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Yaml Pro

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YAML authoring and processing — gotchas, validation, and safe loading — use when writing configs or parsing YAML.

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  • Added September 29, 2026
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A100/100

Scanned September 29, 2026

npx -y skills add aicodedecode/awesome-muse-skills --skill yaml-pro --agent claude-code

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SKILL.md
---
name: yaml-pro
description: YAML authoring and processing — gotchas, validation, and safe loading — use when writing configs or parsing YAML.
category: document-processing
---

## Overview

YAML is the config language of the DevOps world — readable, but full of
footguns (the infamous `no` → `false`, octal surprises, billion-laughs
attacks). This skill covers writing safe, predictable YAML and parsing it
defensively in code.

## When to use

- Authoring configs (CI pipelines, Kubernetes manifests, app settings)
- Designing YAML-based file formats or DSLs
- Parsing YAML safely in applications (avoiding deserialization attacks)
- Templating YAML (anchors, merge keys, and when to avoid them)
- Validating YAML configs with schemas in CI

## Core concepts

**Quote defensively.** YAML's implicit typing converts unquoted `yes/no/on/off`,
`0o17`-style numbers, and version-like strings (`3.10` → `3.1`). Quote strings
that could be misinterpreted — especially versions, identifiers with leading
zeros (`"007"`), and anything resembling a boolean. Explicit is better than
clever.

**Safe loading only.** Never use a full YAML loader on untrusted input — it can
instantiate arbitrary objects (the classic deserialization attack). Always use
the safe loader, which handles only plain scalars, lists, and maps. This is
non-negotiable for any YAML from users or networks.

**Anchors and merge keys: use sparingly.** `&anchor` / `*alias` / `<<: *merge`
reduce duplication in hand-written configs, but they complicate programmatic
processing and confuse newcomers. Fine for small DRY wins; for heavy reuse,
prefer a templating layer or config generation in code.

**Schema-validate configs.** JSON Schema validates YAML too (YAML is a superset
of JSON). Validate CI configs, app settings, and manifests against a schema in
CI — catching a typo'd key at commit time beats debugging a silent misconfig
in production.

**Multi-document files.** `---` separates documents in one stream; some tools
read only the first. Know whether your consumer handles multi-doc files before
relying on them.

## Practical workflow

1. **Start from a known-good example** for the target system; adapt minimally
   rather than writing from memory.
2. **Quote aggressively:** versions, booleans-as-strings, leading-zero numbers,
   and any value where the type matters downstream.
3. **Keep nesting shallow** (3–4 levels max); deep nesting is hard to read and
   easy to mis-indent — refactor into flatter structures or multiple files.
4. **Validate in CI:** schema check + a dry-run/parse of the consuming tool
   (e.g. `kubectl --dry-run`, CI config linter) on every change.
5. **In code, always safe-load;** convert to typed config objects with defaults
   and validation immediately after parsing — don't pass raw dicts around.
6. **Document the config:** a commented example file or schema with
   descriptions is worth more than a wiki page nobody updates.

## Common pitfalls

- **The Norway problem:** `no`/`yes`/`on`/`off` becoming booleans — quote
  country codes and string flags.
- **Tabs for indentation** — forbidden in YAML; use spaces, consistently (2 is
  the convention).
- **Version `3.10` parsed as float `3.1`** — quote versions, always.
- **Merge-key surprises:** `<<: *base` silently overrides in non-obvious order
  with multiple merges; prefer explicit keys for critical settings.
- **Giant YAML files** generated by tools — split into multiple files with
  clear naming; 2000-line YAML is unreviewable.
- **Secrets in YAML committed to git** — configs get committed; secrets don't
  belong in them. Reference secret stores via placeholders resolved at deploy
  time.

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