Get the summary and URL of a specific SearchShopAI Research Note by its slug (returned by search_research_notes).
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The note slug, e.g. 'the-ai-attribution-blind-spot' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read. The description adds that it returns summary and URL specifically. No contradictions, but no further behavioral details beyond 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, no wasted words. Front-loaded with action and resource. Efficient and to the point.
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?
Tool is simple with one parameter and no output schema. Description clarifies return fields (summary and URL) and origin of slug. Adequate for a single-note retrieval tool, though lacks response structure details.
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% with a well-described slug parameter including maxLength and example. The description does not add additional meaning beyond the schema; baseline 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 the action 'Get the summary and URL' and the resource 'Specific SearchShopAI Research Note', and specifies the method 'by its slug'. It also distinguishes from sibling search_research_notes by noting the slug comes from that 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 usage sequence: first use search_research_notes to get slugs, then this tool. It does not explicitly state when not to use or list alternatives, but the context is clear enough for an agent to infer correct usage.
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, but there is clear overlap between 'recommend' and the deprecated 'skincare_recommend', and 'shop' as a routing tool could be ambiguous with 'search_products' and 'recommend'. Descriptions help but are not fully disambiguating.
Naming patterns are inconsistent: some use verb_noun (e.g., check_inventory, compare_products), while others are single words (shop) or use a noun prefix (skincare_cart, skincare_recommend). The deprecated duplicate 'skincare_recommend' further disrupts consistency.
14 tools is well within the 3-15 range and covers the necessary functions for a skincare commerce server: product lookup, search, recommendation, comparison, compatibility, inventory, checkout, deals, research notes, and issue reporting. No excess or deficiency.
The tool set covers core commerce workflows: browsing, product details, recommendations, checkout, deals, and compatibility checks. Minor gaps exist (e.g., order history or user profile management) but are outside the apparent scope. The deprecated duplicate is a minor inefficiency.