baseframelabs-catalogue

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

No annotations are provided, so the description carries the full burden of explaining behavior. It mentions 'ranked' but does not disclose what the tool returns, whether it's safe/read-only, how ranking works, or any limitations. The description is too sparse to provide meaningful behavioral transparency.

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 that front-load the action and resource, and include a useful example. Every word contributes meaning, with no fluff or repetition.

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 its purpose and usage. The example helps clarify expected user input. It could be more complete by describing the output (e.g., a ranked list of tool names), but overall it's sufficient for this tool's 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?

The schema already describes the single parameter 'goal' as 'What the user is trying to do.' The description adds value by clarifying it should be a 'plain-language goal' and provides a concrete example, enhancing the semantic understanding of what input is expected.

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 ('find'), a specific resource ('Baseframe Labs developer tools'), and the tool's distinctive functionality (matching plain-language goals and returning ranked results). This clearly differentiates it from sibling tools like get_docs or list_products.

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 an explicit when-to-use instruction ('Use this first when the user describes a problem') with a concrete example. It doesn't explicitly name alternatives or exclusions, but 'first' implies it should precede more specific tools, which is sufficient 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?

No annotations are present, so the description carries the full burden. It states the output (a full guide) but does not disclose error behavior, read-only nature, or format details. For a simple read operation, this is acceptable but not rich.

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 one sentence of 14 words, front-loaded with the verb and resource. Every word contributes meaning, and 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?

For a simple tool with one parameter and no output schema, the description is fairly complete. It explains what the guide contains and that it is selected by slug. Slight improvement could be made by indicating where the slug comes from, but that is not essential for the tool's use.

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 a clear description of the 'slug' parameter. The description's mention of 'by slug' reinforces the schema but adds no additional semantic value beyond what the schema already provides.

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 'Get' and clearly identifies the resource: 'full agent-readable guide for one product by slug'. It also lists content types (overview, features, setup, usage), making it distinct from sibling tools like list_products, get_install, and get_mcp_config, which serve different purposes.

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 when a product slug is known and the full guide is needed. However, it does not explicitly state when to prefer this over sibling tools or how to obtain the slug, leaving the guidance implicit 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 provided, the description carries the full burden. It clearly indicates the tool returns install command and links, but it doesn't disclose potential prerequisites (e.g., authentication), error behavior, or return format. The verb 'get' implies a read-only operation, which provides some transparency, but further context would be beneficial.

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 one sentence with no filler. It conveys the core purpose efficiently and front-loads the key information.

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 getter with two parameters and no output schema, the description covers the essential purpose. It could be improved by mentioning the response structure or error scenarios, but the tool's simplicity keeps it adequate.

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 covers 100% of parameters with descriptions. The description adds little beyond the schema: 'by slug' aligns with the slug parameter. No new semantic value is provided, justifying the baseline score of 3.

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 ('Get') and resource ('install command and links') with a clear scope ('for one product by slug'). It distinguishes itself from sibling tools like get_docs or get_mcp_config by focusing on installation guidance.

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?

Usage is implied: use this when you need an install command for a product. However, there is no explicit mention of when not to use it or alternatives such as get_docs or list_products. The guidance is minimal but 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?

No annotations are provided, so the description carries full responsibility for disclosing behavior. It merely states 'Get the MCP client config' without mentioning return format, side effects, or whether it is a read-only operation. The description does not contradict anything, but it adds no behavioral detail beyond the obvious getter action.

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 filler words. It front-loads the action and resource, and effectively communicates the tool's purpose in one concise line.

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 lack of an output schema, the description should explain the return value or config format, which it does not. It covers the general use case but leaves out details on response shape, making it minimally adequate for a simple two-parameter getter.

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% for both parameters (slug and client), and the schema already describes their meanings. The description adds context about the purpose but does not enrich the parameter semantics beyond the schema, so a baseline 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 the tool gets the MCP client config for wiring a product's MCP server into a user's coding agent. The verb 'Get' and the resource 'MCP client config' are specific, and the phrase 'if it ships one' distinguishes it from other get* tools like get_docs and get_install.

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 a condition for use ('if it ships one') but does not explicitly state when to use this tool versus alternatives such as get_install or get_docs. There is no mention of exclusions or alternative tools, so usage guidance is only implied.

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 transparency burden. It adds context by specifying the scope ('full catalogue') and output fields, implying a read-only, comprehensive operation. However, it does not mention error handling, pagination, or other behavioral caveats, leaving transparency limited.

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 'List', and conveys all necessary information without redundancy. It is an exemplar of conciseness.

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, no output schema), the description fully covers the purpose, scope, and output fields. No critical information is missing for an agent to understand and invoke 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?

The schema has zero parameters and the description provides no parameter information, which is appropriate. The baseline for 0-parameter tools is 4, and the description additionally clarifies the output content, satisfying this dimension.

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 'List the full Baseframe Labs catalogue' with a specific verb and resource, and enumerates returned fields (slugs, categories, install commands). This clearly distinguishes it from sibling tools like find_tools (search) and get_install (installation details).

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 retrieving the complete catalogue, but does not explicitly compare with sibling tools or specify when not to use it. The 'full catalogue' phrasing suggests a comprehensive listing, but it lacks direct alternative guidance.

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