Skip to main content
Glama
dfch

io.github.dfch/biz-dfch-asdste100mcp

Official
by dfch

rules_examples

Read-only

Fetch ASD-STE100 rule content and examples, filtering by rule ID, section, category, or content type. Use pagination to navigate large result sets and locate relevant compliance examples.

Instructions

Return content items across rules, optionally scoped and filtered.

Parameters

id_: When given, only consider the rule with this exact id (case-insensitive). section: When given, only consider rules in this exact section (case-insensitive). category: When given, only consider rules in this exact category (case-insensitive). kind: When given, only return content items of this type (e.g. "ste_example"). max_results: The maximum number of matching content items to return (default 25). offset: The number of matching content items to skip before returning results, for pagination (default 0).

Returns

RulesExamplesResult results holds the (possibly empty) page of matching content items, in document order, after applying offset and max_results. total is the full match count before pagination, and truncated tells the caller whether more content items exist beyond this page. Unfiltered, the ruleset can hold well over a thousand content items, so pagination matters here even though the ruleset itself only has a few dozen rules.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
id_NoOnly consider the rule with this exact id (case-insensitive).
kindNoOnly return content items of this exact type, e.g. 'ste_example'.
offsetNoThe number of matching entries to skip before returning results, for pagination.
sectionNoOnly consider rules in this exact section (case-insensitive).
categoryNoOnly consider rules in this exact category (case-insensitive).
max_resultsNoThe maximum number of matching entries to return.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
offsetYes
resultsNo
truncatedYes
max_resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

A3.9/5.0
Behavior5/5

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

Annotations already mark the tool read-only and non-destructive; the description adds substantial behavioral detail: exact case-insensitive filters, document-order results, offset/max_results pagination semantics, total/truncated fields, and the warning that the unfiltered ruleset can exceed a thousand content items. No contradiction with annotations.

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

Conciseness4/5

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

The description is front-loaded with a one-sentence summary and organized into clear Parameters and Returns sections. It is somewhat long and duplicates schema parameter descriptions, but the return-semantics explanation earns its place.

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?

With zero required parameters and all filters optional, an agent can call this tool correctly and interpret pagination without guesswork. It is complete for invocation, though explicit guidance on how it differs from the many sibling search/filter tools would strengthen it.

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

Parameters3/5

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

Schema description coverage is 100%, so the parameters are already fully documented. The description mostly restates the schema plus a minor 'ste_example' example and pagination note, adding little meaning beyond what the input schema provides.

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 first sentence states a specific verb and resource: returning content items across rules, with optional scoping and filtering. This clearly distinguishes it from rule-metadata tools like rules_overview or rules_toc, though it does not explicitly name sibling tools.

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?

The description gives clear context about what the tool does and why pagination matters, but it never says when to prefer this tool over siblings like rules_search or rules_find, nor does it state exclusions or when-not-to-use conditions.

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