get_tech_stack
CMS, booking platform, email provider, analytics detected on a target URL.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
bizintel
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
C2.3/5.0
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fails to disclose any behavioral traits such as whether it is read-only, if it initiates external requests, or if there are rate limits. With no annotations provided, this is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, which might be seen as concise, but it lacks necessary detail. It is front-loaded with the key capability but too terse to be fully useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is an output schema (not shown), the description does not hint at the return structure, pagination, or error handling. For a detection tool, this incompleteness reduces agent confidence.
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?
The input schema has 0% description coverage for the 'url' parameter. The description only mentions 'target URL' but does not clarify format, required protocol, or if the URL must be the domain or full path, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool detects CMS, booking platform, email provider, and analytics on a target URL. This distinguishes it from sibling tools like audit_website or find_no_booking, though it could be more explicit about the 'get' action.
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?
No guidance on when to use this tool versus sibling tools such as audit_website or bulk_audit. The description does not specify conditions, prerequisites, or alternatives, leaving the agent to infer usage.
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
B3.3/5.0
Disambiguation5/5
Each tool has a clearly distinct purpose: audit vs bulk audit, finding leads with specific conditions, searching, getting details, tech stack, and lead scoring. No overlap that would cause confusion.
Naming Consistency5/5
All tool names follow a consistent verb_noun snake_case pattern (e.g., audit_website, find_no_booking, get_business_details). Verbs are descriptive and nouns clearly indicate the target.
Tool Count5/5
With 8 tools, the set is well-scoped for a business intelligence server. It covers core operations without being bloated or insufficient.
Completeness4/5
The tools cover lead discovery, auditing, and scoring comprehensively. Minor gaps: no detailed audit breakdown beyond score, no export or note-saving functionality, but these are not core to the stated purpose.