stream-coding
CheckedDocumentation-first development methodology. The goal is AI-ready documentation - when docs are clear enough, code generation becomes automatic. Triggers on "Build", "Create", "Implement", "Document",
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What we know about this skill
Publisher
frmoretto
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Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned frmoretto/stream-coding at 42a7cb5cee.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 42a7cb5cee
- Manifest
- skills/stream-coding/SKILL.md
- Scanned
- 3 files, 2,311 lines
- Copies in repo
- 3 — all of them scanned
About this skill
What it does
Stream Coding facilitates a documentation-first software development approach. It aims to generate code automatically based on comprehensive and well-defined documentation. This methodology prioritizes creating clear and detailed documentation, which then serves as the blueprint for AI-powered code generation.
When to use it
- New Project Initialization: Ideal for starting new projects where a strong foundation of documentation is desired from the outset.
- Refactoring Legacy Code: Use to rebuild or modernize existing systems by first documenting their current functionality and then generating updated code.
- Automated Feature Implementation: When implementing new features, prioritize detailed documentation before attempting automated code generation.
- Standardizing Development Practices: Stream Coding can help enforce consistent coding standards through the creation of reusable documentation templates.
Key capabilities
- Documentation-first development
- Automatic code generation from documentation
- Triggers on "Build", "Create", "Implement", and "Document" actions.
- AI-ready documentation output
Example prompts
- “Generate code for a function that calculates the factorial of a given number, based on this documentation: [paste documentation here].”
- “Implement the ‘User Authentication’ feature as described in the attached document.”
- “Build a class representing a 'Product' with attributes and methods detailed in the following specification: [paste documentation here]."
Tips & gotchas
The quality of the generated code is directly dependent on the clarity and completeness of the provided documentation. Ensure your documentation adheres to a consistent structure and includes all necessary details before attempting code generation.