, authentication requirements, data freshness, error conditions, or what the response structure looks like. For a data-fetching 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a straightforward data-fetching tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the monthly time series data looks like, what time periods are available, whether there are data limitations, or how to interpret results. For a data retrieval tool with no structured output documentation, the description should provide more context about the returned data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('monthly time series data for a Forex pair'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'forex_daily', 'forex_weekly', or 'forex_intraday', which would require mentioning the specific time granularity differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With multiple sibling tools for different Forex timeframes (daily, weekly, intraday) and other related tools, there's no indication of when monthly data is appropriate or what distinguishes this from other frequency options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Premium endpoint,' indicating potential authentication or subscription needs, but lacks details on rate limits, error handling, data freshness, or output format. For a financial data tool with no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short phrases: 'Fetches balance sheet data (annual/quarterly). Premium endpoint.' Every word serves a purpose—specifying action, resource, granularity, and access level—with zero waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a financial data tool with potential complexity, the description is incomplete. It lacks details on response structure, error cases, authentication requirements, and how it differs from siblings. 'Premium endpoint' is a start but insufficient for full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'symbol' clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as symbol format examples or validation rules. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Fetches balance sheet data (annual/quarterly).' It specifies the verb ('fetches'), resource ('balance sheet data'), and temporal granularity. However, it doesn't explicitly differentiate from sibling tools like 'fundamentalData_incomeStatement' or 'fundamentalData_cashFlow', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance with 'Premium endpoint,' hinting at access restrictions, but offers no explicit when-to-use advice, alternatives, or exclusions. No comparison to sibling tools like 'fundamentalData_companyOverview' or 'fundamentalData_earnings' is provided, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Premium endpoint,' hinting at potential access restrictions or costs, but doesn't specify rate limits, authentication needs, error conditions, or what 'overview details' entail (e.g., fields returned, data freshness). This is insufficient for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first sentence. The second sentence adds useful context ('Premium endpoint') without redundancy. It could be slightly more structured but avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'company overview details' include (e.g., financial metrics, company description), potential limitations, or response format. For a tool fetching fundamental data, this leaves significant gaps for an agent to understand its behavior and outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, fully documenting the single 'symbol' parameter. The description adds no additional parameter semantics beyond what the schema provides, such as format constraints or examples. This meets the baseline score of 3 since the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetches') and resource ('company overview details'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'fundamentalData_balanceSheet' or 'fundamentalData_incomeStatement' that also fetch fundamental data, leaving ambiguity about what specific overview details are provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 prerequisites (e.g., needing a valid stock symbol), exclusions, or comparisons to sibling tools like 'coreStock_quote' or 'fundamentalData_etfProfile', leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'fetches historical dividend data' implies a read-only operation, it doesn't specify important behavioral aspects like data format, time range coverage, frequency of updates, rate limits, authentication requirements, or error conditions. The description is minimal and lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that gets straight to the point with no wasted words. It's front-loaded with the core functionality and uses clear, direct language without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the dividend data includes (amounts, dates, types), the historical range available, the format of returned data, or any limitations. Given the complexity of financial data and the lack of structured output information, the description should provide more operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'symbol' clearly documented in the schema as 'The stock symbol (e.g., "IBM")'. The description adds no additional parameter information beyond what's already in the schema, which is acceptable given the complete schema coverage but doesn't provide extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('historical dividend data for a symbol'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'fundamentalData_earnings' or 'fundamentalData_splits' which also fetch historical financial data for symbols, leaving room for ambiguity in tool selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools fetching different types of financial data (earnings, splits, balance sheets, etc.), there's no indication of when dividends specifically are needed or what distinguishes this tool from other fundamental data tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'Premium endpoint' which suggests potential authentication or subscription requirements, but doesn't specify rate limits, data freshness, pagination, error conditions, or what 'earnings data' actually includes beyond annual/quarterly granularity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just two brief phrases. While efficient, it might be too minimal given the lack of annotations and sibling tool context. Every word earns its place, but more context could be beneficial.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'earnings data' includes (EPS, revenue, guidance?), doesn't specify time periods covered, doesn't mention data format or structure, and provides minimal behavioral context despite being a data-fetching tool in a crowded namespace.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100% and clearly documents the single required 'symbol' parameter. The description adds no additional parameter semantics beyond what the schema already provides, so it meets the baseline expectation when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches earnings data with annual/quarterly granularity, which is a specific verb+resource combination. However, it doesn't distinguish itself from sibling tools like fundamentalData_incomeStatement or fundamentalData_cashFlow that might also provide financial data, so it doesn't fully differentiate from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like fundamentalData_incomeStatement or fundamentalData_companyOverview. The mention of 'Premium endpoint' hints at potential access restrictions but doesn't provide explicit usage context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 insight. It mentions 'CSV endpoint' which hints at the response format, but doesn't disclose whether this is a read-only operation, potential rate limits, authentication requirements, data freshness, or what happens when no data is found. For a data-fetching 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and includes the useful 'CSV endpoint' detail. Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the CSV response contains, how results are structured, whether pagination exists, or what happens with invalid inputs. The 'CSV endpoint' hint is helpful but insufficient for an agent to properly interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters (symbol and horizon with enum values). The description adds no parameter-specific information beyond what's in the schema - it doesn't explain the relationship between parameters, provide examples, or clarify edge cases. Baseline 3 is appropriate when schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Fetches') and resource ('upcoming earnings calendar') with the additional detail of 'CSV endpoint' indicating the format. It distinguishes from siblings like fundamentalData_earnings (which likely provides historical earnings data) by specifying 'upcoming' and 'calendar', but doesn't explicitly contrast with fundamentalData_ipoCalendar which is another calendar-type tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 when to choose this over fundamentalData_earnings for earnings data, or how it differs from fundamentalData_ipoCalendar for calendar data. There's no context about prerequisites, timing considerations, or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions 'Premium endpoint,' which implies potential access restrictions or costs, but lacks details on rate limits, authentication needs, data formats, or error handling. This leaves significant gaps for a tool that fetches financial data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, stating the core functionality in a single sentence. However, it could be more structured by separating the premium endpoint note for clarity, but it remains efficient with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of fetching financial data, no annotations, and no output schema, the description is incomplete. It lacks details on return values (e.g., data structure, fields), error cases, or behavioral traits like pagination or caching, making it inadequate for full agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'symbol' clearly documented. The description does not add any additional meaning beyond the schema, such as explaining symbol formats or constraints, so it meets the baseline for high schema coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as fetching income statement data with annual/quarterly frequency, which is a specific verb (fetches) and resource (income statement data). It distinguishes from siblings like fundamentalData_balanceSheet or fundamentalData_cashFlow by specifying the type of financial statement, though it does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as other fundamental data tools like fundamentalData_balanceSheet or fundamentalData_cashFlow. It mentions it is a 'Premium endpoint,' which hints at access restrictions but does not specify usage contexts or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'CSV endpoint', hinting at a data format, but doesn't disclose critical behaviors like rate limits, authentication needs, pagination, or error handling. For a data-fetching tool with no annotation coverage, this leaves significant gaps in understanding how it operates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. 'CSV endpoint' adds useful context without verbosity. However, it could be slightly more structured by explicitly separating purpose from format, but it remains appropriately sized with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool with 3 parameters. It lacks details on return format (beyond 'CSV'), error conditions, or usage context. For a data-fetching tool in a financial API, this leaves the agent under-informed about how to interpret results or handle edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters (symbol, date, state). The description adds no additional parameter semantics beyond what's in the schema, such as explaining how filters combine or CSV format specifics. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('fetches') and resource ('active or delisted symbols'), making the purpose understandable. It distinguishes from siblings by specifying it's about listing status rather than financial data or indicators. However, it doesn't explicitly differentiate from other fundamentalData tools like companyOverview or earnings, which slightly limits clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 mentions 'CSV endpoint' but doesn't explain if this is for bulk data, historical tracking, or integration purposes. No exclusions or prerequisites are stated, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'fetches' implies a read operation, it doesn't disclose behavioral traits like whether this requires authentication, rate limits, what time period the data covers, or the format/structure of returned data. The description is minimal and lacks essential context for a data-fetching tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized for a simple tool and front-loads the key information (fetches historical stock split data).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'historical' means (time range, frequency), what data format to expect, or any limitations/requirements. Given the complexity of financial data tools and lack of structured context, this description leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'for a symbol' which aligns with the single parameter in the schema. With 100% schema description coverage (the schema fully documents the 'symbol' parameter), the description adds minimal value beyond what's already in the structured data. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('fetches') and resource ('historical stock split data for a symbol'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'fundamentalData_dividends' or 'fundamentalData_earnings', which also fetch historical financial data for symbols.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools fetching different types of financial data (e.g., dividends, earnings, balance sheets), there's no indication that this tool is specifically for stock splits rather than other fundamental data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Premium endpoint,' which suggests potential authentication or rate-limiting needs, but doesn't detail these aspects, response format, error handling, or data scope. This leaves significant gaps for a data-fetching tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences that are front-loaded and waste no words. Every part ('Fetches historical options chain data. Premium endpoint.') earns its place by stating purpose and a key behavioral note.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (fetching financial data with 3 parameters) and lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error cases, or detailed behavioral traits, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, thoroughly documenting all parameters. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 without compensating for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('fetches') and resource ('historical options chain data'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from its sibling 'optionsData_realtimeOptions' beyond the 'historical' qualifier, which is implied but not contrasted.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'optionsData_realtimeOptions' or other data-fetching tools. The mention of 'Premium endpoint' hints at potential access restrictions but doesn't clarify usage context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions 'premium endpoint,' hinting at potential cost or access restrictions, but fails to describe critical behaviors like rate limits, authentication requirements, data freshness, or response format details. This leaves significant gaps for a tool fetching realtime financial data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—just two short sentences that directly state the tool's function and key characteristic. Every word earns its place with no redundancy or unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of realtime options data and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like rate limits or authentication, doesn't explain the output structure, and offers minimal context about when to use it. For a premium financial data tool, this leaves too many unknowns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional parameter semantics beyond what's in the schema, such as explaining the relationship between 'symbol' and 'contract' or clarifying data format implications. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('realtime options chain data'), making the purpose immediately understandable. It distinguishes this as a 'premium endpoint,' which differentiates it from potential free alternatives, though it doesn't explicitly contrast with sibling tools like 'optionsData_historicalOptions'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 mentions it's a 'premium endpoint,' which implies cost or access restrictions, but doesn't specify when to choose realtime over historical options data or how it differs from other options-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states what the tool calculates but doesn't describe how it behaves: no information on output format (though datatype parameter hints at JSON/CSV), rate limits, authentication needs, error handling, or whether it's a read-only operation. For a tool with 6 parameters and no annotations, this leaves significant gaps in understanding its operational characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for what it communicates and is front-loaded with the core functionality. Every word earns its place in defining this technical indicator.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a technical indicator with 6 parameters, no annotations, and no output schema, the description is incomplete. It explains what TRIX is but doesn't provide context about typical use cases, interpretation of results, or how it fits within the broader technical analysis toolkit. For a tool that likely returns numerical indicator values, the absence of output schema means the description should at least hint at the return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. It doesn't explain how parameters like 'time_period' or 'series_type' specifically relate to TRIX calculation. Baseline 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the '1-day Rate Of Change (ROC) of a Triple Smooth EMA (TRIX)', which is a specific technical indicator. It distinguishes itself from siblings like 'technicalIndicators_rocr' (Rate of Change) and 'technicalIndicators_tema' (Triple Exponential Moving Average) by combining both concepts. However, it doesn't explicitly mention it's for financial time series data, which is implied but could be more explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling technical indicators (e.g., 'technicalIndicators_ema', 'technicalIndicators_rocr'), there's no indication of when TRIX is preferred for momentum analysis over other indicators. It also doesn't mention prerequisites like needing historical price data or typical use cases in technical analysis.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Retrieves' implies a read-only operation, but it doesn't specify whether this is a real-time or historical data source, if there are rate limits, authentication requirements, or what the output format looks like (beyond the 'datatype' parameter). For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence ('Retrieves coffee prices.') that is front-loaded with the core purpose. There is no wasted verbiage or redundancy, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 parameters, no nested objects) and high schema coverage (100%), the description is minimally adequate. However, with no annotations and no output schema, it lacks details on behavioral traits (e.g., data freshness, error handling) and return values, which are important for a data retrieval tool. It meets the baseline but doesn't provide full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear enum values for 'interval' and 'datatype'. The description adds no additional parameter information beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieves coffee prices' clearly states the verb ('retrieves') and resource ('coffee prices'), making the purpose immediately understandable. It distinguishes this tool from other commodity tools like 'commodities_aluminum' or 'commodities_corn' by specifying coffee. However, it doesn't explicitly differentiate from other price retrieval tools in the sibling list (e.g., 'coreStock_quote' for stocks), which keeps it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'commodities_globalIndex' for broader data or other commodity-specific tools, nor does it specify any prerequisites or constraints for usage. The agent must infer usage from the tool name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'fetches' implying a read operation, but doesn't disclose behavioral traits like rate limits, authentication needs, data freshness, or error handling. For a data-fetching tool with no annotations, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (fetching financial time series data), no annotations, and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose but lacks context on data format, usage scenarios, and behavioral constraints that would help an agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters (symbol and datatype). The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain what 'adjusted' means or provide examples of symbol formats). Baseline 3 is appropriate when the schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('fetches') and resource ('monthly adjusted time series data for a stock symbol'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'coreStock_monthly' (unadjusted) or 'coreStock_dailyAdjusted', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools (e.g., 'coreStock_monthly', 'coreStock_dailyAdjusted', 'coreStock_weeklyAdjusted'), there's no indication of when monthly adjusted data is preferred over other frequencies or formats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool 'fetches' data, implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, authentication requirements, data freshness, or error handling. For a data-fetching 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (fetching time series data) and the absence of both annotations and an output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and return values. With no output schema, the description should ideally hint at the response format, but it doesn't, leaving gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for all three parameters (symbol, market, datatype). The description adds no additional meaning beyond what the schema provides, as it doesn't explain parameter interactions, examples, or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('fetches') and resource ('daily time series data for a cryptocurrency'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish itself from sibling tools like 'crypto_intraday', 'crypto_weekly', or 'crypto_monthly', which likely provide similar data at different time intervals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools (e.g., crypto_intraday for intraday data, crypto_weekly for weekly data) or any specific contexts where this tool is preferred. Usage is implied by the name 'daily', but no explicit guidelines are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it 'fetches' data (implying read-only), but doesn't mention authentication requirements, rate limits, data freshness, or what the response structure looks like. For a data-fetching tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details about response format, data granularity, or how it differs from similar tools. With no output schema, the description should ideally mention what kind of data structure to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with all parameters well-documented in the input schema. The description doesn't add any parameter-specific information beyond what's already in the schema, so it meets the baseline score when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('monthly time series data for a cryptocurrency'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'crypto_daily', 'crypto_weekly', or 'coreStock_monthly', which would require explicit comparison to achieve a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'crypto_daily' or 'crypto_weekly' for different timeframes, or 'coreStock_monthly' for non-crypto assets. Without any contextual usage instructions, the agent must infer based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states 'retrieves,' implying a read-only operation, but doesn't specify data sources, update frequency, rate limits, authentication needs, or error handling. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Retrieves US durable goods orders data.' It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 optional parameter, no output schema, no annotations), the description is minimally adequate. It states what data is retrieved but lacks context on data recency, granularity, or comparison to siblings. Without annotations or output schema, more behavioral details would improve completeness, but it meets the baseline for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with one parameter ('datatype') fully documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides, such as default behavior or data format implications. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieves US durable goods orders data.' It specifies the verb ('retrieves'), resource ('US durable goods orders data'), and scope ('US'). However, it doesn't explicitly differentiate from sibling tools like 'economicIndicators_cpi' or 'economicIndicators_retailSales' beyond the resource name, which is why it doesn't achieve a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 any prerequisites, constraints, or sibling tools for comparison. The agent must infer usage based on the tool name alone, which is insufficient for optimal selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool 'Retrieves' data, implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, authentication requirements, data freshness, or potential errors. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without unnecessary elaboration, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 optional parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks context on usage, behavioral details, or output format. While adequate for a simple retrieval tool, it doesn't fully compensate for the absence of annotations or output schema, leaving room for improvement in guiding the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters ('interval' and 'datatype') well-documented in the input schema, including enums and defaults. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for adequate coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Retrieves') and resource ('the effective federal funds rate'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'economicIndicators_treasuryYield' or 'economicIndicators_inflation', which are related economic indicators but serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (e.g., other economic indicators like CPI or unemployment rate), there's no indication of when this specific rate is appropriate, what context it applies to, or any prerequisites for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Retrieves', implying a read-only operation, but doesn't mention any behavioral traits like rate limits, data freshness, authentication needs, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple data retrieval tool with two well-documented parameters and no output schema, the description is minimally adequate. However, it lacks context about the data source, time ranges, or what the returned data looks like, which could help the agent use it more effectively. With no annotations, more behavioral detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with clear enum values and defaults for both parameters. The description doesn't add any parameter semantics beyond what's in the schema, but since the schema is comprehensive, the baseline score of 3 is appropriate—adequate but no extra value from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieves') and resource ('US Real Gross Domestic Product (GDP) data'), making the purpose immediately understandable. However, it doesn't differentiate from its sibling 'economicIndicators_realGDPPerCapita', which retrieves similar but distinct data, leaving some ambiguity about when to choose one over the other.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as other economic indicators or the sibling realGDPPerCapita tool. The description lacks context about typical use cases or prerequisites, leaving the agent to infer usage based solely on the tool name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Fetches' implies a read-only operation, it doesn't mention any rate limits, authentication requirements, data freshness, or potential costs/limitations. For a data-fetching tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that immediately communicates the core function. There's no wasted language or unnecessary elaboration - every word serves the purpose of explaining what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context about when to use it, behavioral constraints, or output format details. The 100% schema coverage helps, but the description itself doesn't provide enough guidance for optimal tool selection and usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'intraday time series data' which hints at the interval parameter, but adds no meaningful semantic context beyond what's already in the schema (which has 100% coverage). The schema already thoroughly documents all 5 parameters with descriptions, enums, defaults, and requirements, so the description provides minimal additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetches') and resource ('intraday time series data for a Forex pair'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'forex_daily' or 'forex_weekly' which likely fetch different timeframes, leaving some ambiguity about when to choose this specific intraday tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With many sibling tools available (including other forex tools like forex_daily, forex_weekly, forex_monthly, and forex_exchangeRates), there's no indication of when intraday data is appropriate versus daily, weekly, or other forex data sources.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions 'fetches' which implies a read operation, but doesn't specify whether this requires authentication, has rate limits, returns paginated data, or includes metadata like timestamps. For a data-fetching tool with zero annotation coverage, this leaves critical behavioral traits undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized for a straightforward data-fetching tool and front-loads the core purpose effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple data retrieval tool with 3 parameters and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose but lacks behavioral context (no annotations) and doesn't explain what the returned data looks like (no output schema). The 100% schema coverage helps, but overall completeness is limited to the bare essentials.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for all parameters (from_symbol, to_symbol, datatype). The description adds no additional parameter semantics beyond what the schema provides, such as explaining Forex pair conventions or datatype implications. Baseline 3 is appropriate when the schema does all the documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('fetches') and resource ('weekly time series data for a Forex pair'), making the purpose specific and understandable. However, it doesn't distinguish this tool from sibling tools like 'forex_daily' or 'forex_monthly' that likely fetch similar data at different frequencies, leaving some ambiguity about when to choose this specific tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With sibling tools like 'forex_daily', 'forex_monthly', and 'forex_intraday' available, the agent has no indication whether this tool is for historical analysis, real-time data, or specific use cases, leaving usage decisions to guesswork.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool 'retrieves' data, implying a read-only operation, but does not specify aspects like data freshness, rate limits, authentication needs, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality without any wasted words. It is appropriately sized for a tool with no parameters, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description is minimally complete. It covers what the tool does but lacks details on behavioral traits (e.g., data sources, limitations) and does not explain the return format. For a retrieval tool with no structured output documentation, more context would be helpful, but it meets the basic requirement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by implying the tool returns a fixed set of categories (gainers, losers, most active) and is limited to US tickers, which provides semantic context beyond the empty schema. However, it does not clarify what 'top N' means (e.g., default value or range), leaving minor ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieves the top N gainers, losers, and most actively traded US tickers.' It specifies the verb ('retrieves'), resource ('US tickers'), and scope ('top N gainers, losers, and most actively traded'). However, it does not explicitly differentiate from sibling tools like 'coreStock_bulkQuotes' or 'coreStock_daily', which might also retrieve ticker data, leaving some ambiguity about uniqueness.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not mention any context, prerequisites, or exclusions, nor does it refer to sibling tools for comparison. This lack of usage instructions makes it harder for an AI agent to decide when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'Premium endpoint' which hints at potential access restrictions or costs, but doesn't describe authentication requirements, rate limits, data freshness, pagination, error conditions, or what 'fetches' actually returns. For a financial data tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - just 7 words in a single sentence. Every word earns its place: 'Fetches' (action), 'cash flow data' (resource), '(annual/quarterly)' (key specification), 'Premium endpoint' (important constraint). No wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a financial data tool with no annotations and no output schema, the description is insufficient. It doesn't explain what format the cash flow data returns (structured financial statements? raw numbers?), doesn't specify time periods available, doesn't mention authentication or rate limiting, and doesn't clarify what 'Premium endpoint' means operationally. The agent would struggle to use this effectively without trial and error.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with only one parameter (symbol) fully documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides about the symbol parameter. Baseline 3 is appropriate when the schema does the heavy lifting for parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('cash flow data') with specificity about the data type and periodicity (annual/quarterly). It distinguishes from some siblings like fundamentalData_balanceSheet or fundamentalData_incomeStatement by focusing on cash flow, but doesn't explicitly differentiate from all financial data tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving cash flow statements rather than other financial statements, but doesn't provide explicit guidance on when to choose this over alternatives like fundamentalData_balanceSheet or fundamentalData_incomeStatement. The 'Premium endpoint' note suggests potential access restrictions but doesn't specify when to use premium vs free endpoints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 insight. It mentions 'CSV endpoint' which hints at data format, but doesn't disclose rate limits, authentication needs, data freshness, scope (global/regional), or what 'upcoming' timeframe means. For a data-fetching tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with zero waste. Every word earns its place: 'Fetches' (action), 'upcoming IPO calendar' (resource), 'CSV endpoint' (implementation detail). Front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description is minimally adequate but could be more complete. It identifies the resource and format, but lacks context about data scope, freshness, limitations, or how it differs from similar tools. Without annotations or output schema, the agent has limited understanding of what to expect from this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the baseline is high. The description doesn't need to explain parameters, though it could mention that this tool requires no inputs (which is implied by the empty schema). The mention of 'CSV endpoint' adds some context about output format beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetches') and resource ('upcoming IPO calendar'), making the purpose immediately understandable. It distinguishes from siblings like fundamentalData_earningsCalendar by specifying IPO focus, though it doesn't explicitly contrast with all sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like fundamentalData_earningsCalendar or other calendar-related tools. The description mentions it's a CSV endpoint, but doesn't explain when this format is preferable or what limitations it might have compared to other data formats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Premium endpoint' (hinting at possible access restrictions or costs) and realtime nature, but lacks details on rate limits, authentication needs, error handling, or response format. For a tool with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality ('Fetches realtime quotes for multiple stock symbols') and adds only essential qualifiers ('up to 100', 'Premium endpoint'). There is zero wasted text, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is minimal but covers the basic purpose and scope. It doesn't address behavioral aspects like rate limits or error handling, which are important for a premium API tool. The schema handles parameters well, but overall completeness is adequate with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters (symbols, datatype) well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Fetches realtime quotes') and resource ('for multiple stock symbols'), with explicit scope ('up to 100'). It distinguishes from sibling tools like coreStock_quote (single symbol) and coreStock_daily (historical data), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'Premium endpoint' and the 100-symbol limit, suggesting it's for batch queries. However, it doesn't explicitly state when to use this versus alternatives like coreStock_quote (single symbol) or coreStock_intraday (time-series data), leaving some ambiguity for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that this is a 'Premium endpoint' (implying possible authentication or rate limits) and 'requires intraday interval' (a specific constraint). However, it doesn't mention other behavioral traits like response format details, error handling, or whether it's a read-only operation, leaving gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded: two brief sentences that directly state the tool's purpose and key constraint. Every word earns its place with no redundancy or unnecessary elaboration, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a technical indicator with 4 parameters), no annotations, and no output schema, the description is minimally complete. It covers the core purpose and a key constraint but lacks details on output format, error cases, or deeper behavioral context. It's adequate but leaves clear gaps for an agent to infer usage fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'interval' relates to 'intraday' or provide examples for 'month'). This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: 'Volume Weighted Average Price (VWAP)' specifies the exact technical indicator, and 'Premium endpoint, requires intraday interval' adds context about access and interval requirements. It distinguishes from siblings by naming VWAP specifically, but doesn't explicitly contrast with other technical indicators like SMA or EMA.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance: 'requires intraday interval' suggests when to use this tool (for intraday data) and potentially when not to use it (for non-intraday intervals). However, it doesn't explicitly state alternatives (e.g., other technical indicators for different purposes) or provide clear exclusions, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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