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

With no annotations, the description carries the full burden and discloses key behaviors: the server's tools become available across clients and appear with a specific naming pattern after restart. This is genuine behavioral context beyond the schema, though it does not mention failure modes or idempotency.

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, immediately stating the action and its outcome. Every clause adds value: the purpose, the effect, and the restart requirement. 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?

The description is complete enough for a simple add operation, covering the main outcome and a critical post-condition (restart). It does not address edge cases like duplicate adds or prerequisites (e.g., server must already be installed), but these are not essential given the tool's straightforward nature.

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 100% coverage for both parameters, so the description adds no additional parameter-level detail. The baseline of 3 applies because the schema effectively documents the 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?

The description uses a specific verb ('Add') and resource ('an MCP server to your Launcher stack'), clearly stating the tool's function. It also differentiates from siblings like install_server by focusing on making tools available through Launcher, which is distinct from installing the server itself.

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 indicates the purpose — to make server tools available in every AI client — and notes that tools appear as `<slug>__<tool>` after restart, giving clear usage context. However, it does not explicitly mention when not to use this tool or contrast it with alternatives like install_server, so it lacks explicit 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?

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly indicates a read-only retrieval ('Get full details') and mentions that install instructions are included, but it does not explicitly state that it avoids any side effects or describe what happens if the slug is invalid. It provides some context but not comprehensive 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 a single, concise sentence that front-loads the core purpose ('Get full details') and appends the key extra detail about install instructions. Every word earns its place, with no unnecessary filler.

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 one-parameter read tool with no output schema, the description is sufficiently complete: it states what the tool returns (full details) and what is included (install instructions). It could be enhanced by explicitly noting it does not install anything, but overall it covers the essential information needed.

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 fully describes the single parameter 'slug' with 'Server slug (from search results)', which covers 100% of parameters. The description does not add extra meaning beyond implying the server is specific, but baseline is 3 due to high 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 uses a specific verb 'Get' with a clear resource 'full details about a specific MCP server', which directly states the tool's function. It clearly distinguishes from sibling tools like search_servers (list/search) and install_server (perform installation), as it focuses on retrieving detailed information for a known server.

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 context: use this tool when you need comprehensive details about a specific server, given a slug. However, it does not explicitly mention when not to use it or name alternatives like install_server. The context is clear but lacks explicit exclusions or alternative 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 provided, so the description must carry the full burden. It conveys that this is a read operation returning a manual install snippet, but does not disclose response format, side effects, or prerequisites. Some transparency is present but not comprehensive.

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, concise sentence that leads with the primary action and includes the alternative guidance in parentheses. Every word earns its place, with 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?

For a simple tool with only 2 parameters and no output schema, the description covers the core purpose and usage context. The main gap is not describing the return value format, but the term 'snippet' implies a configuration string. Given the low complexity, this is 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?

Schema description coverage is 100%, with both parameters ('slug' and 'client') already described in the schema. The tool description adds no parameter-specific insight beyond what the schema already provides, so 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 uses a specific verb ('Get') and resource ('manual install configuration snippet for an MCP server'), clearly distinguishing it from the sibling tool add_to_stack, which is explicitly mentioned for the managed case.

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 explicitly tells the agent when to use this tool vs an alternative: 'use add_to_stack instead if you want it managed by Launcher'. This provides a clear conditional choice and names the specific sibling tool.

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. The verb 'list' implies a read-only operation, which is transparent. But it does not disclose the response format or any edge cases (e.g., empty list). This is sufficient for a simple listing tool but lacks extra behavioral context.

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, focused sentence with no redundant words. It is front-loaded and immediately communicates the tool's 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?

Given the tool's simplicity, the description covers the essential purpose. However, without an output schema, the agent must infer the return format (e.g., an array of category names). This minor gap prevents a perfect score.

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 schema coverage is complete. The description correctly omits parameter details, and the baseline for zero-parameter tools is 4, which is appropriate here.

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 specifies the action (list) and the resource (all available MCP server categories), distinguishing it from siblings that handle server details, search, install, or stack operations.

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 purpose is self-evident: use this tool when you need a list of categories, likely before searching or installing servers. However, it does not explicitly mention alternatives or when not to use it, though the simple nature of the tool makes this a minor 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?

No annotations are provided, so the description carries the full burden. It only says 'Search' without disclosing behavior such as return format, pagination, or authorization requirements. The description is insufficient to inform an agent about the operational characteristics of the search.

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, 13 words, and directly front-loads the action ('Search') and resource ('CuratedMCP catalog'). No unnecessary words or 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 gives the core purpose but lacks details about the output (e.g., what the search returns) and does not compensate for the absence of an output schema. Given the tool's relative simplicity, this is minimally sufficient but leaves room for improvement.

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 all three parameters (query, category, limit) described in the input schema. The description mentions 'keyword, category, or use case' which loosely maps to query/category, but it does not add meaning beyond what the schema already provides, so 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 explicitly states the tool's function: 'Search the CuratedMCP catalog for MCP servers by keyword, category, or use case.' This clearly distinguishes it from siblings like get_server_details, install_server, list_categories, and add_to_stack, which have 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 for discovery ('Search... by keyword, category, or use case') but does not explicitly state when to prefer this over alternatives or when not to use it. It lacks explicit exclusions or references to sibling tools, leaving usage context partially implied.

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