rixot-mcp

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

No annotations are provided, so the description carries the burden of indicating read-only behavior. The verb 'Get' implies a non-destructive operation, and the currency detail adds context. However, it does not disclose any additional behavioral traits such as authentication requirements, data freshness, or potential errors, leaving the transparency at a baseline level.

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, clear sentence that conveys the essential purpose without any waste. Every word adds value, and it is front-loaded with the verb and resource.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema, and a straightforward read operation), the description is fully complete. It tells the user exactly what the tool does and in what currency, which is sufficient for a balance-check utility.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and it correctly omits any parameter details. The schema already covers 100% of the (empty) parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Get' with a clear resource 'Rixot account balance' and specifies the currency (USD). It distinguishes itself from sibling tools like get_article_prompt and get_basket, which target different resources.

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 that this is the direct way to check funds before ordering, nor does it exclude any scenarios. Since siblings are unrelated, but no explicit usage context is given, this dimension is lacking.

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 the fixed output contract (JSON title/html/url, one dofollow link, no images) and the edit/recommendations flow, adding meaningful behavioral context. It does not mention side effects or auth, but for a getter-like tool the disclosed details are 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?

Two sentences, front-loaded with the core function, followed by workflow and contract details. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, its role in the workflow, and the output contract, but omits parameter explanations and does not detail the exact output format beyond a high-level contract. Given the simple getter nature and lack of output schema, it is sufficient but not exhaustive.

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 four parameters with zero description coverage. The description only mentions 'recommendations' in the context of passing edited guidance to order_backlink, leaving keyword, language, and target_url unexplained. The description fails to compensate for the schema 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 uses a specific verb 'Return' and resource 'default article-generation prompt', clearly identifying the tool's function. It also explains the purpose (see how article is written, optionally edit) and distinguishes it from siblings like order_backlink which handles the ordering step.

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 explicit workflow guidance by stating 'Pass the edited guidance back as "recommendations" in order_backlink', showing how this tool connects to a sibling. It implies when to use this tool (before ordering) but doesn't explicitly state alternatives or 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?

No annotations are provided, so the description carries the burden of conveying behavior. The verb 'List' implies a read-only operation, and the phrase 'inspect before publishing' adds context that contents are drafts. However, it does not disclose other behavioral details like side effects or return format, which is acceptable for a simple list tool but not richly detailed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with a parenthetical clarification, front-loading the primary action 'List what is currently in your basket'. Every word serves a purpose, with no redundancy or 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?

Given the tool has no parameters, no output schema, and no annotations, the description adequately covers its purpose and usage. It is a simple read operation, and the description provides enough information for an agent to select and invoke it correctly, including the timing (before publishing).

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 to document. The baseline for a zero-parameter tool is 4, and the description adds no parameter information because none exists; this is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists the current basket contents, using the specific verb 'List' and resource 'basket'. It also clarifies the items are drafted articles/placements for inspection before publishing, which distinguishes it from the sibling publish_basket tool.

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 context 'before publishing', implying the tool is used for inspection prior to a publish action, and thus differentiates it from publish_basket. However, it does not explicitly name alternatives or exclusions, though the use case 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 only mentions the action and filters. It fails to disclose return format, pagination, or any read-only guarantees, leaving the agent uncertain about 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 sentence followed by a filter list, with no redundant information. It is front-loaded and 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?

The tool has no output schema and no annotation support, so the description should provide more context about expected results and filter behavior. It currently lacks essential details for effective 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 description merely lists the parameter names without explaining their semantics. For example, 'dr_min' and 'price_max' are not defined, and schema descriptions are absent, so the agent must guess at their meaning.

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 finds marketplace donor sites for a niche/budget, using the specific verb 'Find' and a distinct resource. It does not explicitly compare to sibling tools, but the resource is unique enough to differentiate it.

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 like list_links or order_backlink. No exclusions or alternative suggestions are given.

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

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

With no annotations, the description carries the full burden. The verb 'List' clearly implies a read-only operation, and it discloses what content is included (status and published URL). However, it does not mention any authentication needs, response formatting, or other behavioral details, 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 a single concise sentence with no redundant words. It efficiently conveys the purpose and key output details.

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 no parameters and no output schema, the description adequately covers the core purpose. It could mention pagination or sorting, but these are not essential given the tool's simplicity. Missing details are minor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, making schema coverage trivially 100%. The description does not need to explain parameters, and the baseline for 0 params is 4, which is appropriate here since no additional parameter detail is required.

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 the specific verb 'List' with a clear resource ('ordered backlinks') and states the returned fields ('status and published URL'). It distinguishes itself from sibling tools like order_backlink and publish_basket by focusing on listing ordered backlinks.

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 is provided on when to use this tool versus alternatives. The description merely states what it does without mentioning exclusions or context where another sibling would be more appropriate.

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 transparency burden. It discloses that no charge occurs yet, that own-content mode requires special account permission, and that payment happens later via publish_basket. However, it does not describe what the API returns (e.g., order IDs, basket state) or mention potential side effects like overwriting existing drafts, 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, compact paragraph that front-loads the primary purpose and then efficiently enumerates the three modes. Every sentence contributes essential information (modes, prerequisites, next step), with no redundancy or filler. The use of parentheses and inline parameter lists keeps it readable despite the complexity.

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 tool with three modes and eight parameters, the description covers the different usage scenarios, required inputs per mode, and the payment flow via publish_basket. It lacks explicit explanation of return values (no output schema exists), potential errors, or idempotency behavior, but the core operational context is well covered. It is complete enough for an agent to invoke it correctly in most 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?

While the schema provides 100% description coverage, the description adds critical semantic meaning by grouping parameters into operational modes: auto (donor_ids + target_url + keyword), prompt (adds recommendations), and own (target_url + content, with optional title/article_url). This mode-based grouping clarifies relationships and constraints that the schema alone does not convey.

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 function: 'Add backlink order(s) to your basket' with the key qualifier 'no charge yet'. It uniquely identifies the resource (backlink orders in a basket) and differentiates from siblings like publish_basket (payment) and get_article_prompt (fetching prompt).

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 explicit usage guidance by detailing three content modes (auto, prompt, own) with exact parameter combinations for each. It also directs the user to prerequisite actions ('fetch the editable base prompt with get_article_prompt first') and the follow-up step ('call publish_basket to pay'), making it clear when and how to use this tool versus 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 discloses the all-or-nothing behavior on insufficient balance, reports the shortfall, and states the topping-up constraint. This is good coverage of behavioral traits, though it doesn't mention what happens on success (e.g., confirmation or return value) or any irreversible effects of publishing.

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 sentences, front-loaded with the main action, followed by a conditional behavior and a constraint. Every sentence adds value: purpose, failure mode, and a necessary user guideline. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and zero parameters, the description is fairly complete. It covers the primary function, the failure scenario, and a usage constraint. It could add what a successful publish returns or that the action is irreversible, but these are not essential given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, so the schema is trivially covered. Per calibration, 0 params gets a baseline of 4. The description adds no parameter-specific info, but none is needed; it focuses on the operation itself.

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 function: 'Publish everything in your basket, paying from your account balance.' This is a specific verb ('publish') with a clear resource ('basket') and payment method. It distinguishes itself from siblings like get_basket (viewing) and order_backlink (individual ordering).

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 useful context: if the balance is short, it 'does nothing and reports how much more is needed,' and topping up is only done in the dashboard. This implies when to use the tool (when balance is sufficient) and when not to (when needing to top up). However, it doesn't explicitly mention alternatives like check_balance before publishing, so it lacks explicit exclusions.

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