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Space-C0wboy

ReliaQuest GreyMatter MCP Server

by Space-C0wboy

customer_playbooks

Queries playbooks for a customer, enabling retrieval of automation workflows with filtering by type and creation date, ordering, and pagination.

Instructions

Playbooks · query customerPlaybooks. Variables: after, filter, first, order. Example variables: {"after":"T18w","filter":{"created":{"earliest":"2026-05-01T00:00:00.000Z","latest":"2026-05-01T00:00:00.000Z"},"types":["CONFIGURATION_CHANGED"]},"first":10,"order":{"direction":"ASC","orderBy":"CREATED_AT"}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNoGraphQL: String
firstNoGraphQL: Int
orderNoGraphQL: IntegrationActivityLogOrder
filterNoGraphQL: IntegrationActivityLogFilter
customer_slugNoOverride the x-reliaquest-customer (OpCo) header.
Behavior2/5

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

The description only says 'query', implying a read operation, but with no annotations provided, the agent cannot know about pagination behavior, rate limits, or permissions. It does not disclose any side effects or additional behavioral traits beyond what 'query' implies.

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 a single line plus one example JSON block, which is compact and includes a helpful example without extra prose. It is efficient and front-loaded with the operation name and variables.

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?

No output schema is provided, and the description does not explain the return shape, pagination semantics beyond the presence of after/first, or the meaning of filter fields. For a GraphQL query tool, this is sparse; the example helps but leaves many gaps.

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?

The description lists variables after, filter, first, order and provides a JSON example showing how to structure filter and order, which adds some value beyond the schema's minimal 'GraphQL: String' descriptions. However, it omits the customer_slug parameter, and the schema descriptions are just type references, so the example only partially compensates.

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 'query customerPlaybooks', providing a specific verb and resource. It distinguishes from mutation siblings like upsert_customer_playbook, but does not explicitly differentiate from the sibling 'playbooks' beyond the customer prefix.

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 alternatives such as playbooks or recommended_playbooks. The description only lists variables and an example, with no mention of use cases, exclusions, or prerequisites.

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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