technical

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

Annotations already indicate readOnlyHint=true (safe read) and openWorldHint=false. The description adds that it returns a readable summary plus structured snapshot in metadata, providing context beyond what annotations offer, with no contradictions.

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, no fluff, front-loaded with the core purpose. Every word adds value, making it concise and well-structured.

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 (1 param, no output schema, good annotations), the description is sufficient. It explains the input and output behavior, though 'structured snapshot in metadata' could be slightly ambiguous. Still, it's largely complete.

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 coverage is 100% with only one parameter, and the description largely repeats the schema's explanation about ticker/company name. It adds minimal new meaning, so baseline score of 3 is appropriate.

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 verb 'Fetch', resource 'full technical record for one stock', and specifies identifier types (ticker or company name). It distinguishes from siblings by focusing on a single stock's record with a summary and metadata.

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 does not explicitly state when to use this tool versus alternatives like get_technical_analysis. It implies it is for a single stock by id, but lacks explicit guidance on when not to use it or which sibling to prefer.

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 indicate readOnlyHint and no openWorldHint. The description adds context: data is from a 'precomputed cache' (not real-time), fuzzy name resolution, and lists all return indicators. This provides useful behavioral insight 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?

The description is dense with useful information and front-loaded. It is not overly verbose given the amount of detail, though a slight trim could improve conciseness.

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?

Despite no output schema, the description thoroughly enumerates all returned indicators and notes the cache source. Combined with the single-parameter input, it provides a complete picture of what the tool does.

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 coverage is 100%, but the description adds significant value by clarifying that tickers can be exact tickers or company names in multiple languages, providing examples, and specifying the max count (25).

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

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

The description clearly states the tool returns technical levels for stocks, listing specific indicators and coverage. It distinguishes from sibling tools by specifying it focuses on precomputed technical analysis for multiple markets, and hints at its use case (pricing up a company list).

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 explains input flexibility (tickers or names, multiple languages) and batch processing, and suggests a use case. However, it does not explicitly compare to similar tools like screen_technicals, leaving some ambiguity about when to use this over alternatives.

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 readOnlyHint=true, so no destructive behavior. The description adds value by explaining output rows contain technical signal score and trend (possibly null), and that results are ordered by market cap. No contradictions.

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?

Three sentences cover the tool's function, output details, and usage hint with no redundancy or fluff. Front-loaded with core 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 no output schema, the description explains the return fields (signal score and trend) and ordering. It lacks mention of pagination or limit constraints but is sufficient for an agent to use the tool correctly.

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 50% (limit and query have descriptions; market and sector lack descriptions). The description adds context by mentioning filtering by market, sector, and query, but does not elaborate on market enum values or sector format. It partially compensates for low coverage.

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

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

The description clearly states the tool lists covered stocks, optionally filtered by market, sector, or name/ticker query, and orders by market cap. It distinguishes itself from siblings by directing the agent to call get_technical_analysis for deeper 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 explicit guidance to use this tool to discover available stocks before calling get_technical_analysis for full levels. It does not contrast with all siblings (e.g., fetch, screen_technicals, search) but gives clear context for 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.

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

Annotations already declare readOnlyHint=true, so no destructive behavior. Description adds context: returns 'full technical snapshot' and is based on precomputed data. No contradictions, and additional behavioral context is provided.

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?

Description is a single paragraph of three sentences, front-loading purpose and key usage. It is efficient with no fluff, though could be slightly more structured. Each sentence contributes value.

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?

Covers main filters and sort options with examples, but lacks details on output structure beyond 'full technical snapshot', pagination, or limit behavior. For a complex tool with 9 params and no output schema, some gaps remain.

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 coverage is 56% (5 of 9 params have descriptions). The description compensates by explaining all filter groups (trend, signal-score range, RSI range, market, sector) and by illustrating sort usage with concrete examples, adding meaning beyond the schema.

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

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

The description clearly states the tool screens the covered universe by precomputed technical conditions, listing filterable attributes and sort options. It specifies verb, resource, and scope, and the examples differentiate it from siblings like get_technical_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?

Provides clear usage patterns with sort examples and recommended scenarios (e.g., 'use sort below_high to surface oversold candidates'). However, it does not explicitly contrast with sibling tools or state when not to use.

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, indicating no destructive behavior. Description adds context that the tool returns a short technical snippet, but overall behavioral transparency is adequately covered by 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?

Two concise sentences that front-load the purpose and include essential details without unnecessary words. Every sentence adds value.

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?

For a simple search tool with good schema coverage and annotations, the description sufficiently covers purpose, parameters, return values, and complementary tools. No gaps.

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 coverage is 100%, but description adds value by explaining that query is a substring search supporting Korean/English. This goes beyond the schema's description for query provided in the schema itself.

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 searches the covered stock universe by company name or ticker, and specifies the return fields (id, title, URL, technical snippet). This distinguishes it from siblings like fetch and get_technical_analysis which focus on retrieving full records.

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 advises pairing with fetch for full technical records, providing some guidance on when to use this tool versus alternatives. However, it does not explicitly state when not to use it or provide context for other siblings like list_covered_stocks or screen_technicals.

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