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RunWhen Platform MCP

List Knowledge Base Articles

list_knowledge_base_articles

List and filter Knowledge Base articles by status or content in a RunWhen workspace for programmatic KB management and troubleshooting.

Instructions

List Knowledge Base articles (notes) in a workspace (structured JSON).

Returns KB articles that feed the workspace's Knowledge Overlay Graph. Articles can contain operational knowledge, runbook context, architecture notes, or any information useful for troubleshooting.

NOTE: For questions like "what do we know about service X?", prefer workspace_chat — it searches KB articles semantically. Use this tool for programmatic KB management (listing, filtering by status).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax articles to return (max 200).
searchNoSearch within article content.
statusNoFilter by status — 'active' or 'deprecated'. Returns all if omitted.
workspace_nameYesThe workspace to query (e.g. 't-oncall').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It adds useful domain context about what articles feed (the Knowledge Overlay Graph) and the kinds of content they hold, but does not disclose pagination behavior, default/max limits in prose, read-only guarantees, or permission requirements. Adequate but leaves real gaps unaddressed.

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?

Front-loaded with the core action and output format, and the NOTE is high-value routing content. The middle sentence enumerating content types (runbook context, architecture notes, troubleshooting) is somewhat expendable but does aid understanding, keeping this just below maximally 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?

An output schema exists, so return values needn't be explained, and the description covers purpose, alternatives, and content scope. It stops short of explaining pagination or the interaction between the search and status filters, which is a minor omission rather than a blocking gap.

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 schema already documents workspace_name, limit, search, and status. The description reinforces 'filtering by status' but adds no syntax, default, or format detail beyond the schema. Baseline 3 is correct when the schema does the heavy lifting.

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?

States a specific verb (List) and resource (Knowledge Base articles / notes) scoped to a workspace, and clarifies the output format (structured JSON). The NOTE distinguishes it from the semantic-search sibling workspace_chat and from get_knowledge_base_article, so an agent can route correctly without opening a schema.

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

Usage Guidelines5/5

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

Explicit when-to-use/when-not guidance: prefer workspace_chat for semantic 'what do we know about service X?' questions, and use this tool for programmatic KB management (listing, filtering by status). Both the alternative and the selecting condition are named.

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