Financial Datasets MCP Server

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by financial-datasets

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but there is some potential confusion between get_crypto_prices and get_historical_crypto_prices, as their names and descriptions overlap significantly. Other tools are clearly differentiated by resource type (crypto vs. stock vs. financial statements).
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case naming. The pattern 'get_[resource]_[specific]' is applied uniformly across all 11 tools, making them predictable and easy to understand.
Tool Count5/5
With 11 tools, the server is well-scoped for financial data access. It covers crypto and stock prices, financial statements, news, and SEC filings, providing comprehensive coverage without being overwhelming or sparse.
Completeness4/5
The tool set covers key financial data domains well, including prices, statements, news, and filings. Minor gaps exist, such as no update or delete operations (which may not be needed) and limited filtering options for some tools, but core workflows are fully supported.
Average 3.1/5 across 11 of 11 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 4 of 5 community issues answered or closed 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 MIT License.
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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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

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 gets historical prices but doesn't specify what data format is returned, if there are rate limits, authentication requirements, or error handling. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
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, straightforward sentence that efficiently conveys the core function. It's front-loaded with the main purpose and avoids unnecessary words, though it could be slightly more informative without sacrificing brevity.
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 (5 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain the return values, error cases, or how to interpret parameters like 'interval' and 'interval_multiplier.' For a tool with multiple parameters and no structured support, more detail is needed to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the parameters have descriptions in the schema. The description mentions 'historical prices' and implies parameters like ticker and dates, but it doesn't explain what 'interval' or 'interval_multiplier' mean or provide any additional semantic context beyond what's inferred from the parameter names.
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 states the tool 'Gets historical prices for a crypto currency,' which clearly identifies the action (gets) and resource (historical prices for crypto currency). However, it doesn't distinguish this from its sibling 'get_historical_crypto_prices,' which appears to serve a nearly identical purpose, making the purpose somewhat vague in context.
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. For example, it doesn't explain how it differs from 'get_current_crypto_price' or 'get_historical_crypto_prices,' nor does it mention any prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 the action ('Gets') without details on permissions, rate limits, data freshness, or output format. This is insufficient for a tool with zero annotation coverage, lacking critical 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 no wasted words. It is appropriately sized and front-loaded, clearly stating the tool's purpose without redundancy or unnecessary 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 lack of annotations and output schema, the description is incomplete. It does not explain what 'available crypto tickers' entails (e.g., list format, supported exchanges, update frequency), leaving gaps in understanding for the agent. This is inadequate for a tool with no structured support.
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 tool has 0 parameters, and schema description coverage is 100%. The description does not add parameter information, which is unnecessary here. A baseline score of 4 is appropriate as no parameters exist to document.
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 states the tool's purpose ('Gets all available crypto tickers'), which is clear but vague. It specifies the verb ('Gets') and resource ('crypto tickers'), but lacks detail on scope or format, and does not differentiate from siblings like 'get_crypto_prices' or 'get_current_crypto_price'. This meets the minimum viable standard.
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 does not mention context, prerequisites, or exclusions, such as how it differs from sibling tools that fetch specific crypto data. This leaves the agent without usage direction.
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 only states the basic action without details on permissions, rate limits, data sources, or response format. This is inadequate for a tool that likely involves external data fetching, leaving the agent with insufficient context for safe and effective use.
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 main purpose, followed by parameter details in a structured 'Args' section. It avoids unnecessary words, but the lack of additional context or guidelines means it might be overly concise for a tool with no annotations or output schema.
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 company news, the absence of annotations and output schema, and only basic parameter info, the description is incomplete. It does not cover behavioral aspects like data sources, error handling, or return structure, making it insufficient for the agent to fully understand the tool's operation.
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 description adds meaningful context for the single parameter 'ticker' by providing an example (e.g., AAPL, GOOGL), which clarifies the expected format. Since schema description coverage is 0%, this compensates well, though it could be enhanced with details like allowed ticker formats or validation rules.
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 'Get' and the resource 'news for a company', making the purpose specific and understandable. However, it does not differentiate from sibling tools like 'get_sec_filings' or 'get_current_stock_price', which might also provide company-related information, 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 siblings like 'get_sec_filings' that might overlap in providing company updates, there is no explicit mention of when this tool is preferred or what distinguishes it, such as news sources, recency, or format.
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 only states the basic action. It doesn't disclose behavioral traits such as data freshness, rate limits, error handling, or authentication needs. For a tool that fetches real-time data, this lack of 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose, followed by parameter details. Both sentences earn their place by adding value, though the structure could be slightly improved by integrating the parameter explanation more seamlessly.
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 real-time financial data, no annotations, and no output schema, the description is incomplete. It lacks details on return values, data sources, potential limitations, or error cases, making it inadequate for informed tool selection.
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 description adds meaningful context beyond the input schema, which has 0% coverage. It explains that 'ticker' is the 'Ticker symbol of the company' and provides examples (e.g., AAPL, GOOGL), clarifying the parameter's purpose and format effectively.
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 'Get' and resource 'current/latest price of a company', making the purpose specific and understandable. It distinguishes from siblings like get_historical_stock_prices by specifying 'current/latest', though it doesn't explicitly contrast with get_crypto_prices or other 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 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 get_historical_stock_prices or get_crypto_prices. The description implies usage for stock prices but doesn't specify exclusions or prerequisites, leaving the agent to infer context from sibling 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 mentions the action ('Get') and parameters but doesn't describe traits like whether it's read-only, requires authentication, has rate limits, returns paginated results, or what the output format is. This leaves significant gaps for a tool with 3 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose followed by parameter details. Each sentence adds value, with no redundant information. It could be slightly more structured (e.g., bullet points), but it's efficient and easy 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 complexity (3 parameters, no annotations, no output schema), the description is incomplete. It covers parameters well but lacks behavioral context (e.g., output format, error handling) and usage guidelines. Without annotations or output schema, more detail is needed to fully inform an agent, especially for a data retrieval 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?
The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains each parameter: 'ticker' as the company symbol with examples, 'limit' as the number of filings to return with a default, and 'filing_type' as the type with examples. This compensates well for the low schema coverage, though it doesn't detail constraints like valid ticker formats or filing type options.
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: 'Get all SEC filings for a company.' It specifies the verb ('Get') and resource ('SEC filings'), distinguishing it from sibling tools that focus on financial statements, news, or prices. However, it doesn't explicitly differentiate from hypothetical similar tools (e.g., 'get_sec_filings_with_details'), though siblings don't include direct 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?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites (e.g., needing a valid ticker), exclusions (e.g., not for historical data), or comparisons to siblings like 'get_balance_sheets' for financial data. Usage is implied by the purpose but not explicitly stated.
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 describes what the tool does but lacks critical behavioral information such as rate limits, authentication requirements, data format of returned prices, error handling, or whether this is a read-only operation. The description is functional but incomplete for safe and effective use.
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 well-structured and appropriately sized, with a clear purpose statement followed by a bulleted parameter explanation. Every sentence adds value, though it could be slightly more concise by integrating the parameter explanations more seamlessly rather than using a separate 'Args' section.
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 annotations, no output schema), the description is partially complete. It excels at explaining parameters but lacks behavioral context and output details. Without an output schema, the description should ideally mention what the return data looks like (e.g., price objects with timestamps and values), which is a notable gap.
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 description provides excellent parameter semantics through the 'Args' section, explaining each parameter's purpose with examples (e.g., 'BTC-USD', '2020-01-01', 'minute, hour, day, week, month', '1, 2, 3'). This significantly compensates for the 0% schema description coverage, making all parameters clearly understandable despite the schema lacking descriptions.
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 ('Gets') and resource ('historical prices for a crypto currency'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_crypto_prices' or 'get_current_crypto_price', which could cause confusion about when to use each.
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. While it mentions that available tickers can be retrieved via 'get_available_crypto_tickers', it doesn't explain when to choose this tool over 'get_crypto_prices', 'get_current_crypto_price', or 'get_historical_stock_prices', leaving the agent without clear usage context.
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 ('Get'), implying a read-only operation, but doesn't cover important aspects like authentication needs, rate limits, error handling, or data freshness. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior and 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 appropriately sized and front-loaded, starting with the core purpose followed by parameter details in a clear 'Args:' section. Each sentence adds value without redundancy. However, the structure could be slightly improved by integrating parameter explanations more seamlessly, rather than a separate list, but it remains efficient and easy to scan.
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 partially complete. It covers the purpose and parameters well, but lacks details on behavioral aspects (e.g., data source, limitations) and output format. Without annotations or an output schema, users are left guessing about the return structure and operational constraints, making it adequate but with clear gaps.
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 description adds meaningful context beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'ticker' as the company symbol with examples (AAPL, GOOGL), 'period' as the statement period with examples (annual, quarterly, ttm), and 'limit' as the number to return with a default. This compensates well for the schema's lack of descriptions, though it could provide more detail on format constraints (e.g., ttm meaning).
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: 'Get income statements for a company.' It specifies the verb ('Get') and resource ('income statements for a company'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_balance_sheets' or 'get_cash_flow_statements' beyond the resource name, 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. It doesn't mention sibling tools like 'get_balance_sheets' or 'get_cash_flow_statements' for financial data, or explain scenarios where income statements are preferred over other financial statements. Usage is implied by the tool name alone, with no explicit context or exclusions provided.
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 'gets' data, implying a read-only operation, but doesn't clarify permissions, rate limits, data freshness, or what happens with invalid inputs. The description adds minimal behavioral context beyond the basic action.
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 well-structured and concise. It starts with a clear purpose statement, then lists parameters with brief explanations and examples. Every sentence adds value, with no redundant or vague language. It's appropriately sized for a tool with three parameters.
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 adequate but has gaps. It covers parameters well but lacks behavioral details like error handling or output format. Without annotations or output schema, more context on what the tool returns would improve completeness for a data-fetching 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?
The description adds significant value beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: ticker as the company symbol with examples, period as the timeframe with examples, and limit as the number to return with a default. This compensates well for the schema's lack of descriptions, though it doesn't detail format constraints like period enum values.
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: 'Get balance sheets for a company.' It specifies the verb ('Get') and resource ('balance sheets'), and distinguishes it from siblings like get_income_statements or get_cash_flow_statements by focusing on balance sheets specifically. However, it doesn't explicitly differentiate from all siblings beyond the resource 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. It doesn't mention when to prefer balance sheets over income statements or cash flow statements, nor does it reference sibling tools. Usage is implied by the resource name alone, with no explicit context or exclusions provided.
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 ('Get'), implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, authentication needs, error handling, or what the return format looks like. For a data retrieval 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 appropriately sized and front-loaded: it starts with a clear purpose statement, followed by a structured list of parameters with explanations and examples. Every sentence earns its place, with no wasted words or redundancy, 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 complexity (a data retrieval tool with 3 parameters) and the lack of annotations and output schema, the description is partially complete. It covers the purpose and parameters well, but misses behavioral context (e.g., return format, error cases) and usage guidelines. For a tool with no structured support, it should do more to compensate, but it's adequate as a minimum viable description.
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 description adds substantial meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose (e.g., 'ticker symbol of the company', 'period of the cash flow statement', 'number of cash flow statements to return') and provides examples (e.g., 'AAPL, GOOGL', 'annual, quarterly, ttm', 'default: 4'). This compensates well for the schema's lack of descriptions, though it doesn't cover all possible nuances like format constraints for 'period'.
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: 'Get cash flow statements for a company.' It specifies the verb ('Get') and resource ('cash flow statements'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_balance_sheets' or 'get_income_statements' beyond the resource name, 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. There are no mentions of when-not scenarios, prerequisites, or comparisons to sibling tools like 'get_balance_sheets' or 'get_income_statements'. The only usage context is implied by the parameters, 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 only describes what the tool does ('Gets historical stock prices') without mentioning rate limits, authentication requirements, data source, response format, error conditions, or whether this is a read-only operation. For a data retrieval 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?
The description is perfectly structured and concise. It starts with a clear purpose statement, then provides a well-organized parameter section with each parameter explained in a single line with helpful examples. Every sentence earns its place with no redundant 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 5 parameters, no annotations, and no output schema, the description does an adequate job on parameters but lacks critical context. It explains what parameters to provide but doesn't describe what the tool returns (data format, structure), error handling, or behavioral constraints. For a data retrieval tool with multiple parameters, this leaves the agent with incomplete understanding of the full operation.
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 description provides excellent parameter semantics despite 0% schema description coverage. It clearly explains each parameter's purpose with examples: ticker symbol examples (AAPL, GOOGL), date format examples (2020-01-01), interval options (minute, hour, day, week, month), and interval_multiplier examples (1, 2, 3). This fully compensates for the lack of schema descriptions.
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 'Gets historical stock prices for a company' - a specific verb ('Gets') and resource ('historical stock prices'). It distinguishes from siblings like get_current_stock_price by specifying historical data, but doesn't explicitly differentiate from get_historical_crypto_prices beyond the 'stock' vs 'crypto' distinction in names.
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 get_current_stock_price for real-time data, or how it relates to get_historical_crypto_prices for different asset classes. No prerequisites, limitations, or comparison context is provided.
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 of behavioral disclosure. It indicates this is a read operation ('Get') but lacks details on rate limits, error handling, data freshness, or response format. It adds some context by mentioning ticker availability via another tool, but overall behavioral traits are minimally covered.
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 front-loaded with the core purpose in the first sentence, followed by parameter details in a structured 'Args' section. Every sentence adds value without redundancy, making it efficient and well-organized for quick understanding.
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 parameter, no output schema, no annotations), the description is adequate but has gaps. It covers the basic purpose and parameter guidance but lacks details on return values, error cases, or behavioral constraints like rate limits, which would enhance completeness for a price-fetching 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?
The schema has 0% description coverage, so the description must compensate. It adds meaning by explaining the 'ticker' parameter as a symbol (e.g., BTC-USD) and referencing get_available_crypto_tickers for valid values. This clarifies semantics beyond the bare schema, though it could provide more detail on format constraints.
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 ('Get the current / latest price') and resource ('crypto currency'), distinguishing it from siblings like get_historical_crypto_prices (historical vs current) and get_crypto_prices (plural vs singular). It directly addresses what the tool does without being vague or tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by referencing the get_available_crypto_tickers tool for valid ticker symbols, which implicitly guides usage. However, it does not explicitly state when to use this tool versus alternatives like get_crypto_prices or get_historical_crypto_prices, missing explicit exclusions or comparisons.
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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