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

With no annotations provided, the description fully discloses the tool's behavior: it returns the input message unchanged. There are no side effects, permissions, or additional behavioral traits to disclose for such a trivial operation.

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, grammatically complete sentence that states the entire purpose. Zero 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 the tool's trivial complexity, an existing output schema, and a well-defined input schema, the description is fully complete on its own. There are no missing details that would impact an agent's ability to invoke this 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?

The input schema already documents the 'message' parameter with 100% coverage, and the description adds no additional meaning beyond referring to it as 'the provided message.' The schema carries the semantic load.

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 specific verb ('echo back') and resource ('the provided message'), clearly distinguishing this from sibling tools focused on README and server management. The one-sentence definition leaves no ambiguity about the tool's function.

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 explicit guidance on when to use this tool versus alternatives. However, the purpose is self-evident as a simple utility, so the usage context is implied rather than 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?

With no annotations, the description carries the burden of transparency. It discloses that the return is the README.md content as text, but it does not mention potential errors, required access, or whether the operation is read-only. For a simple fetch, this is acceptable but not thorough.

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—two sentences with no filler. It front-loads the purpose and then states the return value, earning every word.

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 (no params, simple fetch) and the presence of an output schema, the description is mostly complete. It could mention error cases or that it fetches from a fixed path, but those are minor omissions.

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?

There are zero parameters, so the baseline is 4. The description correctly omits parameter details since none exist, and the schema already indicates no properties.

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 specific verb ('Fetch') and clearly identifies the resource ('README content from CheckPointSW/mcp-servers repository'). It is easily distinguishable from siblings like list_chkp_mcp_servers and get_chkp_mcp_server_tools.

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 when you need the repo's README, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. The context is clear, but no direct guidance is provided.

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 behavioral burden. It effectively explains the fetch-and-convert process and the specific sections included in the resulting markdown. This is transparent about outcome, though it stops short of mentioning side effects, error cases, or network dependencies.

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 well-structured sentences with no fluff. The first sentence states the core function, the second details the process and content, making it easily scannable.

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 has only one parameter, a complete schema, and an output schema (not shown). The description adequately covers the tool's functionality, input domain, and what the result will contain, making it complete for a simple fetch operation.

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% with package_name already described including an example. The description adds the domain context of 'CheckPoint MCP server' but does not provide additional parameter syntax or format beyond the schema. Baseline 3 is appropriate as the description adds marginal value.

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 retrieves NPM package documentation for a CheckPoint MCP server and enumerates the content (README, configuration details, environment variables, usage). This distinguishes it from sibling tools like fetch_readme, which likely only retrieve the README.

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 when full package documentation is needed, but it does not explicitly mention alternatives or provide when-not-to-use guidance. The presence of sibling tools like fetch_readme suggests a potential substitution but no direct comparison is made.

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 mentions it 'Connects to the specified MCP server via stdio' and 'retrieves all available prompts,' providing some insight into the operation. However, with no annotations, it doesn't disclose potential side effects like package installation or process behavior, which are relevant for a tool that executes an NPM package.

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, front-loaded with the main action, and uses concise language. No unnecessary 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?

The tool is simple with a single parameter and a likely output schema covering return values. The description explains the purpose and connection method, making it sufficiently complete for the agent. It lacks prerequisites or error scenarios, but these are not critical 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?

The input schema already has 100% coverage of the single parameter package_name, including an example. The description adds no additional parameter semantics beyond what the schema already provides, so it meets the baseline.

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 'Get all prompts from a CheckPoint MCP server' with a specific verb and resource. It distinguishes from sibling tools like get_chkp_mcp_server_tools and get_chkp_mcp_server_documentation by focusing on prompts.

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 that this tool is for retrieving prompts from a specified MCP server via stdio. However, it doesn't explicitly mention when to use it over sibling tools, though the name itself is self-explanatory.

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 full burden. It discloses that the tool connects via stdio and retrieves all available tools with metadata, which is a faithful representation of its read-only behavior. It does not detail error conditions or prerequisites, but the core behavioral traits are transparent.

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 first sentence stating the core purpose and the second adding execution context. No filler words, and information is 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?

For a tool with one well-described parameter and an output schema, the description sufficiently explains what it returns and how it operates. It doesn't over-specify, and the output schema covers return format, so the description is 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 `package_name` is already fully described in the input schema with an example, giving 100% coverage. The description does not add parameter-level detail, so the schema carries the load; 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?

The description opens with 'Get all tools from a CheckPoint MCP server,' which clearly states the verb (get), resource (tools), and scope (from a CheckPoint MCP server). This distinguishes it from sibling tools like get_chkp_mcp_server_prompts and get_chkp_mcp_server_documentation.

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 it (when you need the list of tools exposed by an MCP server) but does not explicitly contrast with sibling tools or state when not to use it. There are no exclusions or alternative tool references, so guidance remains implicit.

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. It discloses that it fetches a README from a specific repository, parses the markdown table, and returns a list with specified fields. This is transparent about the core process, though it doesn't cover potential error behavior or network dependence.

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 compact: three sentences that state the purpose, method, and return format. Every sentence provides unique information without redundancy or fluff, making it well-structured and 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?

For a zero-parameter tool with an output schema, the description adequately covers what the tool does, where data comes from, and what it returns. It falls short of full completeness by not mentioning error conditions, caching, or source volatility, but given the low complexity, it's nearly 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 tool has zero parameters, so the baseline is 4 per the rubrics. The description adds value by detailing the return values (server_name, package_name, description), which compensates for having no input semantics to clarify.

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 ('List all CheckPoint MCP servers'), the resource ('CheckPoint MCP servers'), and the method ('by parsing the README table'). It distinguishes itself from siblings like 'fetch_readme' (which fetches the raw README) and 'get_chkp_mcp_server_tools' (which targets a specific server's tools).

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 ('List all...' suggests using it when you need an inventory of servers), but it provides no explicit when-to-use guidance or alternatives. It doesn't mention when to prefer 'fetch_readme' or other sibling tools, leaving the agent to infer from the verb.

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