zugabot
Server Details
Paid dev services for AI agents: code review, bug-fix, tests, docs, audits. USDC on Base x402.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
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Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.6/5 across 6 of 6 tools scored. Lowest: 3/5.
Each tool addresses a distinct aspect of the Zugabot service: listing, details, trial, preview, payment, and SDK snippet generation. No overlaps.
Most tools follow a verb_noun pattern (e.g., get_instant_sdk_snippet, list_services). “service_info” is a minor deviation but still clear.
6 tools is a well-scoped set for a service offering paid APIs with discovery, trial, payment, and integration steps.
Covers the main workflows: service discovery, evaluation (preview, trial), payment guide, and code integration. Missing a direct execution tool, but the SDK snippet fills that need.
Available Tools
6 toolsget_instant_sdk_snippetBInspect
Generate a ready-to-run Python snippet to call a Zugabot paid service on YOUR code. Your code is pre-filled — set PRIVATE_KEY and run to pay and execute. Free to generate.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | ||
| service | Yes | ||
| language | No | python |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses that the snippet includes user code and requires a PRIVATE_KEY to pay and execute. It also states generation is free. However, it does not detail error handling, rate limits, or side effects beyond execution.
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 that efficiently convey purpose and a key usage note. No redundancy, but could be slightly more structured with bullet points or examples.
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 3 parameters, no annotations, and an output schema (not shown), the description provides basic context about snippet generation and payment. Missing details on language parameter and output format, but acceptable for a straightforward 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?
The description adds meaning for 'code' (your code is pre-filled) and 'service' (paid service), but contradicts the schema by implying only Python output, while a 'language' parameter exists. Schema coverage is 0%, so more param-specific detail is needed.
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 generates a 'ready-to-run Python snippet' for a paid service. It distinguishes from siblings like 'list_services' and 'preview', but could be more precise about the snippet's exact role.
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 mentions it's 'free to generate', but does not differentiate use cases from siblings like 'run_trial' or 'get_payment_guide'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_payment_guideBInspect
Get copy-paste curl commands and step-by-step payment instructions for calling a Zugabot service. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| service | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description bears full burden. It notes the tool is free, but fails to disclose other behaviors such as whether authentication is needed, what happens with invalid 'service' input, or if the operation 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?
Single sentence, front-loaded with verb 'Get', no fluff. Efficient but could benefit from a brief list of what the output includes.
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?
Covers the main output (curl commands and instructions) but lacks parameter guidance and behavioral details. Given an output schema exists but is not shown, the description is adequate for a straightforward guide but not comprehensive.
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%. The description adds minimal value by implying 'service' identifies the service, but provides no details on valid values, format, or examples. This is insufficient for a single required 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?
Description clearly states the tool's purpose: providing curl commands and step-by-step payment instructions. It distinguishes from siblings like 'get_instant_sdk_snippet' and 'service_info' by specifying the output format and context ('for calling a Zugabot service').
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?
Implies use when generating payment instructions for a Zugabot service, but no explicit when-not or comparisons to alternatives like 'list_services' or 'run_trial'. Agent must infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_servicesAInspect
List all Zugabot paid developer services with prices and x402 pay endpoints. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the tool lists data, implying a read operation. It does not disclose any behavioral traits like authentication needs, rate limits, or idempotency. For a simple list tool, this is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, each providing essential information. No wasted words, and the key details are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and an output schema is present, the description is largely complete. It could be improved by noting that the output schema describes the return structure, but the description itself adequately covers what the tool does.
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 no parameters, and schema coverage is trivially 100%. The description adds value by specifying what is listed (prices, x402 pay endpoints), which is not in the schema, earning a baseline 4.
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 all paid developer services with prices and endpoints, using a specific verb and resource. It distinguishes itself from siblings 'preview' and 'service_info' which likely operate on single items.
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 with 'List all' and mentions 'Free', but does not explicitly state when to use this tool instead of siblings 'preview' or 'service_info', nor provide any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
previewAInspect
Show a representative sample of a services output so you can judge quality before paying. Free; canned sample, not a live run.
| Name | Required | Description | Default |
|---|---|---|---|
| service | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses it's a canned sample, not a live run, and free. However, it does not detail output format, sample size, or any limitations, leaving some behavioral aspects unspecified.
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, concise and front-loaded. No wasted words; 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 a simple tool with one parameter and an existing output schema, the description covers purpose, cost, and nature. It is sufficiently complete for an agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'service' with 0% schema coverage. The description implies it takes a service identifier but does not explicitly describe valid values or format. The meaning is inferable but not fully fleshed out.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Show a representative sample of a services output so you can judge quality before paying.' It distinguishes from siblings (list_services lists services, service_info gives info) by focusing on a sample output.
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 clear context: use before paying to judge quality, and notes it's free and a canned sample. It implicitly sets expectations but does not explicitly mention when not to use or alternative tools beyond the sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_trialAInspect
Run a real AI analysis on your code — free preview. 350-token output, 500-char code cap. Returns actual AI output so you can judge quality before paying. No account needed. Upgrade to the paid x402 endpoint for full unlimited results.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | ||
| service | Yes | ||
| language | No | python |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses key constraints (token output cap, code character limit) and states that the tool returns actual AI output. However, it omits details such as error handling, side effects (e.g., whether the analysis persists), or any required permissions. The disclosed information is useful 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 only four sentences and is front-loaded with the primary purpose. Each sentence adds value: purpose, limits, benefit, and upgrade path. There is no repetition or fluff; it is a model of conciseness.
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?
Considering the tool has 3 parameters (2 required), an output schema, and no annotations, the description provides a solid overview of the tool's function and constraints. However, it fails to describe the purpose or allowed values of parameters like 'service' and 'language', leaving gaps for an agent to properly invoke the tool. The output schema exists, so return value details are not required, but parameter clarity is lacking.
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, and the tool description provides no additional explanation for any of the three parameters (code, service, language). The description only implies 'code' through context but does not clarify semantics for 'service' or the default 'language'. Given the low coverage, the description fails to compensate, leaving the agent with insufficient guidance.
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-resource pair ('Run a real AI analysis on your code') and clearly identifies the tool as a free preview with established limits (350-token, 500-char). It distinguishes itself from siblings like 'preview' and 'list_services' by emphasizing the trial nature and the path to upgrade to a paid endpoint.
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 states when to use the tool ('free preview', 'judge quality before paying') and when to upgrade (paid x402 endpoint). It implicitly sets expectations by noting 'No account needed'. However, it does not explicitly mention alternatives to avoid, but the context is clear enough for effective agent use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
service_infoBInspect
Full detail and payment instructions for a single Zugabot service. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| service | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only adds 'Free' as a behavioral trait. It omits details on idempotency, side effects, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence plus a standalone word, efficiently conveying purpose and cost. It is front-loaded and without unnecessary fluff.
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, the description need not detail return values, but it still lacks guidance on parameter input and prerequisites, making it adequate but not comprehensive.
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?
With 0% schema coverage, the description vaguely indicates 'service' is an identifier but does not specify format, valid values, or examples, failing to compensate for the lack of parameter documentation.
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 provides 'full detail and payment instructions for a single Zugabot service,' with the word 'single' distinguishing it from sibling tools like list_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 use when needing detailed info for one service, but does not explicitly mention when not to use or direct to alternatives like list_services or preview.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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