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Lint an email

lint

Check emailmd markdown for deliverability, accessibility, and readability problems without rendering it: missing alt text, http:// links, Gmail's 102KB clip limit, generic link text, spam-trigger phrases, and more. Fix warnings before sending; suggestions are sometimes intentional (e.g. transactional emails without an unsubscribe link).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
markdownYesThe emailmd markdown document, optionally starting with YAML frontmatter.
partialsNoNamed markdown partials spliced in wherever the document says "::: include <name>".

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool does not render, lists specific checks, and adds a useful caveat about false positives. It does not describe the return format (e.g., structure of warnings), but overall behavior is well conveyed.

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?

Two dense sentences with no filler. Front-loaded with clear purpose, then concrete examples, then a practical caveat. Every word earns its place.

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 2 parameters, 100% schema coverage, and no output schema, the description is largely complete. It explains what the tool checks, the non-rendering behavior, and the intentional-suggestion caveat. The only notable gap is the absence of explicit return value structure, but 'warnings' and 'suggestions' imply the nature of the output.

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% for both parameters, so the baseline is 3. The description adds some context about 'emailmd markdown' and YAML frontmatter, but it does not explain the 'partials' parameter, which is covered only by the schema.

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 a specific verb+resource: 'Check emailmd markdown for deliverability, accessibility, and readability problems'. It explicitly differentiates from sibling 'render' by noting it does this 'without rendering it'.

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 gives clear context: use before sending to fix warnings, and notes that some suggestions are intentional (transactional emails). However, it does not explicitly mention alternatives like 'render' for previewing, missing an explicit when-not-to-use.

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

A4.2/5.0
Disambiguation5/5

Each tool serves a distinct purpose: lint checks markdown issues, read_docs fetches documentation, and render produces HTML. There is no functional overlap, so an agent can easily select the correct tool.

Naming Consistency4/5

All tool names are verbs (lint, read_docs, render), but read_docs uses an underscore while the others are single words. This minor inconsistency is still clear and predictable.

Tool Count5/5

Three tools cover the essential operations for an email markdown server: validation, documentation lookup, and rendering. The count is well-scoped and not excessive.

Completeness5/5

The tool surface covers inspection, learning, and rendering, which are the core interactions needed. There are no obvious gaps for the domain of email markdown processing.