Get industry benchmarks (engagement rate, conversion rate, etc.) for a business type.
| Name | Required | Description | Default |
|---|---|---|---|
| businessType | No | Industry name or slug (e.g. 'restaurants', 'coffee-shops'). Omit for the full catalog. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / businessTypeAdded value: +{
+ "description": "Industry name or slug (e.g. 'restaurants', 'coffee-shops'). Omit for the full catalog.",
+ "type": "string"
+}Input schema / properties / industryRemoved value: -{
- "type": "string"
-}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for disclosing side effects or constraints. It merely says 'get' without noting read-only semantics, authentication requirements, error behavior, or data source/reliability. The examples of metrics offer slight return-value context but no behavioral depth.
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 of 14 words, immediately leading with the verb and resource. It is free of filler and every word 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?
For a simple lookup tool with one optional parameter and no output schema, the description conveys the essential purpose. However, it does not detail the structure of benchmark results, how metrics are calculated, or edge cases. It is minimally adequate but leaves some gaps.
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%—the businessType parameter already has a description including the 'Omit for the full catalog' behavior. The description text adds no new semantic detail beyond what the schema provides, matching the baseline for full coverage.
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 the tool's action ('Get') and resource ('industry benchmarks') with concrete examples (engagement rate, conversion rate). This distinguishes it from sibling tools like getCampaignStats, which focuses on campaign-level data, and getPricing, which handles pricing information.
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 for retrieving industry benchmarks by business type, but does not explicitly state when to use it over alternative tools or provide any exclusions. It lacks guidance on scenarios such as comparing against campaign stats or when to omit the businessType parameter.
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.
Each tool targets a distinct resource and action: campaigns, submissions, benchmarks, pricing, actions, influencers. No two tools have overlapping purposes; even getBenchmarks vs getPricing are clearly separated by context.
All tool names follow a consistent verb_noun pattern in camelCase (e.g., createCampaign, listActions, reviewSubmission). The verbs are varied but the structure is uniform, making the set predictable.
10 tools is well within the ideal 3-15 range and matches the server's scope: campaign creation, stats, submissions, and reference lookups. Each tool earns its place without bloat.
Core lifecycle coverage is solid: create/list/get stats for campaigns, submit/review submissions. Minor gaps exist (no update/delete campaign, no single-submission detail view), but agents can work around them using existing tools.