FinImpulse MCP Server

Server Quality Checklist

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Latest release: v1.2.1
Disambiguation4/5
Tools are mostly distinct by domain (search, summary, financials, holders, options, etc.), but the presence of 'lite' variants (get_search_lite, get_summary_lite) and multiple general/specific pairs (e.g., get_statistics_general vs. get_statistics_risks) creates minor overlap. Descriptions clearly differentiate purposes, so agents can select correctly with careful reading.
Naming Consistency5/5
All tool names follow a strict get_<domain>_<subtype> pattern, with hierarchical consistency across related groups (e.g., get_financials_*, get_holders_*, get_options_*). The only minor deviation is the 'lite' suffix on get_search_lite and get_summary_lite, but this does not break the overall pattern.
Tool Count3/5
31 tools is on the heavy side, exceeding the typical 25+ threshold, but the server's broad scope (stocks, ETFs, mutual funds, options, multiple data categories) justifies the granularity. Each tool serves a specific purpose, though some could potentially be consolidated (e.g., individual financial statements vs. a combined endpoint).
Completeness5/5
The tool set provides comprehensive read-only coverage of financial data, including search, summaries, detailed statements, holders, analyst actions, options chains, and historical data. The end-to-end workflow for options (expirations -> chain -> contracts) and financials (general -> specific statements) is well-supported, with no obvious missing operations for a data-provider server.
Average 4/5 across 31 of 31 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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 ISC 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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}
```
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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?
With no annotations, the description carries the full burden of behavioral disclosure. It only lists categories of returned metrics but does not describe response format, data granularity, potential limitations, or whether any authentication or rate limits apply. The behavior is largely implied by the tool name and metric list.
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 contains two sentences that redundantly restate the same information. The first sentence lists the metric categories, and the second repeats them with slight rewording. This could be condensed into one tight sentence without losing meaning.
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 there is no output schema and no annotations, the description is the only guidance for the agent. It fails to differentiate this tool from many similar sibling metrics tools, does not indicate response structure, and lacks usage scenarios. This is insufficient for reliable 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?
Schema coverage is 100%, with both parameters described. The description adds minimal meaning by indicating the symbol parameter is for a 'single asset,' but does not expand on the 'tag' parameter or provide format details beyond the schema. Baseline of 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 clearly states that the tool returns dividend data, returns, profitability, growth, leverage, and business quality metrics for a single asset symbol. This is a specific verb and resource, but it does not distinguish itself from sibling tools that also retrieve financial metrics, such as get_statistics_annual_returns or get_financials_valuation_measures.
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 when-to-use or alternative guidance is provided. The only contextual hint is 'Primarily applicable to stocks,' which is a domain restriction rather than a comparison to alternatives. The description does not explain scenarios where this tool should be preferred over siblings.
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, the description carries the behavioral disclosure burden. It accurately conveys a read-only operation by saying 'Returns...' and discloses asset-type coverage (stocks and funds/ETFs), which hints at limitations for other asset types. However, it does not go deeper into potential issues like data freshness, invalid symbol handling, or rate limits, leaving some ambiguity.
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 three sentences, front-loaded with the primary purpose, and each sentence adds meaningful information about the tool's scope and content. It is slightly verbose but not wasteful, and the structure is logical – from general function to specifics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description gives a solid high-level overview of what is returned, listing major categories (valuation, dividends, risk, etc.). It is adequate for an agent to understand the tool's purpose, though it lacks detail on the exact return shape and does not explicitly differentiate from overlapping siblings like get_metrics.
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% for the only parameter 'symbol', which is already described as 'Asset identifier (ticker symbol)'. The description adds no further semantic detail about the parameter, so it provides no value beyond 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 tool returns 'a consolidated set of key statistics and performance indicators for an asset' and lists specific data categories (price, valuation, dividends, risk, trailing performance), which is a specific verb-resource pair. It distinguishes itself from narrower siblings by positioning as a 'unified statistics snapshot' covering stocks and funds/ETFs, though it doesn't explicitly reference alternative 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 use when a broad statistics overview is needed, saying it 'acts as a unified statistics snapshot' and covers multiple data types. However, it provides no explicit when-to-use or when-not-to-use guidance, nor does it name alternatives like get_summary or get_statistics_risks for comparison.
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, the description carries the full burden. It transparently indicates the tool is read-only by saying 'Returns' and lists the data blocks it delivers (income statement, balance sheet, cash flow, valuation measures). However, it does not disclose potential limitations like data coverage, delay, or pagination behavior, so it is adequate but not rich.
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 three sentences, front-loaded with the purpose, and each sentence adds meaningful context about scope, data types, and filtering. It is compact without being under-specified.
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 with 5 parameters and no output schema, the description gives a good overview but lacks return structure details. It mentions 'unified response' and lists data blocks, but does not explain the output shape or how to interpret the combined response. This is a notable gap in the absence of an output 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 coverage is 100%, with each parameter described in the input schema. The description adds value by naming 'annual, quarterly, trailing' and 'type and interval' filtering, but this largely repeats schema enum values. Baseline of 3 applies 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns financial statements and valuation measures, with a specific verb ('Returns') and resource ('equity'). It distinguishes itself from sibling tools by emphasizing 'unified response' and filtering by type and interval, which contrasts with the specialized 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when multiple financial statement types or intervals are needed, but it does not explicitly mention alternatives or exclusions. No direct guidance like 'use this for a broad overview' or 'use get_financials_income_statement for a single statement' 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, the description must disclose behavioral traits. It states that the endpoint returns a single unified stream and that event types are optional and 'where available,' which is useful context. Missing are details on response format, pagination, rate limits, or error behavior, leaving moderate 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 three sentences long, with the core purpose front-loaded in the first sentence. Every sentence adds value: the second specifies return content, the third summarizes configuration options without unnecessary padding.
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 an 8-parameter tool with no output schema, the description provides a solid high-level overview but lacks details on return structure, default behaviors, or error conditions. The single unified stream concept is mentioned but not elaborated, so an agent might not know what to expect in the response.
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 description does not need to repeat parameter detail. It does add a useful summary of configurable aspects ('date range, interval, included record types, sorting, and page size') but adds no syntax or semantics beyond what the schema already provides.
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 opens with a specific verb and resource: 'Returns time-series data for an asset in a single unified stream.' It clearly distinguishes itself from sibling tools like get_search or get_financials by focusing on historical prices and event types (dividends, splits, capital gains).
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 the tool is for retrieving historical market data and mentions configurable options, giving clear context for when it would be used. However, it never explicitly states when to use this tool versus alternatives or any exclusions, such as 'use get_market_price for current prices.'
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose the return item structure (headline, description, pub date, tickers, provider) and the asset scope, which is useful. However, it omits behavioral details like pagination defaults, maximum limit, or that a symbol is required. Since the schema captures parameter constraints, the description's additions are moderate.
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 three concise sentences, front-loaded with the primary action and scope, followed by a clear list of return fields. Every sentence adds value, with no redundancy or filler.
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?
The tool has eight parameters, no output schema, and no annotations. The description covers the core purpose and return content, but does not mention required parameters, pagination behavior, or defaults. While the input schema fills many gaps, the description alone is not fully complete for an agent to invoke the tool correctly without relying on the 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%, with all eight parameters described in the input schema. The description adds only broad context ('latest', 'aggregates'), not parameter-specific syntax or examples. This meets the baseline but does not go beyond it.
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 verb 'returns' and the resource 'latest news and press releases for financial assets.' It specifies asset types (stocks, ETFs, mutual funds) and lists the fields included in each item, fully distinguishing it from sibling tools like get_histories or get_summary which serve other purposes.
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 news for a given asset, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions. For example, it doesn't compare with get_search or get_histories, leaving the agent to infer applicability from 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.
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 the response is normalized and includes price, liquidity, performance, and classification fields, which is useful. However, it doesn't mention pagination behavior, rate limits, authentication needs, or what happens when no search_text is provided, leaving some behavioral traits undisclosed.
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 three sentences, front-loaded with the primary action, and each sentence adds value: what it does, when to use it, and what it returns. There is no redundancy or filler, 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?
While the description explains the tool's purpose and return fields, it doesn't fully cover the context needed for a tool with no output schema and no annotations. It omits details on required inputs for meaningful search (e.g., whether search_text must be provided), typical response size, or error behavior. The schema mitigates some gaps, but the description could be more complete.
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% parameter description coverage, including detailed explanations for filters, sort_by, quote_types, and others. The tool description itself adds no parameter-specific semantics beyond the schema, so the baseline of 3 is appropriate since the schema already 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 'Returns a unified, cross-asset search result for financial instruments' and lists specific asset types and use cases (global asset search, ticker autocomplete, discovery flows). It distinguishes itself from siblings like get_search_lite through the emphasis on cross-asset and unified results, though it doesn't explicitly name alternative tools.
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 concrete scenarios for when to use the tool: 'global asset search, ticker autocomplete, discovery flows, and AI-assisted search scenarios.' This gives clear context for appropriate use, though it doesn't explicitly state exclusions or when NOT to use it, which would warrant a 5.
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 for behavioral disclosure. It discloses a limitation (mutual funds unsupported) and a prerequisite (valid expiration date). However, it omits potential issues like large response sizes, pagination behavior, or the need for special permissions. These omissions keep it at a baseline level.
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 three sentences, each serving a clear purpose: what it does, what it applies to, and how to use it. It is front-loaded with the primary functionality and contains no redundant phrases or filler. This is an exemplary level of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's purpose, return contents, applicability, prerequisite step, and common use cases, which is quite comprehensive for a read-only tool. It does not mention filtering or sorting capabilities, but those are documented in the schema. The absence of an output schema is partially compensated by listing the returned fields. Overall, it gives enough context for an agent to decide when to use the 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?
Schema description coverage is 100%, so the baseline is 3. The description does not add any extra nuance about the parameters themselves; it only reiterates the expiration date requirement that is already in the schema. It adds no value beyond what the structured property descriptions provide.
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 states the tool returns the full option chain for a single ticker and expiration date, including a comprehensive list of contract fields. This is a specific verb+resource that clearly conveys the tool's function. However, it does not explicitly distinguish itself from sibling tools like get_options_contracts, relying on the word 'full' to imply the difference.
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 contextual guidance: it works for stocks/ETFs, not mutual funds, and instructs users to call get_options_expirations first. It also suggests use cases like populating an options chain table or feeding strategy builders. It lacks explicit exclusions or alternative tool recommendations, so it does not achieve a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well by disclosing the asset-type-dependent behavior (stocks vs. ETFs/mutual funds) and that governance fields may be standardized placeholders. It does not cover error behavior, data freshness, or response format, but the disclosed variability is valuable.
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 with three sentences that front-load the core purpose and then elaborate on the unified nature. It is concise without being under-specified, earning a high score, though it could be slightly tightened.
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 simplicity (one parameter) and lack of output schema, the description provides a reasonable overview of what fields to expect but remains somewhat vague ('governance fields,' 'fund-specific attributes where applicable'). It does not give examples or detailed return structure, leaving some ambiguity for an 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 only parameter, 'symbol', is fully described in the input schema as 'Asset identifier (ticker symbol).' The description adds no additional parameter-level detail, so it does not go beyond the schema, giving the baseline score of 3.
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 tool returns a profile and descriptive metadata for an asset, with specific content categories. It distinguishes itself as a 'unified profile snapshot' that combines company identity, fund profile, and governance placeholders, which differentiates it from sibling tools like get_summary or get_metrics.
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 obtaining a general profile but provides no explicit guidance on when to use this tool versus alternatives. It does not mention exclusions or when not to use it, leaving the agent to infer its role from the unified snapshot phrasing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a key behavioral trait: non-stock assets return an empty result. It also indicates pagination behavior. This adds useful context beyond a basic 'returns a list' statement, though it does not cover error handling or auth requirements.
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 two sentences, front-loaded with the main function, and every sentence adds value. It is concise without being under-specified.
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?
The description gives a reasonable overview but lacks clarity on how it differs from the sibling get_holders_insiders_transactions. Without an output schema, it partially describes return content ('recent insider actions, roles, and reported positions') but could be more explicit about the full record structure. This leaves some ambiguity for an agent deciding between tools.
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 parameters in detail. The description does not add parameter-level semantics but correctly implies the primary input is a stock symbol. Baseline of 3 is appropriate since the schema carries the burden.
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 returns a paginated list of insider transaction records for an asset, specifying content such as insider actions, roles, and reported positions. However, it does not distinguish itself from the sibling tool get_holders_insiders_transactions, which likely performs a similar function, so it lacks explicit 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-not guidance: 'Applicable only to stocks — for ETFs and mutual funds returns an empty result.' This establishes clear context for appropriate use. However, it does not mention alternatives or when to prefer this tool over other holder-related tools, so it falls short of a full 5.
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?
The description discloses that the response field set is fixed but controllable via select_identifiers and characterizes the output as including core identification, pricing, and performance metrics. With no annotations, it does not explicitly state read-only behavior or error semantics, but the search context makes this implicit. The added context about the fixed field set and the alternative endpoint provides some value but not deep behavioral detail.
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?
Two sentences with no redundancy. The main purpose and the key alternative are stated upfront, making the description 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?
For a tool with 12 parameters, no output schema, and no annotations, the description gives a high-level overview but omits mention of filtering, sorting, pagination, and other capabilities. The schema fills many gaps, but the lack of a defined output structure means the agent must infer the response shape from the brief mention of 'core identification, current pricing, and key performance metrics'.
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 provides 100% coverage of all 12 parameters with detailed descriptions, so the baseline is 3. The description adds a note about select_identifiers controlling the field set, but this largely repeats schema information. No additional parameter semantics are provided beyond the schema.
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 tool returns 'a unified, cross-asset search result for stocks, ETFs, and mutual funds' and distinguishes it from the sibling 'get_search' by emphasizing a 'focused field set' and redirecting to '/v1/search' for comprehensive needs. The verb and resource are specific and unambiguous.
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 explicitly names an alternative endpoint for comprehensive field sets ('For a comprehensive field set use the /v1/search endpoint'), implying this tool is intended for focused searches. However, it does not provide broader when-to-use/when-not-to-use guidance beyond this single distinction.
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 transparency burden. It discloses that the response field set is fixed and controllable via select_identifiers, and that the endpoint returns a focused subset. However, it does not mention the output format, potential errors, or always-returned fields like 'symbol' and 'logo' (which appear only in the schema). This is adequate but not fully transparent.
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 four sentences and mostly to the point. The first two sentences are somewhat redundant ('focused snapshot of key identification, market, and fundamental data' vs. 'core identification, current pricing, key valuation metrics, and fundamental data'), but the essential information about field control and the alternative endpoint is included without excessive verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with no output schema, the description covers purpose, field selection, and the alternative comprehensive endpoint. It gives a reasonable sense of the response contents (identification, pricing, valuation metrics, fundamentals). However, it does not specify the exact response structure or any prerequisites beyond symbol, leaving minor gaps given the lack of an output 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 schema already explains all three parameters. The description adds some context for select_identifiers by stating it controls which fields are included, but this largely parallels the schema's own description. No new parameter semantics are introduced beyond the schema baseline.
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 tool 'Returns a focused snapshot of key identification, market, and fundamental data for a single asset symbol,' using a specific verb and resource. It distinguishes itself from get_summary by explicitly noting the focused nature and directing users to the comprehensive endpoint, 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (for a quick, focused snapshot) and explicitly provides an alternative: 'For a comprehensive field set use the /v1/summary endpoint.' This gives clear context for choosing between tools, though it does not enumerate all possible alternatives or exclusions.
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?
No annotations are provided, so the description carries the full behavioral disclosure burden. It adds a useful caveat about ETFs/mutual funds possibly returning empty results and states the tool returns records, implying read-only. However, it does not disclose pagination behavior, potential authorization requirements, or what happens for invalid symbols—details an agent might need for robust 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 three sentences long and front-loaded with the core purpose. Each sentence earns its place: content scope, filtering capabilities, asset-class caveat, and intended use cases. No redundant filler or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description adequately outlines return contents by naming the metric categories included. It addresses the key edge case of non-stock assets. However, it could explicitly mention pagination (limit/offset) or default behavior for date filters, but the schema already documents these, so the description covers the most critical operational context without overburdening the text.
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 baseline is 3. The description reinforces the meaning of 'types' by listing record types and clarifies 'methodologies' via 'GAAP/normalized', but it does not explain complex parameters like filters, sort_by, or comparison_symbols. Since the schema already handles those, the description adds only marginal semantic value beyond the structured fields.
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 tool returns earnings and estimate records for an asset, listing specific data categories (EPS actuals, earnings vs. revenue, EPS trends, revisions, growth). It distinguishes itself from siblings by explicitly mentioning earnings analytics and the 'Earnings & Estimates dashboards', making its purpose unmistakable.
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 a clear use case: 'Use for populating Earnings & Estimates dashboards or feeding earnings analytics pipelines.' It also gives a when-not-to-use hint by stating ETFs and mutual funds may return empty results. However, it does not explicitly name alternative tools for non-stock instruments or compare with related get_analysis_* tools.
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, the description carries the behavioral disclosure burden. It accurately describes the returned data (counts per recommendation category) and a key limitation (empty results for non-stocks). However, it does not disclose pagination behavior, default ordering, response envelope, or potential rate-limit/auth requirements, so it is moderately transparent but not highly detailed.
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 two concise sentences that lead with the primary purpose, then cover limitations and use cases. Every sentence contributes value, with no redundant or vague wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an 8-parameter read tool with no output schema and no annotations, the description covers the core purpose, return content, asset applicability, and practical use cases. It could have mentioned default ordering or response structure, but the provided details are sufficient for basic 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 coverage is 100%, so the baseline is 3. The description reinforces the time-series nature of the data, which indirectly relates to start_date, end_date, and limit, but it does not add specific parameter semantics beyond the schema's already thorough descriptions.
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 uses a specific verb ('Returns') and clearly identifies the resource: analyst recommendation breakdown for a ticker over time, with explicit counts for Strong Buy, Buy, Hold, Sell, and Strong Sell. It distinguishes itself from sibling analysis tools by emphasizing periodic snapshots and sentiment-change tracking.
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 for when to use the tool: building Recommendations charts or tracking sentiment changes over time. It also states an important exclusion: ETFs and mutual funds may return empty results. It doesn't explicitly name sibling tools as alternatives, but the guidance is sufficient for selection.
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?
No annotations are provided, so the description carries the full burden. It discloses the data scope ('stocks and some funds') and mentions interval filtering, but it does not disclose output format, error behavior, or data availability limitations. As a read-only get call, this is a moderate disclosure 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?
Two well-structured sentences: the first states the core purpose, the second adds filtering options and use cases. No fluff or redundant phrases.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description should clarify return structure. It provides a high-level snapshot and practical use cases but not field-level detail. For a well-known financial statement tool, this is adequate and reasonably complete, though it could be richer.
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 already describes all parameters with 100% coverage. The description adds context about interval filtering and 'historical data' for date range, but does not add significant new semantics beyond what the schema provides.
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 names the exact resource ('Balance Sheet data'), defines its scope ('stocks and some funds'), and explains what it provides ('snapshot of a company's financial position and capital structure'). This clearly distinguishes it from sibling financial tools like income statement or cash flow.
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 gives explicit use cases: 'Use to populate the Balance Sheet section or retrieve historical data for solvency analysis, ratios, and modeling.' It does not explicitly name sibling alternatives or exclusions, but the context is clear enough to guide appropriate selection.
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, the description carries the full burden of behavioral disclosure. It explains the return content and interval filtering, but does not mention response format, pagination, error handling, or any special behaviors. It adds some context but not deep operational detail.
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?
Two sentences, immediately naming the data returned and then providing use cases. No filler or redundancy; every clause adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, but the description sufficiently communicates the nature of the returned data (cash flow statement with three components). It does not specify field-level structure, but given the standard financial domain and sibling context, this is acceptable. The description covers core functionality and use 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 coverage is 100%, so the baseline is 3. The description reinforces interval filtering and 'selected period' but adds little beyond the schema's own parameter descriptions. The phrase 'multi-period series' hints at the intervals array, but the schema already explains supported values and defaults.
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 tool returns 'detailed Cash Flow Statement data' with specific components (operating, investing, financing cash flows), which distinguishes it from sibling tools like income statement and balance sheet. The verb 'Returns' and resource 'Cash Flow Statement' are precise.
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 explicit use cases: 'populate the Cash Flow section or extract multi-period series for liquidity analysis, forecasting, or visualization.' It does not explicitly mention alternatives or exclusion scenarios, but the context is clear enough for an agent to decide when to use this tool.
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?
No annotations are provided, so the description carries the burden of behavioral disclosure. It discloses supported intervals and asset types (stocks/some funds), but it does not explicitly state that the operation is read-only, mention pagination, or describe the return format. For a data retrieval tool, the non-destructive nature is implied but not stated.
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 two sentences, front-loaded with the main purpose, and every sentence adds value. It is concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with four parameters all documented in the schema. The description adds use cases and supported intervals, which is adequate for a data retrieval tool. Since there is no output schema, the description could have mentioned the response type, but it is not essential for this tool type.
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 each parameter. The description adds minimal semantic value by listing the supported intervals, which reinforces the schema, but does not add deeper meaning about date range behavior or how interval filtering interacts with the returned data.
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 tool's purpose: providing key Valuation Measures for stocks and some funds, with specific examples (P/E, EV/EBITDA, P/B). It distinguishes itself from sibling financial statements tools by focusing on valuation metrics rather than income statements or balance sheets.
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 usage context: 'Use to populate the Valuation Measures section or pull valuation metrics aligned to the same date grid as financial statements for comparative analysis.' This indicates when to use it, though it does not explicitly mention when not to use it or name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 honestly reveals a key limitation (empty response for stocks/ETFs) and defines the output scope (standardized time horizons and metric list). It does not cover error scenarios or pagination behavior, but the disclosed limitation is significant and useful.
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 three sentences, front-loaded with the core purpose, and every sentence adds useful detail (time horizons, asset-type caveat, metric list). There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema or annotations, the description reasonably conveys what the response contains (listed metrics across time horizons) and the main caveat for asset types. It does not mention return structure (e.g., array/object shape) or pagination, but given the parameter schema is rich, this is acceptable.
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 defines each parameter. The description adds context about the metrics that might be used in filters/sorting, but does not further elaborate on parameter syntax or semantics beyond what the schema provides, aligning with the baseline.
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 tool returns risk and risk-adjusted performance metrics for an asset across standardized time horizons (3y, 5y, 10y). It lists specific metrics (Alpha, Beta, Sharpe Ratio, etc.), distinguishing it from siblings like get_statistics_general and get_statistics_annual_returns.
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 a clear usage condition: risk metrics are available for mutual funds, but for stocks and ETFs the response may be empty. However, it does not explicitly name alternative tools or state when to use a different tool, such as get_statistics_general, so guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses pagination behavior, asset-type limitations, and the set of returned fields (per-analyst scores, current rating, sentiment, price target, latest announcement date). It does not mention auth, rate limits, or error conditions, but for a read-only list tool this is acceptable.
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?
Two sentences, front-loaded with the core purpose, followed by usage guidance. Every phrase adds information; no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description sufficiently covers purpose, return contents, pagination, and asset-type limitations, and the schema covers parameters comprehensively. However, since there is no output schema, the description could ideally specify the response envelope (e.g., total count) or error behavior, leaving a small gap.
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 already provides 100% coverage of all six parameters, including descriptions and examples for filters and sort_by. The description's mention of filtering by sentiment and sorting by announcement date adds usage context but little new parameter semantics, so baseline 3 is appropriate.
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 uses the specific verb 'Returns' and identifies the resource as 'analyst-level coverage records for an asset', then enumerates the contained data fields. This clearly distinguishes it from sibling tools like get_analysis_recommendations and get_analysis_upgrades_downgrades.
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 states to 'Use for populating an Analysts table in the Analysis module, filtering by sentiment, or sorting by announcement date,' giving concrete when-to-use guidance. It also warns that ETFs and mutual funds 'may return empty results,' a when-not for asset types. However, it does not name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 read-only intent via the verb 'Returns', coverage limitations ('for stocks and some funds'), and filtering behavior ('Supports filtering by interval'). It does not detail error handling, rate limits, or permissions, but for a read-only data retrieval tool, this is adequate.
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 two sentences long, front-loads the core purpose, and includes only necessary details like fields and filtering. No redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description must convey return value expectations. It names key data fields and mentions time-series data, which gives a reasonable picture. However, it does not specify whether the result is a single statement per interval or a list, nor the exact date range behavior, leaving some ambiguity.
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 for all parameters, including enums for intervals and date formats. The description only repeats the interval filtering concept and does not add meaningful detail beyond the schema. This meets the baseline of 3 for high schema coverage.
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 tool returns Income Statement data, listing specific fields (revenue, expenses, net income). It uses the specific verb 'Returns' with the resource 'Income Statement data', and distinguishes from sibling financial tools like get_financials_balance_sheet or get_financials_cash_flow by naming the exact statement type.
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 use cases ('populate the Income Statement section or pull time-series data for financial modeling and charting'), which tells the agent when to use it. However, it does not explicitly mention alternatives or when not to use it, though sibling names make the distinction obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 discloses pagination, filtering/sorting support, the included response fields, and the empty-response caveat for non-stocks. It doesn't cover return structure or potential error conditions, but the transparency is solid for a read 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 three concise, front-loaded sentences: purpose, included fields, and usage caveat. Every sentence contributes meaningful information with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list-returning tool with no output schema, the description provides good coverage: it states the resource, the fields returned, and a key limitation. The complex filter/sort parameters are fully documented in the schema, so the description needn't repeat them. Slightly more detail on response structure would make it complete, but it's already strong.
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 parameters. The description mentions filtering and sorting generically but adds no deeper parameter-level semantics beyond the schema's detailed descriptions. Baseline 3 is appropriate.
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 it returns a paginated list of institutional holders for an asset, including specific fields like position, percent held, and estimated value. It distinguishes itself from sibling tools (holders_general, holders_mutual_funds, holders_insiders) by specifying institutional holders and noting the typical empty response for ETFs/mutual funds.
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 explicitly notes that the tool is primarily relevant for stocks and that ETFs/mutual funds typically return empty responses, providing direct when-to-use guidance and an exclusion. However, it doesn't name alternative tools for those cases (e.g., holders_mutual_funds), so it stops short of fully explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It reveals the edge-case behavior (empty result for ETF/mutual fund symbols) and lists the output fields (position size, percent held, estimated value). This is meaningful context beyond the 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 three sentences, each adding distinct value: what it returns, the question it answers, and a critical edge-case warning. No wasted words, information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description mentions the key response fields (position size, percent held, estimated value), which covers the essential return information. The tool's moderately complex filtering/sorting parameters are thoroughly documented in the schema itself, so the description does not need to repeat them. The empty-result behavior for non-stock symbols adds 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 all parameters (symbol, limit, offset, filters, sort_by) are already well-documented. The description adds no new parameter semantics beyond reinforcing that the symbol must be a stock, which the schema already states. Baseline 3 applies 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a list of mutual funds and ETFs that hold a given stock, including position size, percent held, and estimated value. It also distinguishes itself from sibling holder tools by noting it is stock-centric and returns empty for ETF/mutual fund symbols.
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 implies when to use this tool by framing it as answering 'Which funds hold this stock?' and explicitly warns that it returns empty results for ETF and mutual fund symbols, providing a clear exclusion. It does not name alternative sibling tools, but the use case is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the fund-only scope, the empty result for stocks, and the weight formatting as a percentage of net assets. It does not mention auth/rate limits, but for a read-only query tool these are less critical.
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 three sentences long, front-loaded with the main purpose, and each sentence adds value: what it returns, the stock exception, and intended use cases. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description plus schema give an agent enough to invoke correctly: return content, stock behavior, and filter/sort details. The only gap is that no output schema is provided, and the description doesn't describe pagination behavior, but the schema's limit/offset docs cover that.
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 the schema already fully documents all five parameters including detailed filter and sort syntax. The description adds no extra parameter semantics beyond stating that filtering and sorting are supported, so the baseline 3 is appropriate.
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 tool returns top holdings for funds (ETF or mutual fund), specifies the return fields (ticker symbol, name, weight as percentage), and explicitly notes that stocks return an empty result. This distinguishes it from sibling holder tools like get_holdings_general or get_holders_*.
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 explicit use cases ('Use to display portfolio concentration, issuer exposure, or Top Holdings tables') and a clear when-not behavior ('For stocks returns an empty result'). However, it does not name alternative tools for other holding scenarios, so it misses the full explicit alternatives criterion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals meaningful behavior: US-listed assets include pre-market and post-market session prices, while non-US assets only return regular session and current price. It also clarifies the 'current price' is the most recent traded price. This goes beyond a simple 'gets price' statement.
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 three sentences, front-loaded with the core purpose. Every sentence adds value: first states the action, second details US response, third details non-US response and applicable asset types. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description adequately explains return behavior and asset coverage. It does not mention potential errors or data format, but the provided details about session prices and current price are sufficient for an agent to understand what 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 input schema already provides a complete description of the 'symbol' parameter at 100% coverage. The description adds minimal additional meaning ('single asset symbol'), which is marginal. Per the rubric, baseline 3 is appropriate when schema coverage is high.
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 tool's function with a specific verb and resource: 'Returns the current market price snapshot for a single asset symbol.' It also specifies the asset classes (stocks, ETFs, mutual funds), which differentiates it from sibling tools focused on histories, financials, or statistics.
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 limiting to a single symbol and specifying applicable asset types, but it does not explicitly name alternatives or state when not to use the tool. The context is sufficient for an agent to infer when this is appropriate, though explicit exclusions would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the return contents (annual returns, quarterly breakdowns, category comparisons), availability by asset type, and the empty-result behavior for stocks. It does not discuss rate limits or error conditions, but this is a simple read-only statistics tool, and the disclosed behavior is sufficient for safe use.
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 three sentences, each earning its place: what it returns, asset class limitations, and use cases. It is tightly packed with no redundant or vague wording, and the most important information (function and scope) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description covers purpose, usage, and limitations effectively. It mentions key output facets (quarterly breakdowns, category comparisons) but does not specify the exact return data structure (e.g., JSON object keyed by year), which would be helpful but is not critical for 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 schema covers 100% of the single parameter with 'Asset identifier (ticker symbol).' The description does not add further parameter-level detail, but given the schema's clarity, the baseline of 3 is appropriate. The description's context about asset types indirectly enriches the symbol parameter's meaning.
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 it 'Returns historical annual total returns for an asset by calendar year' with specific details like quarterly breakdowns and category comparisons. It distinguishes itself from sibling tools by specifying asset class coverage (ETFs/mutual funds vs stocks), making the purpose unmistakable.
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 when-to-use guidance: 'analyze long-term historical performance, compare against category averages, or build performance tables.' It also states a critical exclusion: 'returns empty result for stocks,' which tells the agent when not to use it. However, it does not explicitly name alternative sibling tools, relying on the tool list for that.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the tool returns a broad set of fields across multiple views, indicating a comprehensive aggregate response. The word 'Returns' and 'snapshot' imply a read-only operation. It does not disclose authentication or rate limits, but these are less critical for a simple 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 two sentences: the first gives a specific purpose, the second adds usage context. Both are informative and free of fluff, making it appropriately compact and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description provides sufficient context: the full list of data categories, how it relates to other endpoints, and when to use it. The agent can confidently decide to invoke it without needing additional 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 has one parameter, 'symbol', with a description 'Asset identifier (ticker symbol).' The description mentions 'single asset symbol' but provides no additional format or syntax details. With 100% schema coverage, the baseline of 3 is appropriate.
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 states it 'Returns a unified snapshot of identity, profile, market data, fundamentals, ownership, analyst coverage, and fund metrics for a single asset symbol.' This clearly specifies the action, resource, and scope, and differentiates itself as a comprehensive aggregate versus sibling tools like get_profile or get_statistics_general.
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 explicitly says 'Use it when you need fast, accurate, high-coverage data for a ticker without orchestrating multiple endpoints.' This provides clear usage context, though it does not explicitly name alternative tools for exclusion, only implies them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return payload elements (from/to grade, action type, current/prior price targets) and asset-class limitations. It omits pagination defaults or rate limits, but as a read-only feed tool, the disclosed behavior is sufficient for safe 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?
Two efficient sentences with no fluff. The first sentence front-loads the core behavior; the second adds use cases and a caveat. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description compensates by enumerating the key data fields and return type (feed). It also covers intended use and asset-class exclusions. It does not describe the response envelope, but for a straightforward feed tool with self-documenting params, this is adequate.
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?
All 8 parameters have robust schema descriptions (100% coverage), so the baseline is 3. The description adds semantic context around the data fields (upgrades, downgrades, price targets) but does not provide additional syntax or usage details beyond what the schema already documents.
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 opens with 'Returns a feed of analyst rating actions for a ticker', specifying the exact verb, resource, and scope. It lists concrete inclusions (upgrades, downgrades, reiterations, price target changes) and an intended use case, clearly distinguishing it from sibling analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use guidance: 'Use for populating an Upgrades & Downgrades table or tracking rating action feeds.' It also gives an explicit when-not-to-use by stating ETFs and mutual funds rarely have analyst rating coverage, implying stock focus. This is strong usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 discloses that ETF/mutual fund data will be null, and enumerates the returned metrics (ownership percentages, number of institutions, insider transaction flows). For a read-only snapshot tool, this is adequate transparency, though it doesn't mention output format or error 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 two sentences, front-loaded with the core purpose, and every sentence earns its place. The first sentence states the action and scope; the second clarifies applicability and edge-case behavior. No redundant or vague language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter) and absence of an output schema, the description provides a solid overview of what is returned and when it is applicable. It lacks explicit return format and error handling, but for a high-level snapshot tool, the description is complete enough to guide correct use without overcomplicating.
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 already fully describes the single 'symbol' parameter, so baseline is 3. The description adds semantic value by explaining that the parameter's usefulness depends on asset type (stocks vs. funds), which helps the agent understand when the tool should be invoked.
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 a specific verb ('Returns') and resource ('high-level ownership snapshot'), and distinguishes itself from sibling tools by focusing on aggregated institutional and insider holdings rather than detailed breakdowns. It also specifies the asset types it applies to, which further clarifies its unique purpose.
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 usage context by stating the endpoint is 'primarily relevant for stocks' and explicitly notes that ETFs and mutual funds will return nulls. While it doesn't name alternative tools directly, the sibling list (e.g., get_holders_institutional) implies when more detailed data is needed, and the description's scope guidance effectively steers users.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It reveals that results are paginated, that empty results are returned for non-stocks, and enumerates the included data types (transaction descriptions, share counts, values, filer identity, ownership type). This is useful behavioral context, though it omits potential error/edge-case behaviors.
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 two sentences, front-loaded with the core purpose, and each clause adds value: scope, content, granularity comparison, and asset-class limitation. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers the essential behavioral and content aspects: pagination, scope, granularity, asset restriction, and returned data categories. It could be slightly more explicit about the response structure, but the information provided is sufficient for an agent to understand what the tool returns and when to call it.
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?
Input schema has 100% description coverage for all 5 parameters, so the schema already communicates parameter meaning. The description does not add parameter-level semantics beyond what the schema provides; its additional details concern output content rather than parameter usage. Baseline of 3 is appropriate.
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 opens with 'Returns a detailed, paginated list of insider transactions for a stock', which is a specific verb+resource+scope statement. It further distinguishes from sibling tool get_holders_insiders by noting it is 'More granular', making the tool's unique purpose clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly compares to get_holders_insiders ('More granular than get_holders_insiders'), signaling when to prefer this tool for more detailed insider transaction data. It also states a clear exclusion: 'Applicable only to stocks — for ETFs and mutual funds returns an empty result', which tells the agent when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return contents (pricing, Greeks, etc.), applicable underlying types (stocks/ETFs, not mutual funds), and implies a read-only operation via 'Returns a snapshot.' It could add detail on error behavior, but it is reasonably transparent.
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: first sentence states the core function and return fields, second sentence explains scope and exclusions, third sentence gives usage guidance. Every sentence is informative and there is no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description enumerates the primary return fields and clearly scopes the tool to single contracts. It could mention the exact structure of the response, but for a single-parameter tool, it is sufficiently complete.
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 coverage is 100%, so the baseline is 3. The description does not add additional meaning to contract_name beyond what the schema already provides (full identifier and example). Thus, no extra value is contributed.
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 tool returns a single option contract snapshot with a specific list of data fields. It distinguishes itself from sibling tools like get_options_chain by mentioning 'without reloading the full chain.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly provides use cases: 'Use for contract detail panels, deep-link flows, or refreshing a single contract without reloading the full chain.' It also states a limitation: mutual funds are not supported, which helps an agent decide when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears the full transparency burden. It discloses asset eligibility (stocks/ETFs, not mutual funds) and its role in checking options coverage, but doesn't detail return structure or error behavior. Still, for a simple retrieval tool the description adds meaningful 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?
Two sentences, front-loaded with the primary action. The second sentence lists concrete use cases without fluff. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description covers purpose, supported assets, and usage order. It is complete enough for an agent to invoke correctly, though it could optionally mention the result format for empty/no-coverage 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 coverage is 100% for the single 'symbol' parameter, so the schema already documents it. The description adds the context of 'single underlying symbol' and asset eligibility, but doesn't introduce syntax or format details beyond the schema, aligning with the baseline of 3.
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?
Description opens with a specific verb+resource: 'Returns the list of available option expiration dates for a single underlying symbol.' It clearly states the tool's scope (stocks/ETFs) and differentiates itself from siblings by positioning itself as the first step before get_options_chain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit usage context: 'Use as the first step before calling get_options_chain to discover valid expiration dates, build expiration dropdowns, or check whether a symbol has options coverage.' It also states an exclusion ('mutual funds are not supported'), giving clear when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It effectively discloses that the tool returns null for stocks and outlines the data categories included (asset allocation, sector exposure, aggregated valuation characteristics). This is useful context but does not discuss potential limits, data freshness, or error behavior, keeping it from a top score.
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 two concise sentences, front-loaded with the core action and resource, followed by a behavioral caveat and concrete use case. Every sentence provides value, and there is no redundancy or extraneous detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter read tool without an output schema, the description is complete: it explains what data is returned (portfolio composition, asset allocation, sector exposure, valuation characteristics), the fund vs. stock distinction, and the intended application context. This adequately fulfills the tool's information needs.
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 describes the single parameter 'symbol' as 'Asset identifier (ticker symbol)', and the description adds meaningful context by specifying that the symbol should be for a fund and that stock symbols will yield null fields. This goes beyond the schema's generic labeling and clarifies expected input.
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 tool 'Returns consolidated portfolio composition and holdings-level aggregates for a fund (ETF or mutual fund)', using a specific verb and resource. It distinguishes from sibling tools by focusing on aggregate-level holdings data rather than individual holdings or holders, and explicitly scopes to funds.
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 on when to use the tool ('Use to populate Holdings Overview or Portfolio Composition sections') and includes an explicit when-not-to-use condition ('For stocks, all fields return null'). However, it does not name an alternative tool for stocks, so it falls short of the explicit alternative guidance required for a score of 5.
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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