get_competitor_pricePrice statistics (min/max/avg/median) plus recent product samples for a brand, optionally filtered by product-name query. Freshness-stamped. 1 credit; no data = no charge.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Sample size, default 10 | |
| query | No | Optional product-name filter, e.g. "leggings" | |
| domain | Yes | eCommerce domain |
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 results are 'freshness-stamped' and no charge if no data, but does not describe rate limits, what happens on errors, or pagination behavior for samples. Adequate but not comprehensive.
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 totaling ~25 words, with key information front-loaded: what is returned, optional filter, freshness, and cost. No unnecessary 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 the tool has 3 parameters and no output schema, the description effectively communicates the core output and cost model. However, it could be improved by briefly describing the structure of the returned price statistics (e.g., 'returns an object with stats and an array of samples').
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%, so parameters are documented. The description adds value by noting the 'query' parameter is an optional product-name filter and mentions 'Freshness-stamped', linking to data timeliness. It also implies 'limit' controls sample size.
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 provides price statistics (min/max/avg/median) and recent product samples for a brand, optionally filtered by product-name query. This is a specific verb+resource combination. However, it does not explicitly differentiate from sibling tools like get_brand_snapshot or get_history, which could also involve brand data.
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 mentions cost ('1 credit; no data = no charge') and optional filtering, but does not provide guidance on when to use this tool versus siblings like get_promotions or get_readiness_score. Usage context is implied but not explicit.
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.