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Dock

by ai.trydock

create_support_ticket

File a support ticket. Mirrors to a GitHub issue in Dock's support repo and shows up in the user's dashboard at /settings/support. Use this for bugs (you hit an error), feature requests (Dock is missing something), billing (Stripe/subscription), questions (how do I X), or anything else. Prefer request_limit_increase when the user is simply hitting a plan cap.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesDetailed description (5-10000 chars). For bugs: include what you did, what happened, what you expected. For feature requests: the use case.
kindYesTicket category.
titleYesShort headline (3-200 chars). Be specific: 'Table view loses focus on cell edit' beats 'broken'.
contextNoOptional structured metadata echoed into the GitHub issue (workspace slug, URL, error trace, etc).
attachmentUrlsNoOptional list of screenshot/attachment URLs to embed in the issue. URLs must be hosted on the Dock blob store; mint them via POST /api/support/upload first. Max 4.

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It discloses that the ticket creates a GitHub issue and appears in the user's dashboard, which are important side effects. However, it does not mention any permissions or rate limits, though these are less critical for a support ticket creation tool. The disclosed side effects go beyond basic semantics.

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 three sentences and every sentence provides necessary information: the action and side effect, the list of use cases, and the explicit alternative. It is front-loaded with the verb and resource, and contains no filler or redundancy.

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?

Given the tool's complexity (5 parameters, nested object, no output schema), the description covers the core purpose, use cases, side effects, and an alternative. It does not explain return values, but the lack of an output schema makes that less critical. The attachment URL requirement is covered by the schema, so this is reasonably complete.

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?

Schema description coverage is 100%, so each parameter is already documented in the schema. The description adds general guidance about what kinds of tickets to file, but it does not add detail about parameter formats or constraints beyond the schema. This meets the baseline expectation but does not exceed it.

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 uses a specific verb ('File a support ticket') and clearly identifies the resource, then elaborates on the side effects (mirrors to GitHub issue, appears in dashboard). It distinguishes from the sibling tool request_limit_increase by name, so there is no ambiguity about what this tool does.

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 lists when to use this tool (bugs, feature requests, billing, questions, anything else) and explicitly says to prefer request_limit_increase for plan cap issues. This provides clear guidance on alternatives and exclusions, far beyond a vague 'use when needed'.

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