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by ai.trydock

move_rows

Atomically move N rows from their current sheet(s) to a target sheet inside the same workspace. Use for programmatic data migration: dropping a batch of agent-produced drafts onto the right sheet, reorganizing content across LinkedIn / Twitter / Substack tabs, etc. All-or-nothing: if any rowId doesn't belong to this workspace, the entire batch fails before any write fires. Idempotent: rows already on the target sheet are skipped (returns skipped count). Rows land at the destination sheet's tail in the order rowIds was supplied. Emits one row.moved_surface event per row that actually moved. Up to 500 rows per call.

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.
rowIdsYesRow IDs to move (1-500). Order is preserved at the destination: first id lands at the lowest position, last id at the highest.
target_surface_slugYesSlug of the destination table surface. Use list_surfaces to enumerate. 400 if the slug is a doc surface, archived, or not in this workspace.

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the behavioral disclosure burden. It details atomicity (all-or-nothing failure), idempotency (skipping existing rows), ordering, event emission, and the 500-row limit. This is exemplary for a mutation tool.

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 information-dense: every sentence adds a distinct behavioral or usage detail (atomicity, use cases, failure mode, idempotency, ordering, eventing, limit) without fluff. It is well-structured and front-loaded with the primary action.

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?

Despite having no output schema, the description covers all essential operational aspects: atomicity, failure conditions, idempotency, ordering, events, and limits. It is complete enough for an agent to understand the tool's behavior and side effects.

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?

The input schema already provides 100% parameter coverage, describing each parameter (slug, rowIds, target_surface_slug) with its constraints and format. The tool description adds no additional parameter-level meaning beyond what the schema documents, so the baseline score applies.

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 a specific verb+resource: 'Atomically move N rows from their current sheet(s) to a target sheet inside the same workspace.' It clearly distinguishes itself from sibling tools like create_row, delete_row, and update_row by focusing on moving existing rows between sheets.

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 concrete use cases ('dropping a batch of agent-produced drafts onto the right sheet, reorganizing content across LinkedIn / Twitter / Substack tabs') which establish when to use this tool. It does not explicitly name alternative tools for other operations, but the context is clear.

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