technical

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds useful context about the return format ('readable summary and structured metadata'), which goes beyond the annotations. However, it does not disclose potential error conditions, rate limits, or authentication requirements. With annotations covering safety, a score of 3 is appropriate.

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 a single sentence that efficiently conveys both the action and the output. It is front-loaded with the verb and resource, and every phrase adds value. No redundant or irrelevant content.

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 1-parameter read-only fetch tool without an output schema, the description adequately covers the purpose and return format. However, it does not clarify how this tool differs from the closely named sibling 'get_technical_analysis', which could cause selection ambiguity. More context on distinguishing factors would be helpful.

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 schema parameter description fully covers the parameter semantics (ticker or company name with examples). The tool description repeats this information without adding new details. Since schema coverage is 100%, the baseline is 3, and there is no extra value from the description.

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 fetches the full technical record for one stock, with the resource being 'stock technicals' and the verb 'fetch'. It also specifies identification via ticker or company name. However, it does not distinguish itself from the sibling 'get_technical_analysis', which may overlap in functionality.

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 does not mention any exclusions, prerequisites, or comparisons to other tools such as 'screen_technicals' or 'search'. The only implied usage is that it is for a single stock, but no explicit when-to-use guidance is given.

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 read-only, idempotent, and non-destructive behavior. The description adds valuable context: data comes from a precomputed cache (potential staleness) and enumerates the exact output fields, which is helpful given no output schema. No contradiction with 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 two sentences long, front-loaded with the core purpose, and each detail (markets, cache, indicators, input flexibility) earns its place. No redundant or fluff content.

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 has one well-documented parameter and no output schema, the description adequately covers the input (tickers/names), market scope, data source (cache), and output contents (indicator list). It omits edge cases like partial failures, but for a simple getter, this is sufficient.

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 schema already documents the 'tickers' parameter fully (tickers or KR/EN comments, up to 25). The description repeats this and adds the list of supported markets, but that is supplementary context rather than new parameter syntax. Baseline of 3 is appropriate due to full schema 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's purpose: fetching precomputed technical levels for covered stocks, and it lists specific indicators (price, MAs, RSI, etc.). It distinguishes from siblings by focusing on data for given tickers, but does not explicitly contrast with screen_technicals or search.

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 retrieving technical data for specific covered stocks and mentions the precomputed cache, suggesting suitability for quick lookups. However, it does not explicitly say when to use this tool over screen_technicals or search, nor does it mention limitations like stale cache data.

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, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds that results include the latest signal score and trend 'when available', which is useful. However, it doesn't disclose pagination behavior or the default limit, which could affect agent expectations.

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 two concise sentences that front-load the core purpose ('Browse the covered universe') and efficiently convey filters and output content. No unnecessary words or 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 four optional parameters, no output schema, and annotations covering safety, the description provides sufficient context for a listing tool: it states filters and result fields. Minor gaps like limit default and pagination are not critical but would add completeness.

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 description explicitly maps filters to market, sector, and ticker/name, clarifying the purpose of query, market, and sector parameters. Schema coverage is low (25%), so this compensation is valuable. The 'limit' parameter is not described in the description but is already documented in 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 browses the covered universe with optional filters, which matches the title 'List covered stocks'. It distinguishes from siblings like get_technical_analysis and screen_technicals by focusing on the universe listing with signal scores and trends, but does not explicitly name alternatives.

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 usage context is implied ('Browse the covered universe') but there is no explicit guidance on when to use this tool versus siblings like search or screen_technicals. It doesn't state exclusions or prerequisites, which would help an agent decide between tools.

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, covering the safety profile. The description adds context beyond annotations by specifying the universe is 'covered' and by explaining the intent of different sort values, which is useful behavioral information. It does not contradict 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 two sentences, front-loaded with the action and resource, followed immediately by useful sort guidance. There is no filler or redundant information, earning its place efficiently.

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 screening tool with 9 optional parameters and no output schema, the description covers the core purpose and sort strategies but omits details about how filters interact, the effect of the limit parameter, or what a result entry looks like. This is adequate for basic use but not fully complete for complex screening scenarios.

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 schema description coverage at only 22%, the description must compensate. It adds meaning to the sort parameter by explaining which sorts to use for pullbacks/oversold vs leaders, but it does not explain filter parameters like rsi_above, rsi_below, min_signal_score, or max_signal_score beyond their names. Partial compensation leaves gaps.

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 trend, signal score, RSI, market, and sector, providing a specific verb and resource. However, it does not explicitly differentiate from sibling tools like get_technical_analysis or search, relying on the reader to infer that this is a screening rather than a lookup tool.

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?

It provides actionable guidance for sort values, mapping 'below_high'/'rsi_asc' to pullbacks/oversold stocks and 'signal_desc'/'momentum_desc' to leaders. This gives clear context for when to use particular sort options, though it does not explicitly state when to prefer this tool over siblings or mention exclusions.

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. The description adds context beyond these by specifying return fields (ids, titles, URLs, short technical snippets) and language scope (KR/EN). This provides useful behavioral transparency 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 two sentences, front-loaded with purpose and return value, and includes a practical recommendation to pair with fetch. Every word contributes to understanding the tool 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?

For a simple search tool with two params and no output schema, the description explains purpose, search scope, return fields, and relationship to fetch. Combined with full schema coverage and clear annotations, it provides adequate context for an agent to invoke 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 100%, with descriptions for both query and limit. The description adds minimal semantic value, reinforcing that query searches by company name or ticker but not adding syntax or additional 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's function: 'Search the covered stock universe by company name or ticker (KR/EN).' It specifies the resource (covered stock universe), search criteria (company name or ticker, KR/EN), and return contents (ids, titles, URLs, snippets). This differentiates it from siblings like fetch (full record) and list_covered_stocks (likely whole universe).

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 clear context for when to use search ('by company name or ticker') and recommends pairing with fetch for a full record, implying search returns snippets. However, it doesn't explicitly mention when to use list_covered_stocks or screen_technicals, so it lacks complete exclusion guidance.

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