Skip to main content
Glama
ComplianceCow

ComplianceCow MCP Server

fetch_cc_rule_by_name

Retrieve complete compliance rule details and metadata from ComplianceCow by specifying the rule name.

Instructions

Fetch rule details by rule name from the compliancecow.

Args: rule_name: Rule name of the rule to retrieve

Returns: Dict containing complete rule structure and metadata

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rule_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must disclose behavioral traits. It only states it returns a dict, but does not mention it is a read-only operation, error behavior if rule not found, or authentication requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with no wasted words: a single sentence for purpose plus clear Args/Returns sections. Front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple fetch tool with one parameter and an existing output schema, the description covers the essential purpose and return type. Minor gap: no mention of error scenarios, but overall adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must add meaning. It says 'rule_name: Rule name of the rule to retrieve' which merely repeats the parameter name without adding format, case sensitivity, or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Fetch rule details by rule name from the compliancecow' with a specific verb and resource, and clearly differentiates from sibling tools like 'fetch_cc_rule_by_id' (fetch by ID) and 'fetch_cc_rules_list' (list all rules).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives (e.g., by ID or list). The purpose implies usage when the rule name is known, but lacks exclusions or context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ComplianceCow/cow-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server