Skip to main content
Glama

Dock

by ai.trydock

get_workspace_schema

Return a table surface's column definitions so an agent knows what keys create_row/update_row will accept. Each column has key (the field name in row.data), label (human-readable), type (text | longtext | url | status | owner | date | number), position, and, for status/owner columns, the allowed options. Empty array on doc-only workspaces; callers should still be able to write rows (columns auto-seed on first write). Multi-surface workspaces accept surface_slug to scope to a specific table sheet (use list_surfaces to enumerate); omit to fall through to the workspace's primary table surface.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe workspace slug. Accepts either the bare slug ('my-workspace') or the org-prefixed form ('my-org/my-workspace') as shown in the dashboard URL; both resolve to the same workspace.
surface_slugNoOptional. The slug of the specific table surface to read columns from. Omit on single-table workspaces; required on multi-table workspaces if you don't want the primary table surface (lowest position).

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It discloses edge-case behavior (empty array on doc-only workspaces, rows can still be written, columns auto-seed on first write), and explains multi-surface fallback. While it doesn't explicitly state read-only intent, the 'Return' framing and context imply no mutation, and it covers expected structural behavior well.

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?

Four sentences, each serving a distinct purpose: purpose, return fields, edge cases, and parameter guidance. No filler, but the description is a bit dense (about 60 words), so slightly less crisp than the two-sentence ideal. Still informative and well-structured.

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

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must explain the return structure, which it does thoroughly (fields, types, options). It also covers edge cases and parameter behavior, making it complete for a read-only schema tool with 2 parameters, both documented.

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

Parameters5/5

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

Schema covers 100% of parameters, but the description adds valuable meaning: explains slug forms (bare or org-prefixed) and surface_slug selection logic, including that omission uses primary table surface. This goes beyond schema descriptions and helps the agent choose correct values.

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 clearly states the tool returns a table surface's column definitions, with a specific verb ('Return') and resource ('table surface's column definitions'). It also explains the purpose: to know what keys create_row/update_row will accept. This distinguishes it from sibling tools like list_rows or get_workspace.

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?

Explicitly states when to use this tool: when the agent needs to know accepted row keys. It also provides conditional guidance on surface_slug: omit for single-table workspaces, use list_surfaces to enumerate for multi-surface workspaces, and fallback behavior to primary surface. This is clear and actionable.

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

All Dock toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with detailed descriptions that prevent confusion. The main ambiguity arises from send_message vs. the referenced but missing message_teammate tool, and add_column vs. update_surface for schema changes, but these are mostly clarified by the descriptions.

Naming Consistency4/5

The naming convention is predominantly verb_noun with underscores (e.g., create_workspace, list_rows, update_doc). Exceptions like 'search' and 'address_book' (no noun) and the two-word 'react_to_comment' are minor deviations in an otherwise consistent pattern.

Tool Count1/5

With 68 tools, the surface is far too large for an MCP server, exceeding the 50+ threshold for extreme mismatch. This volume creates excessive selection overhead for agents and suggests the tool set could be consolidated or split into focused servers.

Completeness3/5

The server covers broad functionality across workspaces, docs, tables, HTML, comments, files, webhooks, and billing. However, notable gaps exist: the explicitly referenced message_teammate tool is missing (preventing agent-to-agent waking), and there is no create/upload file tool or create API key tool, which creates dead ends in workflows.

Resources