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

No annotations are present, and the description is minimal. It does not disclose side effects, return behavior, persistence, validation, permissions, or whether the draft is immediately usable.

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?

One concise, clear sentence with no unnecessary detail 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?

No output schema or return behavior is described, and the tool lacks enough context for an agent to know what happens after creation or how to handle the response. Parameter meaning is also underspecified.

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 descriptions are absent, and the description only lists required/optional parameters without explaining what engineId, engineVersion, config, or ingredients mean or how they should be used.

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?

States a specific action ('Create a draft cheese') and clarifies 'cheese (game)'. The word 'draft' distinguishes it from publish_cheese and other sibling 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 a draft creation versus publishing, but it does not explicitly state when to use this tool or mention alternatives. No direct when-to-use or when-not-to-use 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?

The description only states the action ('create a draft template') without detailing side effects, return values, or error behavior. Since no annotations are provided, the description carries the burden of transparency, and it falls short by not explaining what happens on success or failure.

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 concise and well-structured. It consists of one clear sentence and a list of required parameters, with no superfluous content. It is easy to parse and understand quickly.

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 complexity of the tool (9 parameters, nested objects, no output schema, no annotations), the description is severely incomplete. It does not explain the meaning of the parameters, the structure of nested objects, or the expected response. An agent would have no way to correctly use this tool beyond knowing that it creates a draft 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 schema description coverage is 0%, and the only mention of parameters is a list of the required ones (engineId, engineVersion, label) without any explanation of their meaning or format. The other six parameters (tags, family, defaults, description, slotDefaults, contentDefaults) are completely undocumented. The description does not compensate for the lack of schema parameter descriptions.

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 purpose: 'Create a draft template.' It also lists the required parameters (engineId, engineVersion, label), which distinguishes it from sibling tools like publish_template or list_templates. This unambiguous action and scope make the purpose highly clear.

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 any prerequisites, conditions, or scenarios where this tool is preferred over siblings. The only hint is the word 'draft,' which implies a specific workflow step, but this is not 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, and 'Get' usefully signals a read-only retrieval rather than a mutation. Still, it does not disclose error behavior, permissions, or what 'full' means in terms of response contents, leaving some behavioral ambiguity.

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 short sentence with no filler. The core action and key parameter are front-loaded, making it immediately scannable for an agent.

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 operation, the description is minimally adequate, but with no output schema and no annotations it does not clarify the full response shape, possible errors, or how this relates to sibling tools like list_templates. The agent can invoke it but may not know exactly what to expect.

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 0%, so the description must compensate for the schema's minimal parameter documentation. It only refers to 'ID' without explaining the format, source, or expected meaning of templateId, adding little beyond the schema's name and type.

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 ('template') with a clear parameter ('by ID'), and the phrase 'full template' distinguishes it from list_templates or create_template. An agent can immediately tell what this tool does and how it differs from sibling 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 when to use the tool: when you have a template ID and need the full template. However, it does not explicitly state when not to use it or mention alternatives such as list_templates or search_assets, so usage guidance is only 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. 'List available game engines' clearly indicates a read-only retrieval operation, though it does not mention output format or potential limitations.

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 with useful examples and no filler or redundant 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?

For a simple parameterless list tool, the description is sufficiently complete. It identifies the resource, gives representative values, and requires no additional context for correct invocation.

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 zero parameters, so there is nothing left undocumented. The description matches the schema perfectly.

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?

Description clearly states the action 'List available game engines' and provides concrete examples, making the purpose unambiguous and distinct from sibling tools like list_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 the tool should be used to retrieve available game engines, but it does not explicitly compare against alternative tools or state when to prefer this tool over siblings such as list_templates or search_assets.

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 word 'list' suggests a non-mutating read operation, but with no annotations the description does not disclose details such as pagination behavior, default limits, or potential side effects.

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 names the operation and the optional filters without unnecessary detail.

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, but the description omits output shape, pagination behavior, and filter semantics, leaving some important details unspecified.

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 0% and the description only lists filter names without explaining their meaning, expected formats, or how cursor-based pagination works.

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 lists templates and names its optional filters, distinguishing it from sibling tools like get_template and list_engines.

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 somewhat implied by 'list templates', but the description does not explicitly explain when to choose this over get_template or search_assets, nor any context for filters.

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 of disclosing side effects. The verb 'Get' strongly implies a read-only operation, but the description does not explicitly state that it makes no changes or require permissions, leaving some ambiguity.

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 concise, well-structured sentence with no unnecessary words or redundant information. It front-loads the action and output, making it easy to parse.

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 states the high-level return values (playable manifest and resolved ingredient URLs) and important constraints (draft or published, owned by the agent). Given the simple single-parameter input and no output schema, this is reasonably complete, though it omits details about response structure or error cases.

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 a single required cheeseId with no description, and the tool description provides 0% schema coverage. The description refers to 'a cheese' but does not explain what cheeseId is, its format, or how to obtain it, so the parameter semantics are under-specified.

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?

Description clearly states the action ('Get'), the resource ('cheese'), and the specific outputs ('playable manifest and resolved ingredient URLs'), with scope ('draft or published') and ownership ('owned by the agent'). This distinguishes it from sibling tools like create_cheese or publish_cheese.

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 gives clear context by specifying that the tool applies to both draft and published cheeses owned by the agent, which narrows when it should be used. It does not explicitly name alternatives or contrast with sibling tools, but the preview-focused wording implies the intended use case.

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 discloses the main side effect—'appears in the feed'—and implies a draft-to-published transition, but it does not state whether the action is irreversible, what permissions are required, or how non-draft cheeses are handled.

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. Both the action and the outcome clause contribute directly to understanding the tool.

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 one-parameter tool with no output schema, the description conveys the action, object state, and result, making it mostly usable. It is slightly incomplete because it leaves usage alternatives and behavioral caveats such as reversibility and permissions implicit.

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 0%, and the description never explicitly names cheeseId. However, 'publish a draft cheese' implies that the sole parameter identifies the draft cheese to publish, adding state context beyond the bare schema, though format and validation details remain unspecified.

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 specifies the verb 'publish', the resource 'cheese', and the state transition 'draft' to 'feed', which clearly distinguishes it from sibling publish_template and preview/create actions. Even without naming a sibling, the resource and verb combination is unambiguous.

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 a clear trigger: use this when a cheese is in draft state and should become visible in the feed. It does not explicitly list alternatives or exclusions, but for a one-parameter publish tool the stated context is sufficient.

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 explains the main state change (draft to published and appearing in the wizard), but does not mention side effects, reversibility, permissions, or validation requirements.

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 with no filler. It states action, object, and outcome efficiently.

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 adequate for a simple publish action, but it omits useful context such as how to obtain templateId, what happens if the template is already published, and whether the action is reversible.

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 only one parameter, templateId, with no description and 0% coverage. The description references 'a draft template' but does not explicitly explain that templateId identifies that template, its source, or format.

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 ('publish') and resource ('draft template') and clearly states the outcome ('so it appears in the wizard'). This distinguishes it from create_template (which creates drafts) and publish_cheese (different resource).

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 the tool (after creating a draft template and when wanting it visible in the wizard), but it does not explicitly contrast it with alternatives or state when not to use it.

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 full burden. It reveals the 'published' scope, but does not disclose pagination behavior (cursor/limit), return shape, or whether search requires any auth/permissions.

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?

One sentence with no filler; the verb and key filters are front-loaded. It is concise, though perhaps at the cost of detail.

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 5-parameter tool with no annotations and no output schema, this description is sparse. An agent cannot infer cursor/limit semantics, the response format, or likely corner cases (e.g., no filters = all published assets).

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 0%, so the description must compensate. It clarifies that kind, typeTags, and theme are filter criteria, but says nothing about the meaning of limit and cursor, leaving a significant gap.

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?

States a specific verb ('Search'), a resource ('published assets'), and three filter dimensions (kind, typeTags, theme), making it distinct from sibling tools like list_engines or create_cheese.

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?

No explicit when/when-not or alternative routing. The intended use is implied by the verb and resource, and no sibling tool performs search, but there is no guidance about limits, pagination, or situations where other tools would be preferred.

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