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by ai.trydock

validate_html

Pre-flight check on html / css / js BEFORE writing via update_html. Returns { ok, errors, warnings, parsed } where parsed has byte counts per field and dropped (true if the sanitizer would strip anything from html). Errors cover cap breaches (html_too_large, css_too_large, js_too_large, total_too_large) and sanitizer rejection (html_sanitize_rejected, html_sanitize_empty). At v2 the sanitizer accepts <script> and <link> — those used to be smells but are now first-class agent markup; isolation lives in the opaque render iframe, not the sanitizer. The smells still stripped: inline on*= attributes, javascript:/data:text/html URIs, <meta http-equiv> tags. NEVER writes anything. Use when iterating on a payload so you don't burn a write on something the surface would reject.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsNoJS to validate (optional).
cssNoCSS to validate (optional).
htmlNoHTML to validate (optional).

TDQS

A4.7/5.0
Behavior5/5

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

Despite having no annotations, the description fully discloses behavior: returns structure, error codes, sanitizer specifics (accepts script/link, strips on* attributes, etc.), and the no-write guarantee. It even explains the v2 change and isolation rationale, providing extensive transparency beyond minimal requirements.

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 detailed but each sentence earns its place. It is logically structured: purpose, return shape, error codes, sanitizer behavior, no-write guarantee, and use case. Information-dense without being bloated.

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?

Given no annotations, no output schema, and the tool's complexity, the description covers all essential aspects: return format, error semantics, sanitizer rules, and intended usage. Completely adequate for an agent to understand and invoke the tool correctly.

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 coverage is 100% with basic descriptions, but the description adds meaning by explaining how the html parameter is validated against sanitizer rules (dropped flag), cap breaches, and error codes. It enhances understanding of parameter purpose beyond the schema's minimal 'HTML to validate (optional)'.

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 performs a pre-flight check on html/css/js before writing via update_html. It uses a specific verb and resource, and the context distinguishes it from sibling validation tools like validate_doc_markdown and validate_formula.

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?

Explicitly says 'Use when iterating on a payload so you don't burn a write on something the surface would reject.' This provides clear when-to-use context, though it doesn't mention alternatives like validate_doc_markdown or validate_formula. The 'NEVER writes anything' statement adds important usage guidance.

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.

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