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imguno-playbook

Reusable AI engineering skills and playbooks for production use.

Skills in this repo are ready to plug into AI-assisted workflows (e.g. Cursor, custom agents). Each skill is a self-contained set of instructions, templates, and references—scoped by responsibility and designed to grow with your systems.


What’s in this repo

  • Skills — Step-by-step playbooks for specific engineering tasks (e.g. building a SQL inventory from code, documenting APIs, analyzing performance). Each skill lives under skills/<skill-name>/ with a SKILL.md, optional templates/, and references/.
  • Playbooks — Structured workflows that combine clarity, traceability, and safety so they can be used in real environments.

Use them as-is or adapt them to your stack and conventions.


Principles

Skills here are:

  • Scoped — Clear boundaries and a single primary deliverable per skill.
  • Versioned — Changes are tracked; history and compatibility matter.
  • Structured — Consistent layout (SKILL.md, templates, references) so tools and humans can navigate them.
  • Production-minded — No destructive defaults; optional steps and follow-ups are explicit.
  • Extensible — New skills can be added without tying the repo to one domain (SQL, APIs, docs, etc.).

Skills

  • Sql Inventory From Code — Collects and maintains a complete CSV-based SQL query inventory (SSOT) by extracting all SQL statements from a service application's source code. This skill's only deliverable is the inventory CSV. Use when extracting SQL from application source code, building a query inventory from the codebase, or preparing for SQL tuning from code.

Additional skills (e.g. API documentation, performance analysis, system docs) will be added over time.


Layout

skills/
└── <skill-name>/
    ├── SKILL.md          # Main instructions and scope
    ├── templates/        # Output templates (e.g. CSV, markdown)
    └── references/       # Optional reference docs

Contributing

When adding or changing skills, keep scope and deliverable clear, document assumptions, and avoid destructive or environment-specific defaults so the playbook stays reusable across teams and repos.

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