AgentScrape

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

Describes statefulness and persistence, but lacks details on lifecycle, expiration, or side effects. No annotations beyond title; bar is moderate.

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, no fluff, front-loaded with action and 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?

Sufficient for a simple tool with one optional parameter and no output schema. Could mention return value (session ID) but not required.

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 covers 100% of parameters with adequate descriptions. The description does not add meaningful 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?

Clearly states the tool creates a stateful browser session for persisting cookies and localStorage. Distinguishes from sibling tools which are for extraction, scraping, screenshots, and workflows.

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 across multiple scrape/workflow calls, but does not provide explicit when-to-use or when-not-to-use guidance, nor 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?

The description adds value by enumerating what metadata is extracted (Open Graph, Twitter cards, JSON-LD, etc.). However, it does not disclose behavioral traits such as authentication needs, rate limits, error handling for invalid URLs, or any side effects (which are minimal). Annotations provide no readOnlyHint or destructiveHint, so the description carries the full burden and only partially fulfills it.

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, front-loaded with the action, and lists the extracted items efficiently. No redundancy or 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?

The description lists what metadata is extracted but omits output format (e.g., JSON object structure) and any return value details. Given no output schema, the description should partially cover this. 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?

The single parameter 'url' has no description in the schema (0% coverage). The tool description does not add any semantics about the URL format, restrictions, or required prefixes. It fails to compensate for the low 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 verb 'extract' and the resource 'page metadata', listing specific metadata types (title, description, Open Graph, etc.). This distinguishes it from sibling tools like `extract_structured_data` and `scrape_webpage` which have different scopes.

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 versus alternatives. No context about prerequisites, limitations, or when to avoid using it. For example, it does not mention that this tool only extracts metadata and not full page content, which could be inferred but not explicitly stated.

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 provide no safety hints. The description lacks disclosure of potential issues like rate limits, costs, latency, or accuracy of AI extraction. It does not state whether the tool modifies the page or is read-only.

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 wasted words. Every sentence adds value: one explains what it does, the other the output format.

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 core functionality but lacks details on wait parameters, error handling, limitations (e.g., dynamic content), and output guarantees. Adequate but not comprehensive given 5 parameters and 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?

Schema coverage is 60%; url, prompt, and schema have descriptions. The description adds context that prompt and schema are complementary but does not explain wait_ms or wait_for, leaving 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 extracts structured data from webpages using AI and natural language, returning JSON. It distinguishes from siblings like scrape_webpage (unstructured) and extract_metadata (metadata-focused).

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 use for structured extraction via natural language or schema, but does not explicitly state when to avoid it or compare to alternative tools like scrape_webpage or screenshot_webpage.

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 (no readOnly/destructive hints), description carries full burden. It mentions 'atomically' and 'Up to 20 steps' but fails to disclose failure behavior, session dependencies, or side effects like page state changes. Significant gaps in behavioral disclosure.

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 verb and resource. Concise but not overly brief; every part adds information. 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 moderate complexity (4 params, no output schema, nested objects in steps), the description is inadequate. It does not explain return behavior, session requirements, or viewport effects. The user is left without enough context 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 only 25% (only 'steps' has a description). The tool description adds value by listing possible actions for steps, but does not explain other parameters like 'viewport', 'session_id', or 'persist_session'. A baseline 3 is appropriate as the description 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?

Description clearly states 'Execute a multi-step browser workflow atomically' and lists specific actions (navigate, click, etc.), distinguishing from siblings that are single-action tools like screenshot_webpage or 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 lacks explicit guidance on when to use this tool vs single-action alternatives. 'Atomically' implies one-shot execution but does not mention that for individual actions, other tools should be used. No 'when not to use' or alternative references.

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 title, the description carries full burden. It discloses 'pay-per-call' but omits important behavioral traits such as rate limits, authentication requirements, handling of JavaScript-heavy pages, or any destructive potential. Minimal disclosure.

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 with no wasted words. Front-loads the main action and output, and adds context (pay-per-call) 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 tool with 5 parameters and no output schema, the description is incomplete. It does not explain return structure for JSON, error handling, or how parameters like wait_for or viewport affect scraping. More context is needed for an agent to use it effectively.

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 the schema already documents all parameters. The description adds little beyond restating output formats. It does not provide deeper meaning or usage tips for parameters like wait_ms or viewport.

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 action ('scrape') and resource ('any webpage'), and specifies output formats (markdown, html, text, json). It distinguishes itself from sibling tools like screenshot_webpage or extract_metadata, as it focuses on returning 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 mentions 'pay-per-call' but does not provide explicit when-to-use or when-not-to-use guidance relative to alternatives like extract_structured_data or extract_metadata. The usage context is implied but not elaborated.

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 provide no behavioral hints (readOnlyHint, destructiveHint). The description does not disclose whether the tool requires an existing browser session, or any side effects like network requests. For a read-like operation, stating it is non-destructive would help.

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 that efficiently conveys the core functionality and supported features. No superfluous text.

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, no output schema, and low schema coverage, the description is too brief. It lacks details on return format (e.g., base64 PNG), dependency on create_browser_session, and behavior of timeouts or errors.

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 low (20%, only full_page documented). The description adds value by explaining viewport options and full-page mode, but does not clarify wait_ms or wait_for parameters. It only partially compensates for the schema 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 captures a PNG screenshot of a webpage, with specific support for viewports and full-page mode. It distinguishes well from sibling tools like scrape_webpage (text extraction) and create_browser_session (session management).

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 visual screenshots but lacks explicit guidance on when to use versus alternatives (e.g., scrape_webpage for text, run_workflow for automation). No exclusions or prerequisites mentioned.

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