Scrapi MCP Server

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

With no annotations, the description carries the transparency burden. It conveys a read-only operation via 'Retrieve' but offers no additional behavioral detail such as authentication requirements, error behavior, or response format. While safe for a read tool, it adds minimal context beyond the obvious.

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 efficiently lists the tool's purpose and options. Every word earns its place, with clear enumeration of the retrievable billing categories. No wasted 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's moderate complexity (3 params, 1 required, full schema descriptions) and no output schema, the description provides enough context: it names the four billing categories, and the schema fills in parameter details. It doesn't explain return structures, but for a simple retrieval tool 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?

Schema coverage is 100%, so the schema already documents all parameters and their enums. The description mentions categories like 'daily usage history' and 'spending limits' that map to action values, but it doesn't add new semantic meaning beyond what the schema already provides. Baseline 3 applies.

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 the specific verb 'Retrieve' and clearly identifies the resource as 'MCP billing information,' then enumerates distinct subtypes (subscription details, available plans, daily usage history, spending limits). This distinguishes it from sibling tools like get_usage by focusing on billing-specific categories.

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 accessing billing data but provides no explicit guidance on when to choose this over get_usage or other siblings. It lacks exclusions or alternative tool references, relying on the term 'billing' to indicate context. This is implied usage rather than clear directive.

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 behavioral disclosure. It explicitly enumerates the returned fields (current plan, subscription credits, purchased credits, total remaining credits), which is informative. It does not explicitly state read-only behavior or auth requirements, but for a zero-parameter query tool, the return specification is a strong 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?

The description is two concise sentences, front-loaded with the primary purpose, and contains no filler or redundant information. It earns its place by stating both the action and the return details.

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 zero-parameter schema, no output schema, and no annotations, the description provides sufficient detail about the tool's behavior and return data. It is complete for an agent to understand what to expect. The only minor omission is an explicit read-only statement, but the nature of the tool makes it evident.

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 tool has zero parameters, and the schema coverage is 100% (trivially, since there are no properties). The description adds meaning by explaining what the response contains, which is valuable for an agent deciding whether to call this tool.

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 with a specific verb ('Check') and resource ('API usage and remaining credits'), and details the return content. It distinguishes itself from sibling tools like get_billing by focusing on credits versus billing information.

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 clear context for when to use this tool (when you need to check API usage and remaining credits) and what it returns. It does not explicitly mention when not to use it or contrast with alternatives like get_billing, but the context is straightforward and not misleading.

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?

Since no annotations are provided, the description carries the burden of behavioral disclosure. It indicates this is a status check (likely read-only) and lists the data shown, which gives some behavioral insight. However, it does not mention any side effects, permissions, or output format 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?

The description is two concise sentences, front-loaded with the main purpose, and every word adds value. There is no redundancy or fluff.

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 (zero parameters, no output schema), the description adequately conveys what it does and what information it exposes. It lists the key data points (health, circuit breaker, failure counts, times) but could be slightly more explicit about the exact response structure. Still, it is largely complete for this simple 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 tool has zero parameters, so the schema covers all parameter semantics (vacuously). The description adds no parameter details, but none are needed. Baseline 4 is appropriate for a zero-parameter tool.

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 a specific verb ('check') and resource ('status of all ScraperServer instances'), and the details (health, circuit breaker, failure counts) distinguish it from sibling tools like get_billing and scrape_url. It fully identifies the tool's purpose.

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 use cases, prerequisites, or when other tools might be more appropriate. This is a clear gap.

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?

There are no annotations, so the description must carry the full burden. It discloses that the tool uses browser rendering to access blocked sites, which is a useful behavioral detail. However, it doesn't mention potential limitations, rate limits, or error behavior, so transparency is incomplete.

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, with the primary purpose stated first and the key capability (browser rendering for blocked sites) as a secondary note. Every sentence is informative and there is 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?

The description covers the core function and a differentiator, but it misses the distinction from scrape_urls, which could lead to agent confusion. Since there is no output schema, the description does mention the return format sufficiently. Overall, it's adequate but with clear 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?

The schema already provides descriptions for both parameters (url and format), and the context signal indicates 100% schema description coverage. The tool description doesn't add significant parameter-level meaning beyond what the schema already provides, so a baseline score 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 scrapes a webpage and returns content in Markdown format, which is specific and action-oriented. However, it doesn't differentiate from the sibling tool scrape_urls, which likely handles multiple URLs, so it falls short of a 5.

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 the ability to access blocked sites through browser rendering, which gives some context for when this tool might be preferred. However, it doesn't explicitly state when to use this tool versus alternatives like scrape_urls, so the guidance is implied rather than explicit.

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 full burden. It discloses parallel processing and browser rendering for blocked sites, which are useful behavioral traits. However, it omits potential limitations such as rate limits, errors on inaccessible pages, or the size of returned content, leaving some operational expectations unspecified.

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 efficient sentences with zero filler. The first sentence front-loads the action and purpose, while the second adds a distinctive capability. Every word contributes 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?

For a relatively simple tool with fully described parameters, the description adequately explains the tool's purpose, output format, and unique ability to handle blocked sites. It lacks only an explicit tie-in to the sibling tool 'scrape_url' and more detail on failure behavior, but these are minor gaps given the simplicity.

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 100%; both 'urls' and 'format' have descriptions. The text's mention of 'multiple webpages' and 'Markdown format' aligns with these parameters but adds no new semantic detail beyond what the schema already provides. The baseline of 3 applies.

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 a specific verb ('Scrapes'), a resource ('multiple webpages'), and a distinctive feature ('in parallel') that sets it apart from the sibling tool 'scrape_url' which likely handles single URLs. It also clarifies the output format ('AI-readable Markdown') and a key capability ('access blocked sites through browser rendering').

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 multiple URLs and for sites that may be blocked, but it does not explicitly mention when to avoid using this tool or point to alternatives like 'scrape_url' for single pages. While context is clear, no direct comparison or exclusions are provided.

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