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

With no annotations, the description carries the full burden, and it does disclose two real behavioral facts: account permission/ownership checks are enforced and only "public" permission is required. It does not state that the operation is read-only, nor describe pagination or error behavior for a tool whose schema exposes limit/offset.

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?

Three short, front-loaded sentences with no padding. Length is appropriate, though the first sentence is a null-information restatement of the name rather than an earning opener.

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?

An output schema exists, so return values need not be described, but the description leaves the tool's actual subject matter vague and says nothing about the two optional pagination parameters. For a get-by-id tool with three parameters and no annotations, this is under-specified.

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% across three parameters. The description mentions neither the required id nor the limit/offset pagination parameters, so it fails to compensate for the schema gap. The only hint is the word "id" embedded in the title-like phrase.

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?

"Get apis id" is essentially the tool name restated in broken grammar, so it barely states what the tool returns. The agent can infer it fetches a single API record by id (as opposed to the sibling acedatacloud_list_apis), but the description itself adds nothing on the resource or its contents.

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 a permission prerequisite ("Required permissions: public", backend account/ownership checks), which is useful context, but never says when to use this tool versus siblings such as acedatacloud_get_api_spec, acedatacloud_get_apis_usage, or acedatacloud_list_apis.

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 adds critical behavioral context: 'No token required' indicating no authentication needed. It also describes the return fields (definition, method, stage, cost). Missing details like rate limits or error handling, but sufficient for basic 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?

Two concise sentences with no unnecessary words. Front-loaded with key action and outputs. Perfectly sized for the tool's simplicity.

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 lookup tool with an output schema, the description covers purpose, parameter, basic behavior, and authentication. Lacks details on error conditions or rate limits, but adequate for effective 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 one parameter 'path' and a clear example. The description adds meaning by explaining what the tool returns (definition, method, stage, cost), complementing the schema's parameter description.

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 verb 'Get', the resource 'one API endpoint's OpenAPI spec', and includes the specific outputs (definition, method, stage, billing cost). It distinguishes from sibling tool 'acedatacloud_list_apis' which lists APIs, not a single spec.

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 does not provide explicit when or when-not to use this tool versus alternatives. It implies use for retrieving a specific API endpoint spec by path, but no comparative 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 full burden. It does disclose that backend account permission and ownership checks apply and that the required permission is 'public', which is genuinely useful auth context. However, it says nothing about read-only nature, pagination behavior, or what the usage data represents.

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?

Three short sentences, front-loaded with the action, no filler. The structure is efficient, though the sentence fragments are somewhat clipped.

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?

An output schema exists so return values need not be explained, but with 0% schema description coverage, no annotations, and an unexplained required id, the definition is too thin for an agent to invoke this tool confidently.

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 adds no parameter meaning at all. The required 'id' parameter is not explained (id of what?), and 'limit'/'offset' are only given placeholder descriptions in the schema. The description does nothing to compensate for the coverage 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 verb+resource ('Get apis usage'), but it is essentially a restatement of the tool name and does not distinguish this tool from siblings such as acedatacloud_get_usage_guide or acedatacloud_get_apis_id. An agent cannot tell from the description what 'apis usage' means concretely or how it differs from adjacent 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?

No when-to-use guidance, no exclusions, and no mention of the alternative acedatacloud_get_usage_guide which sounds nearly identical. The only context given is a permission note, which is not 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 full burden. It adds two useful behavioral facts: that only 'published' content is returned (not drafts), and that source fields are 'localized'. It does not cover auth requirements, error behavior, or fallback when a translation is unavailable.

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 tight sentence with no filler, and the core action is front-loaded. It is perhaps slightly too terse to route the agent between sibling read tools, but nothing wastes space.

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?

An output schema exists, so return values need not be described, and all parameters are documented in the schema. For a simple read-by-slug tool the description is nearly complete, missing only guidance on missing/unpublished slugs and localization fallback.

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 'lang' documented as requested translation language and 'slug' as the public blog slug. The phrase 'localized source fields' loosely signals the lang parameter's effect, but adds no format, default, or fallback detail beyond the schema. 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?

States a specific verb ('Read') and resource ('published article or video'), which maps clearly to a single blog post fetch. It implicitly contrasts with the list sibling (list_blog_posts) by describing a single item, but never names the sibling explicitly.

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 'published' framing implies this is for retrieving an individual live post by slug, which naturally distinguishes it from list_blog_posts. However, there is no explicit when-to-use statement, no exclusions, and no mention of what happens for unpublished or missing slugs.

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 it does add some value by stating that backend account permissions and ownership checks apply plus an access level ('public'). However it says nothing about pagination behavior for limit/offset or side effects, so it only partially compensates for the missing annotations.

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 text is very short and front-loads the operation, but the opening clause is a redundant restatement of the name and the phrasing is stilted. It is brief but not particularly well-structured.

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?

An output schema exists so return values need not be described, but three undocumented parameters, no usage context, and only a bare permission note leave the definition inadequate for a lookup tool with pagination options.

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% across three parameters (id, limit, offset), and the description explains none of them. The required 'id' and the limiting/paging parameters are left entirely undocumented, so the description fails to compensate for the coverage 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?

The description 'Get coin policies id' essentially restates the tool name rather than explaining what a 'coin policy' is or what retrieving its 'id' returns. It gives a verb and a resource but no meaningful scope or differentiation from sibling get_* 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?

No guidance on when to use this versus the many sibling lookup tools, nor any preconditions. The only contextual note is a permission requirement, which is not usage routing.

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 does add real behavioral context by disclosing that backend account permission and ownership checks apply and that 'public' permission is required, which is valuable. However, it says nothing about pagination behavior, what happens on missing/unauthorized ids, or the shape of the result.

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 short and front-loaded, with no filler sentences, but the phrasing "Get datasets id" is awkward and redundant with the name, and the permission sentence is the only substantive 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?

An output schema exists, so return values need not be explained, but the description leaves two documented pagination parameters unexplained and gives no usage context relative to list_datasets. For a resource-fetch tool with zero annotation coverage and 0% param coverage, it is under-specified.

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 all three parameters. It only implicitly references the required 'id' and gives no meaning to 'limit' or 'offset', whose schema descriptions are placeholder tokens. The description adds no semantic value about any parameter.

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?

"Get datasets id" essentially restates the tool name and is ambiguous: it is unclear whether it fetches a dataset by id or fetches the id field of a dataset. It never states it retrieves a single dataset resource, nor does it differentiate itself from the sibling list_datasets.

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?

There is no when-to-use or when-not-to-use guidance, and no mention of list_datasets as the alternative for browsing rather than fetching one dataset. The only routing hint is the required 'id' parameter.

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 no token is required, which is a behavioral trait. However, it does not mention what happens if the UUID is invalid, response size, or any side effects. For a simple read operation, this is adequate 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?

Two sentences, no wasted words. The description is front-loaded with the action and resource, then adds the key usage note about authentication. Every sentence 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?

Given the tool's simplicity (single parameter, output schema exists), the description is complete. It covers the purpose, identifier source, and authentication requirement. No additional context is needed for a basic 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?

The schema has 100% coverage with a description for the only parameter. The description adds context: 'Document UUID (from search results or list),' indicating where to obtain the ID. This adds value beyond the schema's simple type declaration.

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 ('Fetch'), the resource ('documentation page'), and the identifier ('by its UUID'). It distinguishes from siblings like 'acedatacloud_list_docs' and 'acedatacloud_search_docs' by specifying full content retrieval for a single document.

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 the crucial usage hint 'No token required,' indicating that authentication is not needed. This helps the agent decide when to use this tool over other tools that may require tokens. However, it does not explicitly specify when not to use it or mention alternatives.

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. It does disclose that backend permission and ownership checks apply and names the required permission, which is useful. However it says nothing about read-only semantics, pagination behavior implied by limit/offset, or the nature of the lookup, leaving most behavioral context unstated.

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 short sentences with no padding and the purpose stated first. However, the permission sentence is cryptic ("public" as a permission value) and the whole entry is under-specified rather than truly concise.

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?

An output schema exists, so return values need no explanation, but for a 4-parameter tool with zero schema coverage, no annotations, and many similar siblings, the description omits the parameter guidance and sibling differentiation an agent needs to call 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?

Schema description coverage is 0% and four parameters (lang, limit, offset, lookup_value) are entirely unexplained in both schema and description. The description does not compensate at all for the coverage gap, so even the required lookup_value has no stated meaning 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?

"Get documents openapi.json" essentially restates the tool name without a clear verb+resource explanation of what a document actually is or what is returned. It does not distinguish this from siblings like acedatacloud_get_doc, acedatacloud_get_api_spec, or acedatacloud_search_docs.

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?

There is no when-to-use guidance and no mention of alternatives among the many doc/spec siblings. The agent gets only a permission note, not a condition that selects this tool over near-identical ones.

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. It usefully states that backend account permissions and ownership checks apply and lists 'public' as the required permission, adding some behavioral context beyond structured fields. However, it omits other relevant traits such as read-only nature, idempotency, or error behavior.

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 very short and front-loaded, with no wasted sentences. The first sentence is awkwardly phrased, but the overall brevity is appropriate for a simple get 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?

Given the tool's simplicity and the presence of an output schema, the description still fails to state what resource is being fetched or what the 'id' parameter refers to. It also does not differentiate from sibling list or get tools, leaving the agent with insufficient context for correct selection.

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 does not mention any parameters. It provides no meaning for 'id', 'limit', or 'offset', leaving the placeholder schema descriptions as the only (non-informative) source.

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 'Get integrations id' essentially restates the tool name and does not clearly specify that it retrieves a single integration resource by ID. It fails to distinguish this tool from sibling acedatacloud_list_integrations or other get_* 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 mentions permissions and ownership checks but provides no guidance on when to use this tool versus alternatives such as acedatacloud_list_integrations. There are no explicit conditions or exclusions for its use.

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 full burden. It discloses the auth requirement (no token) and matching behavior (case-insensitive substring), but lacks details on error handling, rate limits, or what happens if model is not found.

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 sentences with no wasted words. First sentence covers action and return, second sentence covers auth. Highly efficient.

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 has one parameter and an output schema (implied), the description is largely complete. It explains the lookup method, return content, and auth. Missing potential edge cases like 'not found' behavior, but overall 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 schema already provides a description for the 'model' parameter. The tool description adds value by explaining the case-insensitive substring matching behavior, which goes beyond the schema's 'id or name' description.

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 verb 'look up' and resource 'models', specifies case-insensitive substring matching by id/name, and mentions the return of credit pricing and capabilities. This distinguishes it from sibling tools like acedatacloud_list_models.

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 for when to use (look up specific models) and explicitly states no token is required. However, it does not explicitly mention when not to use or suggest alternatives like list_models for browsing.

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 does disclose meaningful traits: authentication is not required ('No token required') and the response shape varies by dataset type (contact-only datasets return pricing_mode and reference_quote instead of checkout prices). It omits rate limits or whether the call is purely read-only, but the behavioral disclosure is solid.

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?

Three short sentences, front-loaded with what is returned, then the exception case, then the auth note. No filler, though the second sentence is slightly dense with unglossed field names.

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?

An output schema exists, so return values need not be enumerated, yet the description still flags the conditional fields an agent should expect. Combined with the auth statement, it is adequate for a single-parameter lookup tool.

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% and the single 'service' parameter is fully documented in the schema (UUID or alias). The description adds no syntax or format detail beyond that, so baseline 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?

States a specific verb+resource ('Get billing unit, free amount and display cost rules'), so an agent knows exactly what it retrieves. It does not name or contrast with siblings like acedatacloud_get_service or acedatacloud_get_public_usage_packages, so differentiation is left to inference.

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?

Adds useful conditional context — public contact-only datasets behave differently and return pricing_mode/reference_quote rather than checkout prices. However, it never says when to pick this over adjacent pricing-related siblings, so usage is implied rather than directed.

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 does meaningful work: it discloses that ladders are service-specific, that substitution from the generic catalog is invalid, and that the caller should fail closed if the public service detail cannot be read. It omits auth requirements and rate limits, but the data-integrity and failure-mode guidance is substantive.

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 purpose and its distinguishing constraint are front-loaded in the first sentence, and each following sentence adds a distinct constraint (what the pricing reader lacks, ladder non-portability, fail-closed). Slightly fragmented by line breaks but no 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?

An output schema exists, so return values need not be spelled out, and the description covers scope, the substitution hazard, and the failure behavior. For a single-parameter read tool this is close to complete, missing only peripheral details like error surface or caching.

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% and the schema already defines 'service' as a UUID or exact alias, so the description's parameter-level contribution is limited to the implication that service selection determines which ladder is returned. 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?

Names a specific verb and resource ('Get one service's public Usage packages') and scopes it to Credit-to-USD pricing, then explicitly contrasts it with the pricing reader, which returns cost rules but not package amount/price pairs. An agent can distinguish this from get_pricing and list_model_catalog without opening a schema.

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 identifies the alternative source (the pricing reader) and the condition that selects this tool instead — needing package amount/price pairs — and warns against substituting the generic model catalog ladder. It stops short of a full when-not-to-use rubric, but the routing context is clear.

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, but it does disclose two useful behavioral facts: backend account permission and ownership checks apply, and it requires the applications:read permission. It omits whether the call is read-only, whether it paginates, and what side effects (if any) occur, so it is only partially adequate.

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 three short, front-loaded sentences with no filler. It is appropriately sized, though its brevity reflects under-specification rather than tight editing.

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?

An output schema exists, so return values need not be explained, but the input parameters are entirely undocumented and the purpose is opaque. For a four-parameter tool with zero annotations, the description is significantly incomplete.

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% across four parameters (id, token, limit, offset), and the description adds no meaning for any of them. The agent cannot tell what id identifies, what token is for, or how limit/offset behave, so the description fully fails to compensate for the coverage 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?

"Get recharge cards allocations token" essentially restates the tool name verbatim, so the agent learns almost nothing about what a "recharge cards allocations token" actually is or returns. The only added signal is the permissions line, which is behavioral rather than purpose. This is close to a tautology.

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?

There is no statement of when to use this tool versus the many sibling get/list tools, nor any prerequisite or exclusion beyond an API permission string. An agent is left to infer the scenario entirely.

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. It adds value by stating 'No token required' and listing returned fields, but does not explicitly disclose read-only nature, error handling, or rate limits. It partially compensates but leaves gaps.

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, efficient sentence that lists all key aspects. No redundant words, front-loaded with the purpose. Perfectly concise for the information needed.

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 presence of an output schema (not shown), the description need not explain return values. It covers the essential input and behavior (no token required). It could mention what happens if the service is not found, but overall it is fairly complete for a simple get tool.

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 parameter description. The description does not add significant extra meaning beyond the schema; it says 'Get one service's full detail' but doesn't elaborate on the parameter format. Baseline score 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 verb 'Get', specifies the resource 'one service', and lists the exact details returned (title, description, type, unit, free_amount, cost). This differentiates it from sibling tools like acedatacloud_list_services (list multiple) and acedatacloud_get_pricing (focused on pricing).

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 for retrieving full details of a single service, but lacks explicit guidance on when to use this versus alternatives like list_services. It mentions 'No token required' which hints at public access, but no when-not or exclusions are 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?

No annotations are provided, so the description carries full burden, but it does disclose two useful behavioral facts: backend account permission scoping and ownership checks, plus the required permission level. It says nothing about pagination behavior though the schema exposes limit/offset, nor about response shape.

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?

Three short sentences, front-loaded with the action and following with the permission constraint. Nearly no waste, though the phrasing is terse to the point of being under-specified rather than genuinely concise.

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?

An output schema exists, so return values need not be described, but the description leaves the required id parameter's meaning, the pagination parameters, and the distinction from sibling list/get tools entirely unexplained. Inadequate for a 4-parameter tool with 0% schema documentation.

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 placeholder descriptions (e.g. "acedatacloud_get_services_apis_limit") convey nothing. With 4 parameters — including a required id whose relationship to the resource is undefined — the description adds no semantics at all, so it fails to compensate for the coverage 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?

"Get services apis" identifies a resource relationship but is close to a restatement of the tool name, with no verb-level detail about what is being retrieved or scoped. It does not clearly distinguish itself from siblings like acedatacloud_list_apis or acedatacloud_get_services_proxies. Purpose is inferable but vague.

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 states a permission requirement ("public") but gives no guidance on when to use this tool instead of list_apis, get_services_proxies, or the other service/API siblings. No preconditions or exclusions are offered.

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 disclosure burden. It signals that auth/ownership checks gate the call, which is genuinely useful, but says nothing about pagination behavior (despite limit/offset params), result shape, or what a "proxy" record contains.

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?

Three short sentences with the resource statement front-loaded and zero padding, but the brevity reflects under-specification rather than density — the space saved is information the agent needed.

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?

An output schema exists so return values need not be described, but the vague purpose, undocumented parameters, absent annotations, and missing sibling differentiation leave the definition inadequate for a paged list-style endpoint.

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 mentions none of the four parameters. The required `id` is undocumented (service id? proxy id?), and limit/offset/ordering are entirely unexplained in both schema and description, so the caller must guess.

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?

"Get services proxies" essentially restates the tool name with a verb+resource pairing but adds no scope, no notion of what a "proxy" is here, and no differentiation from the close sibling acedatacloud_get_services_apis. An agent cannot tell what this retrieves beyond the bare resource name.

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 states permission prerequisites ("Backend account permissions and ownership checks apply. Required permissions: public") but gives no when-to-use guidance, no distinction from acedatacloud_get_services_apis or acedatacloud_get_service, and no exclusions. Prerequisites are not usage guidelines.

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 burden. It discloses that the tool returns a guide explaining the platform, write-confirmation model, and authentication. While it doesn't explicitly state it is read-only, the description makes the behavior clear.

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: first states the purpose, second details the content. Extremely concise, front-loaded, and no 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 no parameters and an output schema, the description is complete. It explains what the guide covers, which is sufficient for an agent to decide when to invoke this tool.

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 no parameters, so the schema is fully covered. The description does not need to add parameter-specific information, and it provides context for what the tool returns.

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 'gets a guide' for using the platform, specifying it covers available tools, write-confirmation model, and authentication. This distinguishes it from sibling tools that perform specific operations like create, list, or delete.

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 guide is meant to understand the platform before using other tools, but it does not explicitly state when to use it or when not to, nor does it mention alternatives.

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 burden. It states basic behavior (list, sorted newest first) but lacks details on pagination, authentication requirements, rate limits, or whether announcements are cached. Adequate 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?

Single sentence with no filler. Immediately states purpose and ordering. 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 list tool with one optional parameter and an output schema, the description is mostly complete. It clarifies ordering and that announcements are 'published'. Could mention the sorting field (e.g., by date) but current phrasing is sufficient.

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 covers the single 'limit' parameter with a clear description. The tool description adds ordering info ('newest first') which is about output, not parameter semantics. No additional parameter context beyond schema.

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 'List published platform announcements (newest first)', specifying the action, resource, and ordering. It differentiates from sibling list tools like acedatacloud_list_models or acedatacloud_list_orders by focusing on announcements.

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 guidance on when to use this tool versus alternatives. The description implies usage for retrieving announcements, but does not mention scenarios where siblings would be preferred (e.g., using acedatacloud_get_doc for specific documents).

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. It discloses that no token is required and mentions the optional filters, but lacks details on pagination, rate limits, or other behavioral traits such as whether it returns all results or is paginated. The output schema likely covers return format, so this is adequate but not outstanding.

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 followed by a short clarification, front-loaded with the main purpose. Every word is necessary and no filler is present. It is appropriately sized and structured for efficient reading.

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 existence of an output schema, the description need not explain return values. It covers purpose, optional scoping, and authentication requirement. It is mostly complete for a list tool, though it could mention the default limit or ordering, but those are in the schema.

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%, so baseline is 3. The description briefly mentions optional scoping by service and stage, which aligns with parameters, but adds little extra meaning beyond the schema descriptions. It does not elaborate on limit or provide additional context.

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 verb 'List' and resource 'API endpoints', specifies optional scoping by service and stage, and notes what each item carries (path, method, stage, cost). This distinguishes it from sibling list_* tools that list other entities.

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 on when to use the tool (listing APIs with optional filters) and mentions 'No token required.' However, it does not explicitly exclude scenarios where alternatives like list_services might be better, though the purpose is sufficiently distinct.

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. It discloses one meaningful behavioral trait – this is a public endpoint requiring no account or blog permission – which is genuinely useful. But it omits pagination behavior, default ordering, whether unpublished/draft content is included, and how the lang translation parameter affects results.

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 short sentences, front-loading the scope statement before the access note. Nothing is wasted, though the terseness comes at the cost of the missing parameter guidance noted elsewhere.

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?

An output schema exists so return values need not be explained, but for a five-parameter, zero-required listing tool with low schema coverage, the description leaves the agent guessing about pagination, category filtering, and translation behavior. It is under-specified for the 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?

Schema description coverage is only 20%, so the description must compensate and does not. 'articles or videos' loosely maps to content_type, but lang, limit, offset, and category filtering/pagination semantics are never mentioned, leaving four of five parameters with no descriptive support beyond bare schema fields.

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+resource ('List published articles or videos'), which clearly separates it from the get_blog_post sibling that fetches a single post. It does not distinguish itself from other list-style siblings such as list_showcases or list_announcements, so it stops short of a 5.

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 account or blog permission required' gives one useful usage condition (public, auth-free access), which is real guidance. However, there is no explicit when-to-use vs get_blog_post, no mention of when to prefer list_blog_posts over sibling list tools, and no 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, the description adds 'No token required' which is helpful for understanding access constraints. However, it does not disclose other behavioral traits such as rate limits, ordering, or whether it is read-only.

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 that efficiently conveys purpose, output contents, and authentication requirement without any redundant 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 low complexity (one optional parameter, output schema present), the description adequately covers the essential information. The mention of output fields compensates for the lack of output schema details in the prompt.

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 covers the single parameter ('limit') with a description. The tool description does not provide additional meaning or usage details for this parameter beyond what the schema already states.

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'), the resource ('downloadable datasets'), and the key output fields ('title, price, download/preview URLs'). It also notes 'No token required', distinguishing it from sibling tools that may require authentication.

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 guidance on when to use this tool versus alternatives like acedatacloud_list_model_catalog. The description does not specify conditions or exclusions, leaving the agent without decision context.

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 provided, but the description adds the behavioral note 'No token required'. It also mentions sorting (newest/ranked) which isn't in schema. Could elaborate on the ranking default.

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 sentences, front-loaded with purpose, and concise alternative. No unnecessary 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?

Output schema exists, so return values aren't needed. Description covers the main purpose, filters, and alternative. Could mention pagination but not required.

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%, and the description reiterates the filters but adds no new semantics beyond 'optionally filtered'. 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 clearly states the verb 'Browse' and the resource 'documentation pages', includes sorting (newest/ranked) and optional filters, and distinguishes from the sibling tool for search.

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?

Explicitly states when to use this tool vs the sibling tool 'acedatacloud_search_docs' for content-relevance search, providing clear 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 provided, the description carries full burden but only adds 'No token required.' It omits details like read-only nature, pagination, or rate limits.

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?

Single sentence conveying purpose and key constraint; no 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?

With one optional parameter and an existing output schema, the description is sufficient. Lacks pagination details but overall 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?

Schema has 100% description coverage for the limit parameter. The description adds the fields returned ({title, options, stage}) and the no-token requirement, complementing the schema.

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 it lists third-party integrations and specifies the fields returned (title, options, stage), distinguishing it from sibling list tools like list_apis or list_models.

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 notes 'No token required,' implying public access, but lacks explicit guidance on when to use this tool versus siblings or context about prerequisites.

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 discloses that no token is required (auth-free read) and states the return includes modality counts and models. This is helpful behavioral context, though pagination or limits are not mentioned.

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 sentences, front-loaded with purpose, no redundant information. Every sentence adds value.

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 output schema exists, simple tool with 2 optional parameters, the description covers purpose, output, and auth. Missing pagination details but still adequate for a list endpoint.

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%, and the schema already describes both parameters. The description adds 'per-model credit pricing' hinting at output but does not enhance parameter understanding beyond the schema.

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 tool lists the model catalog with provider, modality, and per-model credit pricing. It distinguishes from siblings like acedatacloud_list_models by noting it returns modality counts plus matching models.

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?

Description mentions 'No token required,' which is useful authentication guidance, but does not specify when to use this tool versus similar tools like acedatacloud_list_models. Lacks explicit when-to-use or alternatives.

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