/do

> The agent's primary skill. Customize this to match your agent's purpose.

170 stars

Best use case

/do is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

> The agent's primary skill. Customize this to match your agent's purpose.

Teams using /do should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/do/SKILL.md --create-dirs "https://raw.githubusercontent.com/Miosa-osa/canopy/main/templates/micro/skills/do/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/do/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How /do Compares

Feature / Agent/doStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

> The agent's primary skill. Customize this to match your agent's purpose.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# /do

> The agent's primary skill. Customize this to match your agent's purpose.

## Usage

```
/do <input> [--format <format>] [--depth <brief|detailed>]
```

## What It Does

Executes the agent's primary task. Takes user input, processes it according to the
agent's domain expertise, and produces structured output.

Replace this description with your agent's specific capability:
- For a code reviewer: analyzes code and produces review feedback
- For an email responder: drafts email responses matching tone and context
- For a meeting summarizer: extracts action items and decisions from transcripts

## Implementation

1. **Parse input** — Extract the core request and any parameters.
2. **Validate** — Confirm the input is within scope and sufficient.
3. **Process** — Apply domain expertise to produce the output.
4. **Format** — Structure output using the deliverable template.
5. **Deliver** — Return the formatted result.

## Parameters

| Param | Default | Options | Description |
|-------|---------|---------|-------------|
| `--format` | `markdown` | `markdown`, `json`, `text` | Output format |
| `--depth` | `brief` | `brief`, `detailed` | Level of detail |

## Examples

```bash
# Basic usage
/do "Review this function for bugs"

# Detailed output
/do "Summarize this meeting transcript" --depth detailed

# JSON output for programmatic use
/do "Extract entities from this text" --format json
```

## Output Template

```markdown
## Result

### Summary
[Brief answer to the request]

### Details
[Structured breakdown — customize per domain]

### Confidence
[High | Medium | Low] — [reason if not High]
```