Find related service pages, blog posts, resources, glossary terms, case studies, and marketplace news for a topic.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Default 12, max 30. | |
| query | Yes | Topic or service area. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so description does not need to reiterate safety. Description adds that it finds 'related' pages for a topic, but no additional behavioral context (e.g., whether results are ranked or filtered). No contradiction with annotations.
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 of 20 words, clear and front-loaded. Every word adds value - 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?
No output schema exists, but description does not hint at return format (e.g., titles, links, pagination). For an aggregation tool, it should mention the structure or ordering of results. Given simple parameters, a bit more context would help 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?
Schema coverage is 100% - both parameters have descriptions. The description adds minor context ('topic or service area' and 'Default 12, max 30'), but does not significantly enhance understanding 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 states the verb 'Find' and lists the resource types (service pages, blog posts, etc.). It distinguishes itself from sibling search tools by implying aggregation across types, but does not explicitly differentiate, so not a 5.
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 sibling search tools (e.g., search_case_studies, search_glossary). It does not state that it returns results from multiple types, which is the key differentiator.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes (e.g., blog_generator vs. get_blog_post), but there is overlap among some content validation tools (csv_cleaner, duplicate_sku_finder, inventory_checker, product_catalog_validator) which could cause confusion. Also, compare_services and search_services serve similar functions.
Tool names mix styles: some use noun_verb (amazon_listing_manager), others verb_noun (compare_services), and there are multiple prefixes like get_, search_, list_. This inconsistency may hinder an agent's ability to predict tool names.
With 35 tools, the set is large and covers many subdomains. This could overwhelm an agent, making selection challenging. A more focused subset would improve coherence.
The tools cover a broad range of ecommerce operations: listing management for multiple platforms, content generation, data validation, research, and reporting. However, missing update/delete capabilities and some platform interactions limit full lifecycle coverage.
