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by ai.trydock

create_row

Append a new row to a workspace's table surface. The data field is a JSON object with column-name keys. Status column accepts: drafted, queued, sealed, active, blocked. Works on any workspace; columns auto-seed on the first row if the table surface is empty. Multi-surface workspaces accept surface_slug to target a specific sheet (use list_surfaces to enumerate); omit it to fall through to the workspace's primary table surface.

Unmapped data fields: Keys in data that don't match any existing column are still STORED on the row (nothing is dropped), but they won't render in the table UI until the column exists. The response carries an unmapped_fields array listing those keys plus a human-readable warning so an agent can decide whether to surface them, call add_column, or retry with auto_create_columns: true.

Auto-create columns: Pass auto_create_columns: true to have the server append a fresh text column for every unmapped key in one atomic step (humanised label from the key, type text). The response then includes created_columns: ColumnDef[] with the new column metadata. Use this when you're appending machine-emitted rows whose shape you can't predict ahead of time; leave it omitted (default false) when you want explicit schema control.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesRow data as a JSON object (e.g. {"title": "My post", "status": "drafted", "notes": "Initial draft"})
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 table surface slug for multi-surface workspaces. Omit to write to the workspace's primary table surface. 400 if the slug is a doc surface, archived, or doesn't exist.
auto_create_columnsNoWhen true, the server auto-creates a text column for every key in `data` that doesn't already exist on the surface, then writes the row in the same call. Returns `created_columns` in the response listing the new column defs. Default false: unmapped keys are still stored on the row but won't render in the UI until you `add_column` them yourself.

TDQS

A5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that unmapped fields are stored but not rendered, that auto-create columns happen atomically with humanised labels, and that responses include unmapped_fields, warning, and created_columns. It also discloses fallback to the primary table surface and auto-seeding on empty tables.

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 structured into three targeted paragraphs with bold headers, leading with the core action. Each paragraph earns its place by covering primary behavior, unmapped-field handling, and the auto-create option without redundancy or filler.

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?

Even without an output schema, the description covers return values (unmapped_fields, warning, created_columns) and error contexts (invalid surface_slug yields 400, noted in the schema). It fully explains edge cases like empty tables, multi-surface workspaces, and unmapped data, providing everything an agent needs to invoke the tool correctly.

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?

The input schema documents all four parameters, but the description adds substantial meaning: data keys map to column names, status accepts a fixed set, surface_slug has explicit fallback behavior, and auto_create_columns is explained with atomic creation and return metadata. This goes far beyond the schema's simple property descriptions.

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 opens with 'Append a new row to a workspace's table surface,' a specific verb+resource that clearly distinguishes it from siblings like update_row and delete_row. It also identifies the data field as a JSON object with column-name keys and lists allowed status values, making the tool's purpose unmistakable.

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?

The description explicitly instructs when to use surface_slug (multi-surface workspaces) and points to list_surfaces as the enumeration method. It differentiates when to use auto_create_columns (machine-emitted rows) versus omitting it for explicit schema control, and names add_column as an alternative for handling unmapped fields.

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