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Teachable: Send email

teachable_send_email

Teachable: Send an email from your school to chosen users, the students of a course or all users, as on the Emails, Compose page. Sends a custom email from your school. Students who opted out of instructional and promotional emails in their profile do not receive it. To reach part of a course, take the emails from list_students and pass them in user_emails. By default you confirm each call; you can switch that off for this tool. Reaches other people: confirm with the user before each call. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesusers, course or all_users.
subjectYesEmail subject.
course_idNoRecipients when to is course.
user_emailsNoRecipients when to is users.
body_markdownYesEmail body.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With annotations only covering the safety profile (readOnly=false, destructive=false, openWorld=true), the description adds real context: opted-out students are excluded, confirmation is required by default but can be disabled for this tool, and a Cotlet API key with app access is needed. It stops short of describing delivery failures or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the purpose, then layers recipient logic, opt-out caveat, and confirmation requirement. Reasonably dense and every sentence carries information; the confirmation sentences are slightly repetitive but not padded.

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?

For a 5-parameter, no-output-schema send tool, the description covers recipients, opt-out behavior, prerequisites, and per-call confirmation. It leaves the success/failure return contract unstated, but with no output schema the caller's most pressing questions are answered.

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% (baseline 3), and the description goes further by linking `to=users` to `user_emails` sourced from list_students and clarifying the three recipient modes, adding semantic meaning beyond the schema's terse field descriptions.

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?

States a specific verb (send an email) and resource (your school / students / users) and enumerates the three recipient modes that map to the `to` enum, so an agent can tell it apart from siblings like `teachable_reply_to_comment` or `teachable_moderate_comment`. The 'as on the Emails, Compose page' anchor makes the capability unambiguous.

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?

It explains how to reach a subset of a course ('take the emails from list_students and pass them in user_emails'), naming the sibling to source the list from, and states the confirmation conditions before each call. It doesn't explicitly say when NOT to use this tool versus other messaging tools, but the recipient-mode guidance is concrete.

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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