bde-score

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is clear. The description adds value by specifying the score range (0-100), the factors covered, and the limit of up to 25 stocks per market. This discloses important behavioral traits beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two short paragraphs. The first sentence states the purpose immediately, followed by a brief explanation of factors and a clear args section. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description appropriately focuses on input and behavior. It explains the limit of 25 stocks per market and the composite nature. It could have mentioned whether results are sorted or if there is pagination, but overall it is sufficiently complete for a simple parameterized tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining the 'market' parameter, its allowed values ('US', 'HK', 'CN', 'ALL'), default, and even a behavioral note about the result limit (25 stocks). This provides complete semantic meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns a composite BDE score (0-100) for stocks in a market, covering momentum, volatility, value, and quality. It distinguishes itself from sibling tools like get_esg_analysis and get_sector_analysis by focusing on a specific multi-factor score, though it could have explicitly contrasted with get_stock_analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any conditions, prerequisites, or exclusions. The agent is left to infer context from the tool name alone.

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

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

Annotations already indicate read-only and idempotent (readOnlyHint=true, idempotentHint=true). The description adds the important note that ESG data is derived from quantitative factors, not dedicated ratings, which provides valuable behavioral context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise: two sentences plus a note and an Args section. Every part serves a purpose, with the core function stated first. No unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (so no need to describe return values) and one well-described parameter, the description is largely complete. The examples with international tickers imply broad market coverage, but slight more context on scope might help.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero description coverage, but the description provides examples (AAPL, 00700) and explains the parameter as a stock ticker symbol. This adds meaning beyond the schema, though more detail (e.g., case sensitivity) could be helpful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool retrieves ESG analysis for a stock, with a specific verb 'Get' and resource 'ESG analysis'. The note differentiates it from dedicated ESG ratings, and it is distinct from sibling tools which cover other analyses.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there is no mention of when not to use it or how it differs from siblings beyond their names.

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

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

Annotations already provide safety profile (readOnlyHint, idempotentHint, destructiveHint). Description adds multi-market context but no additional behavioral details beyond what annotations imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences plus an args section; highly concise with no extraneous words, front-loading the main purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple input, output schema presence, and annotations, the description is adequate. Could mention output structure but not necessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by defining 'symbol' as company name or ticker and its role, adding meaningful interpretation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the action ('compare'), the resource ('BDE scores'), and the scope ('across US/HK/CN markets'), distinguishing it from siblings like get_bde_score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states when to use (comparing same company's BDE scores across markets), but does not explicitly mention when not to use or alternatives, though it is implied by sibling names.

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

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

Annotations already convey readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds that it shows average scores per sector, but provides no further behavioral context (e.g., caching, pagination, or side effects). This 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise: two sentences plus an args section. The purpose is front-loaded, and every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one optional parameter with default, output schema exists), the description covers the key aspects: what it returns (sector-level analysis, rankings, average scores) and valid market values. It is slightly lacking in explaining what 'BDE' stands for, but overall complete for the scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description lists the allowed values for the market parameter ('US', 'HK', 'CN'), going beyond the schema which only defines the type. This adds meaningful guidance for the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves sector-level BDE analysis and rankings, showing average scores per sector. It is specific and distinguishes itself from sibling tools like get_stock_analysis or get_esg_analysis which operate at stock or ESG level.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There is no mention of when not to use it or under what conditions it is appropriate, leaving the agent without contextual selection criteria.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds 'factor breakdown' as a behavioral detail but does not elaborate on other traits like rate limits, authentication, or output structure. It contributes modestly beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Very concise, two sections: action description and Args. Front-loaded with purpose. Every sentence adds value with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (detailed analysis) and presence of output schema, the description adequately covers input parameters and core purpose. It could mention that the output is a factor breakdown but output schema likely covers it. Siblings are distinct.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description provides full parameter semantics in the Args section, including examples for symbol (AAPL, 00700, SH600519) and market codes. This adds significant meaning that the schema lacks.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Get detailed BDE analysis for a specific stock including factor breakdown', specifying the verb, resource, and scope. It distinguishes from siblings like get_bde_score (which may be a summary) and get_esg_analysis (different type).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description implies usage for detailed single-stock BDE analysis but lacks explicit guidance on when to use versus alternatives, such as get_bde_score or get_multi_market_comparison. No exclusions or non-usage conditions provided.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the 'top 50' limit, which is useful context beyond annotations. However, it does not disclose potential rate limits, data freshness, or how the BDE score is calculated, leaving some behavioral ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences for the purpose plus two parameter entries. Every sentence adds value, and the structure front-loads the key action. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (2 optional parameters, simple screening) and the presence of an output schema, the description is complete. It covers the core functionality, parameter details, and return limit. Annotations handle safety and idempotency. Nothing critical is omitted.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully carries the burden. It explicitly lists allowed values for market ('US', 'HK', 'CN', 'ALL') and provides range and default for min_score (0-100, default 70), adding meaning beyond the raw schema. This is comprehensive for a simple parameter set.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'screen' and resource 'stocks', specifying the BDE score threshold criterion and return limit of 50. However, it does not explicitly distinguish this tool from siblings like get_bde_score or get_esg_analysis, which could cause confusion about when to use this screener vs. other tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for screening stocks by BDE score, but provides no explicit guidance on when to use this tool versus alternatives (e.g., get_stock_analysis for individual stocks). There are no exclusions or prerequisites stated.

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