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christianclaudio

mcp-server-sigma

Workbooks List Workbook Agents

workbooks_list_workbook_agents
Read-only

List AI agents defined in a specific workbook, with optional filtering by version tag. Use it to inspect available agents before managing or deploying them.

Instructions

List AI agents defined in a specific workbook (optionally filtering by version tag).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workbook_idYes
version_tag_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.4

TDQS

B3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds almost nothing behavioral beyond that — no note on scoping rules, permissions, result size, or what an 'agent' object represents here.

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?

A single well-formed sentence with the resource stated first and the optional filter in a trailing parenthetical. It is efficient and front-loaded, though it is arguably too terse for a tool with zero schema documentation.

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

Completeness3/5

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 need not be described, and this is a simple two-parameter read. Still, the required workbook_id is undocumented in both schema and description, leaving a gap for an identifier whose format an agent cannot infer.

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 two parameters rely entirely on narrative. The description hints that version_tag_name is an optional filter, but says nothing about workbook_id's expected form (ID vs name), nor the version tag's syntax or matching behavior.

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?

States a specific verb (List) and resource (AI agents defined in a specific workbook), which distinguishes it from workbooks_run_workbook_agent and admin_list_org_workbook_agents. It does not name those siblings explicitly, but the workbook-scoped framing makes the target set unambiguous.

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 parenthetical about version tagging implies the intended filtering use case, so usage is inferable. However, it never states when to reach for this tool versus the org-level agent listing or the run-agent tool, and gives no preconditions or exclusions.

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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