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Magnus Hedemark
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Each README is written for a human audience, explaining: - What the skill does (not what format it follows) - What benefit the user gets from installing it - Quick setup and usage patterns - When to load/trigger the skill - What scripts, references, and templates it ships data-scientist already had a README — left unchanged. 48 READMEs added across all skill and bundle directories.
30 lines
1.4 KiB
Markdown
30 lines
1.4 KiB
Markdown
# CLI Builder — Design Agent-Friendly CLI Tools
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A comprehensive design guide and scaffold for building CLI tools that **AI agents can actually use**. 10 universal design patterns grounded in real failures from building 15+ agent-facing CLIs.
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## Why Install This Skill
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When your agent loads this skill, it can **design, build, and refactor CLI tools** that agents can discover and use without human help. That means:
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- **Every `--help` output becomes a contract** the agent parses to understand your tool
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- **Every command supports `--json`** for machine-readable output the agent consumes
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- **Every operation is idempotent** — `--dry-run` previews changes before they happen
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- **Authentication is lazy** — help and dry-run work without credentials
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- **Errors are structured** — different exit codes for different failure modes
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## What You Get
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| Directory | Purpose |
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|-----------|---------|
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| `SKILL.md` | 500+ line reference: 10 design patterns, 3-phase build workflow, agent-compatibility test suite |
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| `templates/` | Python API client scaffold and bash CLI scaffold |
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| `references/` | Agent-compatibility test suite, Python API client pattern |
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## Triggers
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Load this when building a new CLI tool, refactoring an existing tool that causes agent friction, or debugging why your agent keeps failing to use a CLI properly.
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## Requirements
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Bash, Python 3.8+, jq, and a standard Unix CLI environment.
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