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

No annotations provided. The description does not disclose side effects, API key usage, or what actions the autonomous loop performs (e.g., browsing, scraping). The agent is left uninformed about the tool's behavior beyond the name.

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—concise but under-informative. It lacks structure and omits crucial details, so it is not appropriately sized for the tool's complexity.

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 having an output schema, the description fails to provide adequate context for a multi-step autonomous research tool. It omits workflow, prerequisites (e.g., API key authentication), and expected outcome, leaving the agent with significant ambiguity.

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%. The description adds no context for the three parameters: 'topic', 'depth', and 'api_key'. The meaning of 'depth' (number of iterations? scope?) and the role of 'api_key' remain undefined, placing high burden on the schema which provides no 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 uses a clear verb ('Run') and identifies the resource ('autonomous multi-step research loop'). However, it does not distinguish this tool from siblings like 'deep_research' or 'research_topic', which may also involve research loops.

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. The description lacks context for when a multi-step research loop is appropriate compared to a single search or simple extraction.

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 provided, the description carries the full burden of disclosure. It mentions the use of Playwright and a headless browser, but fails to describe key behaviors such as timeouts, error handling, what each action returns in detail (e.g., screenshot viewport vs full page), or authentication implications.

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 relatively short and front-loaded with the core purpose. The actions are presented in a clear bullet-like list, but the structure could be improved by grouping related information or providing example usage.

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 (multiple actions, 4 parameters, no output schema, and 0% schema coverage), the description is insufficient. It lacks important details like return types for each action, error handling, prerequisite conditions, and constraints on the URL.

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 0% description coverage, so the description must compensate. It lists possible action values and hints at the instruction format for click/type, but does not explain the 'api_key' parameter or provide details on how to use each action fully.

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 that the tool browses a webpage using a headless Chromium browser and lists the available actions. It distinguishes itself from siblings like 'web_search' (which returns search results) by mentioning interactive actions (click, type), but could explicitly say it handles dynamic JavaScript content.

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 provide any guidance on when to use this tool over alternatives like 'extract_article' or 'web_search'. It lists actions but does not explain the context in which this tool is preferred (e.g., for interactive pages requiring JS execution).

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 must fully disclose behavior. It outlines the multi-step, autonomous process but omits details like authentication requirements (though api_key parameter hints at it), rate limits, or side effects. It adds moderate context beyond the name.

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, front-loaded sentence with no wasted words. It efficiently conveys the core function.

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 output schema exists, so return values are covered, but the description lacks details on parameter usage and depth of research. For a complex multi-step tool, more context on the process and parameter semantics is needed.

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 does not explain any of the three parameters (topic, depth, api_key). With 0% schema description coverage, the description should compensate but fails to clarify what depth means or how api_key is used.

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 conducts autonomous multi-step research, searching, reading, and synthesizing findings. It distinguishes from simpler siblings like web_search and browse_page, though it overlaps with autonomous_research and research_topic.

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 when to use this tool (for multi-step synthesis) but does not explicitly state when not to use it or mention alternatives. Siblings like web_search or browse_page are not referenced for exclusion.

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?

Discloses key behavioral traits: stripping of navigation/ads and return of specific fields (title, text, counts). Provides useful context beyond raw schema, though no error or auth details.

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, front-loaded with purpose, no fluff. 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?

Return values are well described, but missing details on error handling, input validation, and the role of api_key. Adequate for a simple tool but leaves 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?

With 0% schema coverage, the description adds no meaning to the url or api_key parameters. No format or usage hints for either.

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?

Clearly states the tool extracts article text from a URL, specifies stripping of navigation/ads, and lists return fields. Differentiates from siblings like web_search or browse_page.

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 on when to use this tool vs siblings like browse_page or research_topic. Does not mention prerequisites or 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?

No annotations provided. The description discloses that no API key is needed, which informs authentication expectations. However, it does not mention rate limits, error handling, or data format, which are relevant behavioral traits.

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 sentence that is front-loaded and contains no redundant information. Every phrase serves a 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?

For a simple tool with no output schema and no annotations, the description covers the essential: data source, authentication, and core function. It could mention output format but is sufficient for basic usage.

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 description must compensate. The description clarifies the api_key parameter is unnecessary but does not add meaning to the location parameter beyond the schema. Partial value added.

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 gets current weather using a specific service (wttr.in) and notes no API key is needed. It distinguishes from sibling tools (research/browsing) by being weather-specific.

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 weather retrieval but provides no explicit when-to-use or when-not-to-use guidance. Since siblings are unrelated, no alternatives are mentioned, leaving context clear but lacking 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 must carry full burden. It discloses that the tool performs search and extraction, and that depth controls number of pages. However, it does not mention potential side effects, authorization needs, rate limits, or behavior on errors. For a multi-step workflow, more detail is needed.

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 with clear structure: first states overall workflow, second describes the depth parameter. Could be slightly more structured (e.g., list steps) but remains efficient without verbosity.

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 (multi-step, 3 parameters, no output schema or annotations), the description covers the process and return format ('compiled research brief with sources') but lacks detail on error handling, limits, or the omitted api_key parameter. It is adequate but not 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 0% (no parameter descriptions in schema). The description explains 'query' implicitly and 'depth' explicitly (controls pages 1-5), but omits any mention of the 'api_key' parameter, leaving it undocumented. This is a significant gap.

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 it's a multi-step research workflow that combines web search and extraction to produce a research brief. This distinguishes it from pure search (web_search) or extraction (extract_article) tools. However, it does not explicitly differentiate from autonomous_research, which might have overlapping 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 implies usage for quick research by controlling depth, but does not provide explicit guidance on when to use this tool versus alternatives like deep_research or autonomous_research. No when-not or alternatives mentioned.

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 provided, the description bears full burden. It discloses that no API key is required and returns titles, URLs, and snippets, but lacks details on rate limits, result limitations, or error handling. Merely adequate for a search tool.

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 exceptionally concise with two short sentences, front-loading the core action and return format. 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.

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

For a simple search tool with no output schema and 3 parameters, the description covers the basic purpose and return format but lacks parameter behavioral details and usage context. Partially adequate but not full.

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 0% and the description adds no parameter-specific information. It does not explain the 'query' parameter, the 'limit' default or behavior, nor the purpose of 'api_key' (beyond stating no API key required). Parameters remain largely mysterious.

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 performs web search using DuckDuckGo, specifying the resource (web) and action (search). It distinctively sets it apart from sibling tools like get_weather or browse_page.

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 general web searches but provides no explicit guidance on when to use this tool versus siblings like deep_research or research_topic. No exclusions or alternatives are mentioned.

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