| name | prose |
| description | Author or edit any prose for the Toasty project — documentation, design docs, READMEs, PR descriptions, issue bodies, commit message bodies, or other human-readable text — following project writing conventions |
Writing Toasty Prose
Load this skill whenever writing or editing prose for this project: documentation in docs/, READMEs, design docs, PR descriptions, issue bodies, commit message bodies, or any other human-readable markdown.
Writing Style
- Be fact-focused: State what things are and what they do
- Avoid buzzwords: No "leverage", "synergy", "paradigm", etc.
- Avoid fluff: Every sentence should convey information
- Avoid business jargon: No "stakeholders", "deliverables", "action items"
- Avoid weasel words: No "very", "really", "quite", "somewhat"
- Avoid dramatic terms: No "critical", "crucial", "vital", "essential" unless something will actually break
- Avoid figurative metaphors: Pick the literal word for the thing, not the analogy. "Features light up on PostgreSQL" → "Toasty enables features on PostgreSQL". "Query shape" → "query pattern" or "query form". Other recurring offenders: "under the hood" (just describe what's there), "out of the box" (just say "by default"), "first-class" (say what's actually supported), "magic" (say what the code does). If you can't replace the metaphor with a literal noun or verb without losing meaning, you probably don't know what you mean yet.
- Be direct: Say what you mean without hedging
- Use concrete examples: Show, don't tell
- Use active voice: "The engine executes queries" not "Queries are executed by the engine"
- Use present tense: Describe how the system works now, not how it was designed or how it will work
- Document current behavior only: Omit historical decisions, deprecated approaches, and planned future work
Examples
Bad: "This component is critical for ensuring optimal query performance."
Good: "This component optimizes queries by combining multiple database round-trips into one."
Bad: "The simplification phase leverages various transformations to enhance query efficiency."
Good: "The simplification phase rewrites association traversals into explicit subqueries."
Bad: "Native arrays light up on PostgreSQL for Vec<scalar> fields."
Good: "On PostgreSQL, Vec<scalar> fields use native array columns (text[], int8[], …)."
Bad: "## Query shapes that work"
Good: "## Supported queries"
Document Structure
- Start with what the thing is
- Explain why it exists (what problem it solves)
- Explain what it does
- Show how to use it (if applicable)
- Provide examples