Where a product sits on price against its category: starting price vs the category median, min, max and sample size — the most citable one-line stat.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Product slug. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description discloses output components but not behavioral aspects like error handling, data freshness, or whether it's read-only.
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-loads key purpose; no wasted words, though structure could be improved with lists for clarity.
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 no output schema or annotations, description explains return values (median, min, max, sample size) and context; lacks edge-case handling but adequate for a simple tool.
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 has 100% coverage for the single slug parameter with basic description; the tool description adds context about output but not parameter semantics beyond what schema provides.
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 it returns price positioning statistics (starting price vs category median, min, max, sample size) for a product, distinguishing it from siblings like get_pricing or get_price_history.
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?
Implies use when needing price positioning compared to category, but no explicit guidance on when to use over alternatives like get_pricing or calculate_tco.
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: from TCO calculation to comparison, discovery, LLM cost estimation, negotiation guides, hidden costs, positioning, price history, and full pricing records. No two tools overlap significantly; they complement each other.
All tool names follow a consistent verb_noun pattern with lowercase and underscores, primarily using 'get_' for five tools and other specific verbs like 'calculate', 'compare', 'discover', 'estimate'.
With 9 tools, the server is well-scoped for a pricing analysis domain, covering essential queries without being overwhelming or sparse.
The tool surface comprehensively covers the pricing domain: discovery, comparison, detailed pricing, hidden costs, TCO, price history, positioning, and negotiation advice. No obvious gaps are present for the intended use case.
