Autonoma Agent Services
Server Details
Paid agent trust checks, receipt verification, research, data work, and monitoring.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
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 3.3/5 across 3 of 3 tools scored.
Each tool has a clear, distinct purpose: listing services, requesting with payment, and previewing evidence. There is no overlap between the three.
All tool names use a consistent snake_case verb_noun pattern (list_, request_, trust_), making them predictable for an agent.
Three tools is within the well-scoped range (3-15). Each tool serves a necessary function for the domain of agent services.
The core workflow of discovering, requesting, and previewing is covered, but a tool to check request status or history is missing, which agents might need.
Available Tools
5 toolslist_offersList paid agent servicesAInspect
Return current fixed-price services and verified performance totals.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
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 only states the return value (services and performance totals) but does not disclose any behavioral traits such as read-only nature, authentication requirements, rate limits, or whether data is cached. Minimal disclosure.
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, front-loaded sentence that contains no extraneous information. Every word is necessary to convey the tool's function efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there are no parameters or output schema, the description sufficiently communicates the core output: current fixed-price services and performance totals. However, it could provide a bit more context on what 'verified performance totals' entails (e.g., sales, ratings) for complete understanding, 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?
There are no parameters, so the description does not need to add parameter meaning. Baseline is 4 per instructions. The description avoids misleading or redundant info about 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 explicitly states it returns current fixed-price services and verified performance totals, which is a clear verb+resource combination. It distinguishes from sibling tools 'request_service' (requesting) and 'trust_preview' (previewing) by focusing on listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to view available offers, but provides no explicit guidance on when to use it versus alternatives like request_service or trust_preview. No when-not or exclusionary criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
quote_taskQuote a custom taskCInspect
Classify and price a bounded task. Requires authority to commission the work and a target scope.
| Name | Required | Description | Default |
|---|---|---|---|
| request | Yes | ||
| deliverables | No | ||
| target_scope | Yes | ||
| authorization_attestation | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only mentions authorization requirements, missing details on side effects (e.g., whether a quote is saved), idempotency, 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 concise with two sentences, but it omits critical details, making it under-informative rather than efficiently complete. Every sentence should add value; here, the missing parameter explanations detract.
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 0% schema coverage, the description should compensate. It fails to explain what 'bounded task' means, the pricing mechanism, or the response format, leaving significant gaps for an AI agent to 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?
Schema description coverage is 0%, yet the description adds no information about the four parameters (request, deliverables, target_scope, authorization_attestation). It only alludes to two of them indirectly, failing to clarify their purpose 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 'Classify and price a bounded task' clearly states the tool's function. It implies a quote generation process, differentiating from sibling tools like 'list_offers' or 'request_service', though not explicitly naming them.
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 prerequisites: 'Requires authority to commission the work and a target scope.' It implies these conditions must be met before use but provides no explicit guidance on when to avoid this tool or mention of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
request_serviceRequest paid agent workCInspect
Request a service. Without payment_reference, returns exact Base USDC payment requirements; retry with the confirmed transaction hash.
| Name | Required | Description | Default |
|---|---|---|---|
| offer_slug | Yes | ||
| target_scope | No | ||
| payer_address | No | ||
| payment_reference | No | ||
| authorization_attestation | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose side effects. It hints at a two-step payment flow but does not state whether it mutates state, authorization needs, or rate limits. The behavior around 'retry' is unclear.
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 fluff. The first sentence states the purpose, the second explains the critical payment flow. 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?
With no output schema, no annotations, and 5 undocumented parameters, the description is insufficient. It does not explain return values beyond 'payment requirements', error cases, or the meaning of additionalProperties 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 0%; none of the 5 parameters are described in the schema. The description only implicitly explains payment_reference and its role in the flow, leaving offer_slug, target_scope, payer_address, and authorization_attestation unexplained.
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 'Request a service' and outlines a payment workflow: first call without payment_reference returns payment requirements, then retry with transaction hash. However, it does not differentiate from sibling tools like list_offers or trust_preview.
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 some workflow guidance (first without payment_reference, then with hash) but no explicit when-to-use vs alternatives, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
task_capabilitiesDiscover task capabilitiesAInspect
List bounded digital work this agent can quote and deliver.
| Name | Required | Description | Default |
|---|---|---|---|
No 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 states the tool lists capabilities, which implies a safe read operation. However, it does not disclose any additional behavioral traits such as authentication needs, rate limits, or result size.
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, front-loaded sentence with no unnecessary words. Every word contributes 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 no parameter, no output schema, and no annotations, the description is largely complete for a simple list tool. It lacks detail on return format but is adequate for 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?
No parameters exist, and schema coverage is 100%. Baseline for 0 parameters is 4. Description adds no parameter info because none are 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 uses specific verb 'list' and resource 'bounded digital work this agent can quote and deliver'. It clearly distinguishes from sibling tools like 'list_offers' (which lists offers) and 'quote_task' (which quotes a specific task).
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 you need to know the agent's capabilities, but does not explicitly state when to use versus alternatives like 'list_offers' or 'request_service'. No when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trust_previewFree agent trust previewBInspect
Run a free deterministic preview of supplied agent evidence.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It indicates the preview is 'free deterministic', implying non-destructive and consistent output, but does not disclose side effects, permissions, or state changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no extraneous words. Every part contributes meaning.
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?
Despite the tool having zero defined parameters, the free-form input schema adds complexity that is not explained. The description omits how to supply evidence and what the preview output contains, making it incomplete for agent 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?
The schema defines zero parameters with additionalProperties: true, meaning the tool accepts arbitrary input. The description mentions 'supplied agent evidence' but does not clarify what keys or structure are expected, leaving the agent uncertain about input format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a 'preview of supplied agent evidence', specifying the action (preview) and resource (agent evidence). It distinguishes from siblings like list_offers and request_service by describing a preview operation.
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, whether to use before committing, or when to prefer other tools.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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