get_promotionsActive promotions/discount codes for a brand: code, discount type/value, min order, validity window. Freshness-stamped. 1 credit; no data = no charge.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | eCommerce domain |
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 notes 'Freshness-stamped' and 'no data = no charge', but lacks disclosures on authentication needs, error handling, or what happens with invalid domains.
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 concise sentences, front-loaded with the core purpose and key return fields. No wasted words.
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?
Given a single parameter and no output schema, the description adequately explains what is returned and notes freshness and cost. Could be slightly more detailed about response format (e.g., array) but overall 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 input schema has 100% coverage with a single parameter 'domain' described as 'eCommerce domain'. The description adds minimal extra meaning beyond the schema, only hinting at 'brand' context.
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 specifies the verb 'get' and resource 'promotions', enumerates the returned fields (code, discount type/value, min order, validity window), and differentiates from siblings like 'get_brand_snapshot' which cover broader brand info.
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 explicit guidance on when to use this tool over alternatives. The description implies it is for active promotions, but does not mention exclusions or provide context for choosing among siblings.
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 aspect of competitive intelligence: coverage, snapshot, price, history, promotions, readiness, and monitoring request. There is no overlap or ambiguity.
Most tools follow a 'get_' prefix pattern, but 'request_monitoring' uses 'request_'. This slight inconsistency is justified by the different action type (request vs. retrieve), but still deviates from the predominant convention.
With 7 tools, the set is well-scoped for a competitive intelligence server. Each tool serves a distinct need without being overwhelming or too few.
The tools cover the main competitive signals: snapshot, price, history, promotions, readiness, and domain monitoring. Minor gaps like listing all monitored domains are absent, but the core workflows are complete.