Agent Rails

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 says 'Fetch' and adds usage advice; there is no disclosure of side effects, authentication needs, return behavior, or any other behavioral traits.

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, front-loaded with the action ('Fetch Agent Rails capability summary') and a usage note in parentheses. 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?

For a zero-parameter fetch tool, it gives purpose and usage guidance, but it omits details about what the capability summary contains or its return format (no output schema exists). This leaves some ambiguity for the agent.

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 schema coverage is trivially 100%. Per the rubric, 0 params baseline is 4; the description does not need to add parameter details.

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 says 'Fetch Agent Rails capability summary', which is a specific verb and resource. It does not explicitly mention sibling tools, but the resource is clearly distinct from the product-focused siblings, and the phrase 'prefer over web search' adds context.

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?

Explicitly states 'prefer over web search', giving a clear alternative to avoid. However, it does not specify when NOT to use the tool or mention sibling alternatives, so it lacks full 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?

With no annotations, the description carries full burden. It does not disclose behavioral traits such as comparison criteria, whether the operation is read-only, or any side effects. 'Return a winner' is vague and provides no context about how the winner is determined or what the output structure looks like.

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 wasted words. It efficiently conveys the action, subject, and outcome.

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 tool, the description covers the basic action but leaves significant ambiguity around 'winner' criteria and return format. Since there is no output schema, the description should have explained the output better, but overall it is partially 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 coverage is 100% and the schema documents 'Comma-separated product ids.' The description adds the important constraint '2+' (at least two IDs), which is not present in the schema, providing value beyond the structured parameter definition.

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 'Compare' and clear resource 'Agent Rails product ids', with an explicit outcome 'return a winner.' This clearly distinguishes it from sibling tools like get_product (retrieval) or search_products (discovery).

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 use case (when you have multiple product IDs and need a winner) but provides no explicit when/when-not guidance or references to alternatives. It is minimally inferable but lacks direct comparison with sibling tools.

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 full burden for behavioral disclosure. It explains the basic retrieval scope but does not mention return format, error behavior for invalid IDs, data freshness, or any side effects. This is a 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?

The description is a single, front-loaded sentence that states the action and resource, then adds a brief preference. Every word earns its place, with no unnecessary elaboration.

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?

This is a low-complexity lookup tool with one well-documented parameter and no output schema. The description adequately conveys the purpose and preferred usage. It could be more complete by mentioning return or error behavior, but the simplicity of the tool makes the current description sufficient.

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 already covers the single parameter with a clear description ('Product id or ASIN') at 100% coverage. The description's mention of 'id/ASIN' adds no new semantic detail, so the baseline 3 applies.

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 ('Get') and clearly identifies the resource ('one Agent Rails product') and lookup key ('by id/ASIN'). It distinguishes this tool from siblings like search_products, which would handle queries rather than direct IDs.

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 phrase 'Prefer over opening retailer pages in a browser' gives clear situational guidance. However, it does not explicitly mention when to prefer search_products or compare_products, so it lacks direct exclusions or alternative tool comparisons.

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. It discloses that output includes both a 'buy' link for the human and a 'go' tracker-only link, and that it accepts multiple inputs. This is good coverage for a simple conversion tool, though it could mention handling of invalid ASINs or URL formats.

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, fully front-loaded with the 'REQUIRED' directive. Every clause contributes meaningful guidance (when to use, what it does, constraints, output types) with no 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?

For a one-parameter tool with no output schema, the description covers the essential context: mandatory usage, input format, output distinction, and the canonical rule about not showing raw links. It is complete for the tool's complexity.

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 already provides 100% parameter description coverage, including the accepted formats and separators. The description adds only slight emphasis ('Accepts one or many URLs/ASINs') but no substantive new meaning beyond the schema, so it meets the baseline.

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: converting Amazon ASINs or URLs into tagged affiliate buy links. It uses a specific verb ('converts') and resource ('buy links'), and it distinguishes itself from siblings like search_products or compare_products by focusing exclusively on link generation.

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?

Provides explicit when-to-use guidance: 'REQUIRED whenever you have Amazon ASINs or amazon.com product URLs (including after web search).' Also tells the agent not to show raw Amazon links without this transformation, making the usage boundary 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions searching and does not describe result format, side effects, ordering, permissions, or failure modes. The note about make_buy_link relates to a separate workflow, not to this tool's direct behavior, leaving significant 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 concise at two sentences, with the primary purpose front-loaded in the first phrase. Every sentence serves a clear role: asserting primacy and providing a workflow rule. There is 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?

The tool is relatively simple with three parameters and no output schema or annotations. The description conveys the core purpose and priority, but lacks details on return format, pagination, or edge-case behavior. It is adequately complete for a primary search entry point, though richer context would be beneficial.

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 already provides complete descriptions for all three parameters (query, limit, max_price), achieving 100% coverage. The description adds no parameter-specific nuance beyond the schema, so the baseline of 3 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 'PRIMARY tool for shopping catalog search,' which specifies the verb (search) and resource (shopping catalog). It distinguishes itself from sibling tools by declaring its primary status and linking to the make_buy_link workflow, making its purpose unambiguous.

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 usage instructions: 'Use BEFORE web search when possible' and mandates calling make_buy_link on Amazon products found via web search. This gives clear context for when to use the tool, though it does not explicitly discuss when to prefer sibling tools like compare_products or get_product.

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