AgentScrape

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

Discloses key behavioral trait: persistence of cookies and localStorage. Without annotations, this helps agents understand statefulness. Could mention session expiration behavior or resource limits, but adequate for the tool's simplicity.

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?

Single sentence that is efficient and front-loaded with the core purpose. 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 low complexity (one optional parameter, no output schema), the description covers the essential behavior. Missing return value (likely a session ID), but implied for creation tools.

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?

Input schema covers 100% of parameters with descriptions. The tool description adds no additional explanation beyond schema. Baseline 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 the tool creates a stateful browser session that persists cookies and localStorage. It uses a specific verb ('Create') and resource ('browser session'), and distinguishes from stateless sibling tools like scrape_webpage.

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?

Implies usage for scenarios needing persistence across multiple calls, but lacks explicit when-not-to-use or alternative recommendations. However, the context of sibling tools provides implicit guidance.

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 beyond a title, the description carries full burden but only lists extracted fields, not behavioral traits like HTTP requests, destructiveness, or rate limits. It is adequate for a simple tool but lacks depth.

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 with no wasted words, front-loading the purpose and enumerating details 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?

Given the tool's simplicity (one parameter, no output schema), the description adequately covers what metadata is extracted, though it lacks details on return format or edge cases.

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 one parameter 'url' with 0% description coverage, and the description does not mention the parameter, leaving the agent to infer its meaning solely from 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 verb 'Extract' and the resource 'page metadata', enumerating specific types (title, description, Open Graph, etc.), making it distinct from sibling tools like scrape_webpage or screenshot_webpage.

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 metadata extraction but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or when-not-to-use scenarios.

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?

Minimal annotations (only title), description does not disclose authentication needs, error handling, or side effects. Missing behavioral traits beyond 'AI-powered' and 'returns JSON'.

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, 28 words, front-loaded with key information, 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?

Lacks details on return format beyond JSON, error handling, and purpose of wait_ms/wait_for parameters despite moderate complexity (5 params, no output schema).

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?

60% schema coverage provides baseline; description adds that output matches prompt/schema but does not explain wait_ms or wait_for parameters.

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 describes extraction of structured data from webpages using natural language, distinguishing it from siblings like scrape_webpage (raw HTML) and extract_metadata (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?

Implies usage for structured data extraction but lacks explicit guidance on when to use vs. alternatives, 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?

Important behavioral details are missing: the description does not explain atomicity semantics, error handling, session dependencies, or that steps are sequential with no rollback. With no annotations to supplement, the agent is left guessing about side effects and failure behavior.

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 concise, using two sentences to state purpose and constrain step count. However, it lacks structure to guide understanding of nested parameters or usage context.

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 the tool's complexity, the description omits return format, error handling, session management, and detailed step configuration. With no output schema and minimal annotations, the description leaves significant gaps for an AI agent.

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?

Only one of four parameters (steps) has a schema description. The tool description does not elaborate on viewport, session_id, or persist_session, leaving them ambiguous. The step limit is mentioned but not explicitly linked to the steps array parameter.

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 executes multi-step browser workflows atomically, listing specific actions (navigate, click, etc.), which gives a concrete understanding. It distinguishes from sibling tools that are single-action tools for scraping, screenshotting, etc., by specifying the orchestration nature and step limit.

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 lacks explicit guidance on when to use this tool versus siblings. It does not state prerequisites (e.g., session creation) or when to avoid it (e.g., for simple single actions). Usage context is only implied by the feature list.

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 only include a title, so the description bears full responsibility. It does not disclose behavioral traits like rate limits, authentication needs, error handling, or that the tool executes JavaScript. The pay-per-call note is a billing detail, not a behavioral trait.

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 the core purpose. No redundancy. The cost note is secondary but concise. Efficient use of 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?

With 5 parameters and no output schema, the description lacks details on return format structure, size limits, error handling, or dynamic content behavior. It is minimal for a tool of this complexity.

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%, so baseline is 3. The description adds little beyond listing format options, which are already in the schema. No additional parameter meaning is provided.

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 scrapes any webpage and returns content in multiple formats (markdown, html, text, json). This differentiates it from sibling tools like screenshot_webpage (screenshots) or extract_metadata (metadata only).

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 prerequisites, exclusions, or compare with sibling tools. The 'Pay-per-call' note hints at cost but does not clarify usage context.

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 lack readOnlyHint, destructiveHint, etc. Description adds viewport and full-page support but omits details like permissions, error handling, or what happens on failure. No contradictions 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?

Single sentence, front-loaded with purpose. Efficient and to the point without unnecessary 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?

Tool is straightforward, but description lacks information about the output format (e.g., base64 PNG, file path) and no output schema. Adequate for basic usage but incomplete for full agent understanding.

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?

Only 20% of parameters have schema descriptions. Description adds meaning for viewport and full_page but fails to explain wait_ms and wait_for, which are crucial for timing. Schema coverage is low, and description does not fully compensate.

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 captures a PNG screenshot of any webpage, with support for viewports and full-page mode. It effectively distinguishes from sibling tools like scrape_webpage (text extraction) and extract_structured_data.

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 screenshots with various viewports but provides no explicit guidance on when to use this tool vs alternatives, no 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.