search-router

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 return behavior (server status and echo) but gives no details about response format, errors, or whether authentication is needed. This is minimal but not misleading.

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, using only two sentences with no unnecessary words. Everything contributes to the tool's 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?

The tool is simple with one optional parameter and no output schema. The description gives the basic return behavior but lacks specifics about the status format or how the echo is returned. It's adequate but not rich.

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 describes the echo parameter fully, and the description merely repeats 'optional echo'. Baseline score of 3 because schema coverage is 100% and description adds no new 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 the tool's purpose as a health check that returns server status and optionally echoes a string. It distinguishes itself from sibling tools, which are all unrelated utilities.

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 about when to use this tool or alternative approaches. The description simply states what it does without indicating prerequisites or 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?

With no annotations, the description carries the behavioral burden. It candidly discloses the cache dependency, the specific SEARCH_CACHE_MISS error on failure, and the fixed cost per call – all useful behavioral details beyond the tool name. It doesn't cover every aspect (e.g., rate limits, output format) but covers the most distinctive behaviors.

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 tight two-sentence summary with the most critical info (cache-only, error, price) front-loaded. Every word 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.

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

The tool is a straightforward cached lookup with 6 params and no output schema. The description covers the cache behavior and error, but does not describe what a successful response looks like or how to interpret results. Given the lack of an output schema, some return-format guidance would improve completeness, but the essential usage context is present.

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% (all 6 parameters have descriptions), so the schema fully documents parameter semantics. The description adds no additional parameter-specific information, landing at the baseline score of 3.

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 states the tool is a 'cache-only lookup', which clearly identifies a specific operation (lookup) and distinguishes it from sibling search tools by the cache-only constraint. However, it relies on the tool name to imply the resource (web search), and 'lookup' is slightly less explicit than '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 'cache-only' qualifier implies this tool should be used when cached results are acceptable, and the error message hints that live tools like web_search_simple or web_search_deep might be alternatives. However, no explicit when-to-use or when-not-to-use guidance is given, and sibling tools are not mentioned by name.

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?

With no annotations, the description carries the transparency burden. It discloses the fixed cost per call and the external provider (Exa), and hints at synthesis behavior. However, it does not state whether the tool is read-only, rate limits, or what the response format will be, which are significant behavioral gaps.

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 conveys purpose, provider, key capabilities, and cost. There is no unnecessary wording or redundancy, making it highly concise and front-loaded.

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 complete schema coverage, the description lacks crucial context for a tool with no output schema. It never states what the tool returns (e.g., a list of results vs. a synthesized narrative) or explains the operational difference from sibling search tools. This is a notable gap for a feature-rich search 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?

The schema already documents all six parameters with descriptions, so baseline is 3. The description adds value by indicating that queries support boolean operators and that results involve multi-source synthesis, giving extra meaning to the query parameter and overall behavior 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 identifies this as a deep research search tool via Exa, with explicit scope (academic, boolean, multi-source synthesis). The word 'deep' distinguishes it from the sibling tools, making its purpose 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.

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

The description implies usage for deep research (academic, multi-source synthesis) but does not explicitly state when to use this tool versus web_search_simple, web_search_medium, or web_search_cached. No exclusions or alternatives are mentioned, leaving the decision to inference from the name.

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?

No annotations are present, so the description carries the full burden. It discloses the back-end engine (Brave) and the fixed cost ($0.008/call), but does not detail expected response format, rate limits, or other behavioral traits. The basic nature of a search tool is implied, but more explicit disclosure would improve transparency.

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, well-structured sentence that front-loads the core purpose ('Default web search via Brave') and appends the cost detail. There is no wasted wording, making it highly efficient.

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 schema fully documents parameters and the output is obviously a list of search results, the description provides adequate tool-level context (engine, cost, scope). It omits any mention of return structure, which would be nice but is not essential for a straightforward search 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?

Schema description coverage is 100%, with each parameter (query, country, language, freshness, max_results, search_type) already documented clearly. The tool description adds no additional parameter-level meaning, so the baseline 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?

The description clearly states it is a 'Default web search via Brave' and specifies it is for 'ambiguous or general queries.' This identifies a specific verb (search), resource (web via Brave), and scope, distinguishing it from the sibling tools (e.g., web_search_deep, web_search_simple).

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 by framing this as the default search tool for ambiguous or general queries. It does not explicitly list exclusions or name alternative tools for other cases, but the 'default' qualifier strongly implies its place among siblings.

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?

No annotations are provided, so the description carries the burden. It adds the provider (Brave) and the fixed cost of $0.003/call, which is useful behavioral context. However, it does not disclose the result format, pagination, or error behavior beyond what 'web search' implies.

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?

A single, front-loaded sentence with no wasted words. It efficiently conveys purpose, use cases, and pricing, making it easy to scan.

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 comprehensive schema (all 6 params with descriptions) and the simple nature of the tool, the description covers essential context: purpose, use cases, provider, and cost. It doesn't explain return values explicitly, but the term 'web search' reasonably implies a list of results.

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 100% field description coverage, so each parameter is already documented clearly. The description adds no parameter-specific details, so it does not elevate beyond the baseline established by 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 states 'Simple factual web search via Brave' – a clear verb (search), resource (web), and provider (Brave). It lists use cases (lookups, definitions, short queries) that differentiate it from deeper search siblings, though it doesn't 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?

Provides clear use-case context: 'lookups, definitions, short queries' – indicating it is for simple, factual queries. This guides when to use, but doesn't explicitly state when not to use or mention alternative tools like web_search_deep.

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