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

With no annotations, the description must carry the behavioral weight. It correctly frames the tool as returning a static checklist rather than performing a live audit, which is important given the tool's name. However, it does not explicitly disclose that it has no side effects, nor does it describe the output format or any potential caveats, leaving some gaps in 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, well-structured sentence that leads with the action and then supplies the supporting detail about the checklist's topics. Every clause carries useful information, and the parenthetical list of performance areas provides semantically rich context without bloat.

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 no output schema, the description is largely complete: it states what is returned and previews the checklist contents. The only minor gap is the absence of an explicit statement about the output structure (e.g., list format), but the term 'checklist' and the listed topics give a sufficient mental model for an agent 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?

The tool takes 0 parameters and the schema is fully covered, so there is no parameter-specific information needed. The baseline for 0 parameters is 4, and the description adds no parameter semantics because none exist; the tool is a simple, parameterless retrieval.

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 names a specific verb ('Return') and a concrete resource ('the AETumi 3D-web performance checklist'), and elaborates on its content with performance topics (DPR cap, Draco/Meshopt, KTX2, instancing, lazy-init, disposal, reduced-motion). This clearly distinguishes it from sibling tools like list_threejs_recipes and get_threejs_recipe, which are about recipes rather than a performance checklist.

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 clearly conveys when to use the tool (when the agent needs the AETumi 3D-web performance checklist), but it does not explicitly state when not to use it or how it relates to the sibling tools. There are no exclusions or prerequisites to note, so the context is clear though not fully harnessed with explicit 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?

With no annotations, the description must carry the burden of behavioral disclosure. It explains that the tool is about 'how to connect', indicating it provides guidance, but it does not explicitly state that it is read-only, that it returns a guide, or describe any side effects. This is a gap but not a contradiction or misdirection.

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, front-loaded sentence that quickly states the core purpose. The phrase 'for premium 3D web components, templates & scenes' is marketing-oriented and adds little for tool invocation, but overall it remains compact and readable.

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 annotations, no output schema) and distinct sibling set, the description is largely complete for selecting and invoking the tool. Minor ambiguity remains about the exact return value, but it does not block correct usage.

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 has no parameters, so the baseline is 4. The description appropriately does not need to add parameter-level meaning; there is nothing to document beyond the tool's overall purpose.

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 ('connect') and names a concrete resource (the hosted AETumi MCP) and target clients (Claude Code, Cursor, Codex). This clearly distinguishes it from sibling tools, which all focus on recipes, templates, or audit tasks rather than connectivity/setup.

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 clear usage context: use this tool when you need instructions for connecting the hosted AETumi MCP to supported clients. It names the specific clients and server protocol (streamable-HTTP), but does not explicitly state when not to use it or mention alternatives; its uniqueness among the siblings makes this less critical.

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 disclosure burden. It indicates a read operation (via 'Get') implying no side effects, but it does not explicitly state safety, error behavior, or what constitutes 'details'. It adds the valid ID list, which is useful, but leaves out any mention of invalid-ID handling or return format. It is not misleading, but it is minimal.

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. It front-loads the purpose ('Get details for one AETumi 3D website template') and appends the valid IDs without any redundant phrasing. Every word earns its place.

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 get tool, the description is adequate but not complete. It does not describe what 'details' includes (e.g., name, price, features), nor does it address potential errors or the response structure. Since there is no output schema, the agent must infer what it will receive. The list of valid IDs mitigates some uncertainty, but the vague 'details' leaves a meaningful gap.

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 documents the id parameter, so the baseline is 3. The description adds concrete valid values (aerae, aerae-luxe, aesport, aebiker, avelor), going beyond the schema's generic example. This extra specificity helps the agent select a correct id without needing an enum or additional lookup.

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 (Get), the resource (details for one AETumi 3D website template), and the selection mechanism (by id). It even enumerates the valid IDs, leaving no ambiguity about what the tool operates on. It is distinct from sibling tools like list_templates (which lists all) and get_threejs_recipe (which targets recipes, not templates).

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 a single template's details but does not explicitly contrast with alternatives. It does not state, for example, that list_templates should be used to discover available templates before calling get_template, nor does it mention when not to use this tool. The valid-ID list is helpful context but does not serve as usage 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 carries the behavioral burden. It discloses what the recipe includes (when-to-use, ready-to-paste code, expert notes), the code version constraint (r160+, ESM), and the supported ids, which gives the agent a clear expectation of the response contents.

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 packs purpose, response contents, version constraint, and all known ids with no filler. The most important 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 simple one-parameter getter with no output schema, the description is largely complete: it states what is returned and lists valid inputs. It stops short of specifying the exact response format (e.g., JSON vs. Markdown), but an agent can invoke the tool correctly without that detail.

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 documents the id parameter with an example, and schema coverage is 100%. The description adds value by enumerating the valid recipe ids, making correct invocation easier without needing an external lookup.

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 names a specific verb and resource ('Get one full Three.js / WebGL recipe by id') and differentiates itself from list-style siblings by emphasizing single-item retrieval. The included recipe ID list further disambiguates the tool's exact scope.

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 the usage pattern: call this when you have a specific recipe id. However, it never explicitly contrasts with list_threejs_recipes or says what to do when the id is unknown, so the selection guidance is only 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 full burden of behavioral disclosure. It clearly signals a read-only list and adds the notable 'you own the full source' trait, which is useful context. It does not mention pagination, output format, or any restrictions, leaving some behavioral uncertainty.

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, front-loaded sentence with no filler. Every clause adds value: the subject, the tech stack, and the ownership guarantee.

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, no-output-schema tool, the description is nearly complete: an agent knows what the list contains and the key ownership fact. It loses the top score only because it does not explicitly differentiate from sibling list_threejs_recipes or suggest a follow-up like get_template.

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 there is no parameter meaning to add beyond the schema. Per the baseline for no-parameter tools, this is appropriate; the description supplies useful context about what is being listed without needing to document 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 states a specific verb ('List') and a specific resource ('AETumi's premium interactive 3D website templates') with scoping details (Three.js / WebGL, React / Next.js). The 'templates' wording helps distinguish it from sibling list_threejs_recipes, and the ownership clause adds meaningful specificity.

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 intended use is implied: call this tool when the user wants a catalog of AETumi templates. However, it does not explicitly contrast with list_threejs_recipes or direct the agent to get_template for further detail, so the guidance is not as strong as it could be.

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 states it returns ids, titles, and keywords, implying a read-only retrieval. However, it does not explicitly confirm no side effects, nor does it mention ordering, pagination, or filtering behavior. It provides basic behavioral info but lacks depth.

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 main action front-loaded and the return fields clearly stated. The parenthetical examples add useful detail without bloat. Every word earns its place.

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 parameterless list tool, the description is complete. It tells the agent what the tool lists, the domain categories, and the exact return fields (ids, titles, keywords). There is no missing information that would prevent an agent from calling it 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 tool has zero parameters, so the description need not explain parameter semantics. It appropriately focuses on the return value. Since there are no parameters, a baseline of 4 is warranted, and the description does not introduce any ambiguity.

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) and the resource (expert, production-grade Three.js/WebGL recipes) with specific examples of recipe categories. It distinguishes itself from siblings like get_threejs_recipe (which likely fetches a single recipe) and list_templates (which lists templates) by explicitly focusing on recipes.

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 listing recipes but does not explicitly state when to use this tool versus alternatives. It does not mention exclusions or direct the agent to get_threejs_recipe for a single recipe. The context is clear but not explicit about selection criteria.

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