zugabot

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

With no annotations, the description carries the full burden. It discloses that the tool generates a snippet, requires a PRIVATE_KEY for payment/execution, and is free to generate. It does not describe any destructive side effects, but the generation itself is likely safe.

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, front-loaded with the core purpose, and includes necessary context (pre-filled, PRIVATE_KEY, free) without waste.

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 are not required in the description. However, the description fails to document parameters, leaving a gap in usability. The tool's complexity is moderate, but missing parameter semantics reduces completeness.

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 3 parameters with 0% description coverage. The description does not explain what 'code', 'service', or 'language' represent beyond implying that 'code' is the user's pre-filled code. This is insufficient for proper use.

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 action ('Generate a ready-to-run Python snippet') and resource ('to call a Zugabot paid service'). It distinguishes from siblings by focusing on code snippet generation rather than listing, previewing, or trialing services.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when one needs to call a paid service programmatically, but it does not explicitly state when to avoid this tool or mention alternatives among siblings like 'preview' or 'run_trial'.

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

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

With no annotations, the description must disclose behavior. It mentions 'Free' as a behavioral note and indicates it returns copy-paste commands. However, it does not clarify whether calling a service incurs costs, if authentication is needed, or if the tool 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 very concise with two phrases. It is front-loaded with the main purpose (curl commands and instructions). However, it could benefit from a slightly more structured format, e.g., specifying the parameter.

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) and only one parameter, the description covers the core functionality. However, it lacks parameter guidance and does not mention the output format beyond 'copy-paste curl commands', which may be insufficient for an agent to fully understand the return value.

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 0% description coverage for the only parameter 'service'. The description adds no meaning beyond the schema, merely referencing 'calling a Zugabot service'. The agent cannot infer what values the parameter accepts (e.g., service name, ID).

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 provides curl commands and payment instructions for a Zugabot service, distinguishing it from siblings like service_info (which likely provides general info) and get_instant_sdk_snippet (SDK code). The verb 'Get' and resource are specific, but it could be more explicit about what 'payment instructions' entails.

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 service_info. The description implies usage for payment-related tasks but does not exclude other scenarios or mention prerequisites such as needing a service name.

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?

Lacks annotations, but description adds that the tool is 'Free' and lists contents. However, it does not disclose potential side effects, authentication needs, 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?

Extremely concise: a single sentence with the key information upfront. 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?

With no parameters and an output schema present, the description adds useful detail about return contents. Missing sibling differentiation but otherwise complete for a simple list 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?

No parameters exist, and schema coverage is 100%. The description correctly adds no parameter info, meeting the baseline for zero 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 clearly states the verb 'list', the resource 'all Zugabot paid developer services', and specifies inclusion of 'prices and x402 pay endpoints'. This makes the purpose highly specific and distinguishable from siblings.

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 'service_info' or 'preview'. The description does not provide context for selection.

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 exist, but the description discloses it's free, uses a canned sample, and is not a live run. It doesn't cover authentication or side effects, but for a preview tool, these are less critical.

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 (27 words) are front-loaded with the main purpose. No superfluous 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?

With one parameter and an output schema, the description covers core purpose, cost, and sample nature. It doesn't detail parameter format, but the tool is simple enough that completeness is 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 sole parameter 'service' has no schema description (0% coverage) and the description does not explain what values it accepts. The agent lacks guidance on valid inputs.

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 shows 'a representative sample of a services output' for 'judge quality before paying', distinguishing it from siblings like run_trial (live trial) and service_info (information). It also clarifies it's free and canned.

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 using before paying and contrasts with 'not a live run', guiding when to use. It doesn't explicitly name alternatives, but the sibling list provides context for exclusion.

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 exist, so the description carries the burden. It discloses code and output limits and states no account is needed, but does not explicitly clarify read-only behavior or potential side effects. The information 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?

The description is concise with four sentences, front-loading the primary purpose. It efficiently communicates key constraints and upgrade path without unnecessary text.

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 are covered. However, with 3 parameters and no annotations, the description should detail all parameters and behavioral context. It is incomplete regarding 'service' and 'language', affecting overall completeness.

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. It mentions a 500-character code cap, adding value for the 'code' parameter, but fails to explain the 'service' or 'language' parameters. This leaves significant gaps in understanding parameter 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 the tool runs an AI analysis on user code as a free preview, specifying output and code caps. It distinguishes itself from sibling tools like 'list_services' or 'preview' by focusing on trial execution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly recommends using this tool for free previews before deciding on paid upgrades, and suggests the paid x402 endpoint for unlimited results. It does not exclude other use cases or mention alternative tools, but provides clear usage 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?

With no annotations, the description bears full responsibility for behavioral disclosure. It only states 'Free', indicating no cost, but omits other traits like auth requirements, side effects, 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?

The description is very short (two sentences) but lacks necessary detail about the single parameter. It could be more informative without being verbose.

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?

Although an output schema exists (lowering the burden for return value explanation), the description fails to specify how to provide the 'service' parameter (e.g., ID vs. name) and what 'full detail' entails.

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 sole parameter 'service' has no description in the schema (coverage 0%) and the description provides no additional meaning, such as format, examples, or constraints.

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 returns 'full detail and payment instructions' for a single service, which is specific and distinct from listing all services. However, it does not explicitly differentiate from siblings like 'get_payment_guide' or 'get_instant_sdk_snippet'.

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. There is no mention of prerequisites, exclusions, or context for selection among sibling tools.

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