get_competitor
Returns full comparison data for a single competitor by slug — wedge, features, FAQs, and the MatFlow vs competitor matrix.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Competitor slug |
Returns full comparison data for a single competitor by slug — wedge, features, FAQs, and the MatFlow vs competitor matrix.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Competitor slug |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes what data is returned but does not disclose behavioral traits such as whether it is read-only, rate limits, or side effects. For a read operation, stating it is non-destructive would add value.
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, front-loaded with action and key components, no wasted words. Efficiently conveys the tool's purpose and output.
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 1 parameter and no output schema, the description sufficiently enumerates the returned components (wedge, features, FAQs, matrix). However, a bit more detail on the structure or format would be helpful for complete understanding.
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 description coverage is 100% (slug with enum and description). The tool description does not add extra meaning beyond the schema's parameter documentation. 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 verb 'Returns' and resources: 'full comparison data for a single competitor by slug', listing specific components (wedge, features, FAQs, matrix). It distinguishes from siblings like 'list_competitors' which only lists competitors.
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 to get detailed data for a single competitor, but does not explicitly state when to use this vs alternatives like 'list_competitors' for listing. No when-not or exclusions are provided.
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 has a clearly distinct purpose: retrieving competitor details, listing competitors, FAQs, pricing, and features. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., get_competitor, list_features). No deviations.
Five tools is an ideal size for a product information server. Each tool has a specific role, no redundancy, and the set feels well-scoped.
The tool set covers key information areas: competitor comparisons (list and detail), FAQs, pricing plans, and feature catalog. No obvious gaps for the domain.