This prompt instructs the AI to act as an experienced business communication specialist and generate a ready-to-send professional email template based on user-supplied details such as email type, recipient, purpose, key points, tone, and context. The result is a clearly structured, concise, and persuasive email—including a short subject line, appropriate greeting, organized body (with bullets when helpful), a specific call-to-action, and a professional closing—formatted for immediate use with...
Scanned 9/12/2026
Install to Claude Code
npx -y skills add BetterPromptme/skills --skill email-architect --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: email-architect
description: This prompt instructs the AI to act as an experienced business communication specialist and generate a ready-to-send professional email template based on user-supplied details such as email type, recipient, purpose, key points, tone, and context. The result is a clearly structured, concise, and persuasive email—including a short subject line, appropriate greeting, organized body (with bullets when helpful), a specific call-to-action, and a professional closing—formatted for immediate use with customizable placeholders and checked against clarity, tone consistency, and completeness standards.
compatibility: Requires betterprompt >= 0.1.3
metadata:
openclaw:
homepage: https://github.com/BetterPromptme/skills
emoji: 🧩
requires:
anyBins:
- betterprompt
- bp
os:
- linux
- darwin
install:
- id: node
kind: node
package: betterprompt
bins: [betterprompt, bp]
label: Install BetterPrompt CLI (node)
---
## What it does
This prompt instructs the AI to act as an experienced business communication specialist and generate a ready-to-send professional email template based on user-supplied details such as email type, recipient, purpose, key points, tone, and context. The result is a clearly structured, concise, and persuasive email—including a short subject line, appropriate greeting, organized body (with bullets when helpful), a specific call-to-action, and a professional closing—formatted for immediate use with customizable placeholders and checked against clarity, tone consistency, and completeness standards.
> For more installation instructions go to https://raw.githubusercontent.com/BetterPromptme/skills/refs/heads/main/betterprompt/SKILL.md to check out this skill.
## Inputs
### textInputs
Pass each text input using `--input <key>=<value>` flags.
| Variable key | Required? | Description | Defaults |
| --- | ---: | --- | --- |
| `tone` | Optional | What communication style fits best? | `Professional, Friendly, Formal, Urgent, Persuasive, etc.` |
| `purpose` | Required | What’s the main goal or outcome you want from this email? | (none) |
| `recipient` | Optional | Who are you writing to | `Client, Colleague, Manager, Partner, Customer` |
| `email_type` | Optional | What kind of email are you writing | `Introduction, Follow-up, Request, Apology, Announcement` |
| `key_points` | Required | List the main details or information you want to include (2–4 short bullet points). | (none) |
| `additional_context` | Required | Any background information, previous interactions, company or project details that help clarify the situation. | (none) |
### Models and options
This skill's modality is: **`text`**.
To discover which `model` values you can use (and which `options` keys/values are valid for each model), run:
```bash
betterprompt resources --models-only --json
```
Then filter the returned JSON array to entries where `modality` is `"text"`.
## How to run
### Step 1: Collect inputs
First, run `betterprompt resources --models-only --json` and filter to `modality: "text"` to discover valid models and available options:
```bash
betterprompt resources --models-only --json
```
Use only the models and option values that appear in the filtered results.
Then collect all inputs from the human:
- Required text inputs:
- `purpose`
- `key_points`
- `additional_context`
- Optional text inputs (use defaults if not provided by the human):
- `tone` (default: `Professional, Friendly, Formal, Urgent, Persuasive, etc.`)
- `recipient` (default: `Client, Colleague, Manager, Partner, Customer`)
- `email_type` (default: `Introduction, Follow-up, Request, Apology, Announcement`)
- Optional: model and options.
- Present the human with the default model **`grok-4-fast`** and its available options. Look up `grok-4-fast` in the `betterprompt resources` output (filtered to modality `"text"`) and show its `availableOptions` as: `key: val1, val2 (default), val3 | key2: ...`. Mark a value `(default)` if it matches these defaults: `{"reasoningEffort":"low"}`.
- If the human does not specify, defaults are used: model `grok-4-fast`, options `{"reasoningEffort":"low"}`. Other models from the resources call are also available.
If any required text input is missing, **ask the human for what's missing**. Do not assume or fabricate values.
### Step 2: Run via BetterPrompt CLI
Use the frontmatter's `name` as the positional argument (for this skill, use `email-architect`).
Command form:
```bash
betterprompt generate email-architect \
[--input <key>=<value>] \
[--model <model>] \
[--options <options JSON>] \
[--json]
```
Notes:
- Pass each text input as a separate `--input <key>=<value>` flag.
- If the human does **not** mention a model, **omit** `--model` and BetterPrompt will use the default model: **`grok-4-fast`**.
- If the human does **not** mention options, **omit** `--options` and BetterPrompt will use the default options: **`{"reasoningEffort":"low"}`**.
- If the run times out, the response will include a `runId` you can use to fetch the result later.
Example (using defaults shown above):
```bash
betterprompt generate email-architect \
--input 'tone=Professional, Friendly, Formal, Urgent, Persuasive, etc.' \
--input purpose=<value> \
--input 'recipient=Client, Colleague, Manager, Partner, Customer' \
--input 'email_type=Introduction, Follow-up, Request, Apology, Announcement' \
--input key_points=<value> \
--input additional_context=<value> \
--model grok-4-fast \
--options '{"reasoningEffort":"low"}'
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