get_pricing
Normalized pricing.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes |
StackResolve
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
D1.5/5.0
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but 'Normalized pricing' reveals nothing about side effects, read-only behavior, data transformation, or output characteristics. The agent has no idea what normalized means or what happens when the tool is invoked.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two words, which is under-specification rather than effective conciseness. It omits essential information and provides no structure or front-loaded clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one required parameter, no output schema, and no annotations, the description is completely inadequate. The agent lacks even the basic context needed to invoke the tool correctly or interpret its results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not mention the 'domain' parameter at all. The agent receives no explanation of what domain represents, its format, or its semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Normalized pricing' is a noun phrase with no explicit verb or action, making it unclear what the tool actually does. It vaguely suggests retrieving pricing data but does not clearly state the resource or how it relates to the 'domain' parameter. It borders on tautology with the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like get_usage, get_company, or get_profile. No context about typical use cases, prerequisites, or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
C2.6/5.0
Disambiguation2/5
resolve and find_tools_for_task both return ranked tool recommendations for a task, and how_to also surfaces recommendedTools, making their boundaries unclear. search_tools adds further overlap as a registry search by query and requirements. The company/research and registry lookup tools are more distinct, but the task-to-tool cluster is genuinely confusing.
Naming Consistency4/5
The naming is almost entirely snake_case verb_noun: get_company, find_competitors, search_tools, compare_products, list_registry. The exceptions are audit and resolve as bare verbs and how_to as an idiom, but they are still recognizable.
Tool Count4/5
Fifteen tools is at the upper end of a reasonable range, and the broad scope of registry lookup, research, comparison, audit, and interface generation supports a larger surface. However, find_tools_for_task largely duplicates resolve, so the count is slightly higher than necessary.
Completeness4/5
The server covers the main registry lifecycle: listing, searching, getting records, comparing, researching, pricing, readiness auditing, and generating agent interfaces. It is intentionally read/research-oriented, so the lack of registry CRUD is not a severe gap. Minor missing pieces like direct per-product OpenAPI retrieval or registry entry management are workable around.