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by ai.trydock

list_rows

List rows in a workspace's table surface. Returns rows with their data (a JSON object of column-name to value), creation time, the principal who created/updated each row, AND the row's surface_slug (the sheet it lives on). Empty array if no rows have been added yet. Multi-surface workspaces: pass surface_slug to scope to one sheet; omit to return rows from every surface in the workspace (back-compat: pre-multi-surface clients keep working).

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.
limitNoMax rows to return (default 100, max 1000)
offsetNoNumber of rows to skip (for pagination)
surface_slugNoOptional table surface slug for multi-surface workspaces. Filter rows to one sheet. Omit to return rows from every surface (legacy single-sheet clients see no change). 400 if the slug is a doc surface, archived, or doesn't exist.

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description discloses return format (column-value JSON, creation time, principal, surface_slug) and empty array behavior. It also explains multi-surface scoping behavior, though it does not mention auth or error cases beyond what's in the schema.

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?

The description is a single compact paragraph with no filler. Every sentence adds value: purpose, return shape, empty result, and multi-surface behavior.

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?

The tool has a moderate parameter count and no output schema, but the description explains return value, behavior, and scoping option. It could mention default limit or sorting, but schema covers limit/offset.

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

Parameters4/5

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

Schema covers 100% of parameters, so baseline is 3. The description adds meaningful context for surface_slug (scoping behavior and back-compat), exceeding baseline.

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 it lists rows in a workspace's table surface and specifies the return fields. This distinguishes it from get_row, create_row, update_row, and delete_row siblings.

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?

The description provides explicit guidance on when to pass surface_slug (multi-surface workspaces) and when to omit (to return all surfaces). It also notes back-compat for pre-multi-surface clients, implying legacy usage.

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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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