read_docsFetch emailmd documentation from emailmd.dev. Call with no arguments for the index of all pages; pass page to read one (e.g. 'buttons', 'frontmatter', 'theme', 'directives/hero'). Read the relevant page before using syntax you are not sure about.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Docs page path, e.g. 'buttons' or 'directives/hero'. Omit for the index. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the optional argument behavior and gives examples, but does not mention error handling or return format. For a simple read tool, this is adequate, though not fully exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences that front-load the core purpose and then provide usage examples and guidance. Every sentence contributes value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and no output schema, the description fully covers purpose, usage, parameter semantics, and when to use it. It is complete enough for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a description for the 'page' parameter (pattern, examples, and 'Omit for the index'), so the description adds little beyond that. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Fetch emailmd documentation from emailmd.dev.' It uses a specific verb ('Fetch') and resource ('emailmd documentation'), and the distinction from siblings (lint, render) is evident, as those tools likely operate on the content rather than retrieve documentation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Call with no arguments for the index of all pages; pass page to read one' and 'Read the relevant page before using syntax you are not sure about.' While it lacks explicit alternatives or when-not-to-use instructions, the guidance is sufficient for a simple documentation fetcher.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
Three tools cover the essential operations for an email markdown server: validation, documentation lookup, and rendering. The count is well-scoped and not excessive.
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.