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MarkAC007

mcp-server-scf

by MarkAC007

scf_list_engagements

Read-only

List audit engagements for an organization, showing frameworks, status, dates, and catalog version. Filter by status to review draft, active, under review, or closed engagements.

Instructions

List the organization's audit engagements (read — viewer role). Each entry carries its frameworks, status, dates and the catalog version its scope was frozen against.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
org_idYesOrganization UUID — obtain from scf_list_organizations
statusNoFilter by engagement status: draft, active, under_review or closed

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv3.4.2
    • changedInput schema / properties / status / description
      Previous value: -"Filter by engagement status (e.g. 'planning', 'fieldwork', 'closed')"New value: +"Filter by engagement status: draft, active, under_review or closed"
    • addedInput schema / properties / status / enum
      Added value: +[
      +  "draft",
      +  "active",
      +  "under_review",
      +  "closed"
      +]
  2. Addedv2.1.0

TDQS

A4.2/5.0
Behavior4/5

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

The annotations already provide readOnlyHint=true, and the description reinforces this with 'read — viewer role.' It also adds useful behavioral detail about the returned entries (frameworks, status, dates, catalog version), going beyond the annotation. No contradictions. Minor omissions like pagination or ordering are not critical for a read-only list tool.

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?

Two compact sentences with no wasted words. The main action is front-loaded, and the read-only role and output content are stated efficiently.

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 read-only list tool with an optional filter, the description is complete enough: it states purpose, scope, and output content. It does not explicitly mention pagination or ordering, but these are not essential given the simple schema and read-only annotation.

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%: org_id and status both have descriptive schema text. The description adds no parameter-level semantics beyond the schema, so the baseline of 3 applies.

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 the specific verb and resource: 'List the organization's audit engagements.' The phrase 'organization's' distinguishes it from sibling scf_list_my_engagements and the 'read — viewer role' hint clarifies its read-only nature. No ambiguity about what the tool does.

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

Usage Guidelines4/5

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

Provides clear context that this is an org-scoped read operation for viewer role, which implicitly differentiates it from scf_list_my_engagements and mutation tools like scf_create_engagement. However, it does not explicitly name alternatives or state when not to use this tool, leaving some inference to the agent.

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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