Atinamos Agent Shop

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get' and 'definition' imply a read-only, non-executing operation, and the output schema covers return structure, but the description does not explicitly state that the service is not invoked or mention any authentication/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 a single, information-dense sentence with no filler. The key facts—what is retrieved, for which service, and by what identifier—are front-loaded and directly useful for tool selection.

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 single-parameter read operation with an output schema, the description is nearly complete. It covers the tool's purpose, target resource, and parameter role; minor omissions are an explicit no-side-effect guarantee and guidance on discovering valid slugs, though sibling tools like list_services may cover that.

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 description coverage, the description compensates by clarifying that the single parameter is the catalogue slug identifying the service. This adds meaning beyond the schema's bare 'Slug' string, though it does not specify slug format or how to obtain a valid slug.

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 states a specific verb ('Get'), a precise resource ('the machine-readable definition of one live Agent Shop service'), and the selection mechanism ('by catalogue slug'). It clearly distinguishes this tool from list_services (one vs. many) and invoke_service (definition vs. 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 gives clear context for when to use the tool: when a caller needs the machine-readable definition of a single live service, identified by its catalogue slug. It does not explicitly name alternatives or state when not to use it, so it falls short of a 5.

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 burden. It reveals two key behaviors: it prepares but does not execute, and it returns the exact request and price. This is valuable, but it omits other behavioral aspects like payment authentication, idempotency, or error conditions. Still, the disclosure is honest and material.

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 fluff. The core purpose and the critical non-execution constraint are front-loaded, and the rest is concise. It 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?

The description covers the immediate action and result, and an output schema exists, so return format is handled. However, it does not explain how to obtain a valid slug, what 'inputs' should contain, or any prerequisites for a paid invocation (e.g., authentication). These gaps make the tool hard to use correctly without external knowledge.

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 provides no explanation of 'slug' or 'inputs'. It doesn't clarify how to obtain a slug or what structure 'inputs' should take. The description adds no semantic value beyond the parameter names themselves, leaving the agent to 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?

The description clearly states the tool's purpose: 'Prepare a paid invocation of one live Agent Shop service' and clarifies it returns the x402 HTTP request and price without executing. This distinguishes it from sibling tools like get_service (view details) and list_services (enumerate), though it doesn't name them 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 description implies usage: it's for preparing an invocation, not executing it. It explicitly notes what it does NOT do ('does not execute the service or bypass payment'), which hints at a boundary, but it lacks explicit guidance on when to choose this over siblings or any prerequisites (e.g., need a slug from a prior search).

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 of behavioral disclosure. 'List services currently available' implies a read-only, filtered snapshot, which is a useful behavioral trait. However, it does not mention pagination, ordering, or whether authentication is required, leaving some room for 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 one concise sentence with no filler or redundant phrasing. Every word adds meaning: 'List', 'services', 'currently available', and 'Atinamos Agent Shop' all contribute to scoping the operation.

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 parameterless listing tool with an output schema, the description is nearly complete. It names the resource and scope, but it could be more complete by indicating how it relates to sibling tools like market_search, which likely overlaps in purpose.

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 description doesn't need to document any. The schema coverage is trivially 100%, and the baseline for no-parameter tools is 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 is clear and specific: it uses the verb 'List' with the resource 'services' and a scope qualifier ('currently available from the Atinamos Agent Shop'). It distinguishes itself from get_service and invoke_service by implying a bulk, read-only listing operation, though it does not explicitly differentiate from market_search or market_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?

There is no guidance about when to use this tool instead of the siblings, such as get_service or market_search. The phrase 'currently available' hints at freshness, but no explicit context or exclusions are given, leaving the agent to infer when this is the right tool.

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 transparency burden. It usefully discloses that results are observational evidence and not a guarantee of current availability or trustworthiness. It does not mention authentication needs, rate limits, failure behaviors, or whether results may be stale, but the caveat adds meaningful context beyond the basic purpose.

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 that immediately states the action and resource, then adds a valuable caveat. There is no filler or redundant repetition of the tool name.

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 two-parameter search tool with an output schema, the description covers the essential purpose and a key data-quality caveat. However, it lacks explicit guidance on choosing this tool over siblings and leaves parameter behavior largely implied, so the overall context is adequate but not fully complete.

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 explaining query and limit semantics. It does not clarify how query is matched, what fields are searched, or how limit affects pagination. The terms are self-explanatory at a basic level, but the description adds no parameter-specific meaning 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?

The description clearly identifies a specific verb and resource: search machine services observed by Atinamos harvesters. It distinguishes itself from likely siblings by emphasizing external discovery sources and observational evidence, making it clear this is a search tool rather than a retrieval, invocation, or listing 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 implies the intended context: searching externally observed machine services rather than confirming availability or endorsing them. However, it does not explicitly state when to use this tool over list_services, get_service, invoke_service, or market_service, nor does it provide exclusions or alternative routing 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 the full burden for behavioral disclosure. It communicates that the operation is a read-only 'Get' from a 'live' registry, which is useful, but it does not mention error behavior, freshness guarantees, authentication, or what happens when the ID 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?

The description is a single, front-loaded sentence with no filler. The only minor issue is redundancy: 'Atinamos' appears twice, and terms like 'observed' and 'live' may be jargon-heavy but are still informative.

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 one-parameter getter with an output schema, the description is mostly adequate. However, it does not clarify how this tool differs from 'get_service', and the terms 'observed machine service' are left undefined. The lack of annotations and alternative guidance creates a meaningful gap.

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% and the schema only describes service_id as an integer. The description adds useful meaning by identifying it as the 'canonical Atinamos service ID', which is the key semantic needed to invoke the tool correctly. It could go slightly further by explaining what 'canonical' implies, but for a single parameter this is adequate.

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 states a specific action ('Get'), a specific resource ('one observed machine service'), and a lookup key ('canonical Atinamos service ID'). It clearly indicates a single-item retrieval rather than a list or search, though it does not explicitly differentiate itself from the sibling 'get_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?

The description implies the appropriate use case: retrieve one service when you have its canonical Atinamos service ID. However, it gives no explicit guidance about when not to use this tool or how it compares to alternatives such as get_service or market_search.

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