literatize

name	literatize
description	On-demand code annotator for LLM context preservation. Adds section-level comments capturing intent, rationale, and gotchas. Use when "literatize", "add literate comments", "annotate this file", "add section comments".
argument-hint	<file-path> [--dry-run] [--context <path>]
allowed-tools	["Read","Edit","Write","Glob","Grep"]
model	sonnet
context	main
user-invocable	true

Literatize — Code Annotation for LLM Context

Add section-level comments to code files that capture intent, rationale, and gotchas — optimized for LLM re-entry across ephemeral sessions.

Not literate programming (Knuth). Documentation embedded in code, following code structure. See references/guide.md for theory and examples.

Steps

1. Parse arguments: file path (required), --dry-run (show diff only), --context <path> (design docs, ADRs)
2. Read target file and any --context files
3. Identify logical sections: imports, config, classes, functions, routes, main, etc.
4. Generate file header block:
   • Purpose (1 line)
   • Architecture sketch (1 line — data/control flow)
   • Key invariants (1 line)
5. For each section, add a comment block (2-6 lines):
   • What: what this section does (1 line)
   • Why: design rationale (1-2 lines) — only if non-obvious
   • Gotchas: pitfalls, key decisions — only if relevant
   • Flow: data/control flow — only for routes/pipelines
6. Use native comment syntax (# Python, // JS/TS, -- SQL, etc.)
7. Section dividers: # ── N. Section Name (no trailing padding, adjust prefix to language)
8. Write file (or show proposed comments if --dry-run)

Rules

Do	Don't
Explain intent and decisions	Describe what code literally does
Assume cold-start reader	Assume prior context
Keep blocks 2-6 lines	Write essays
Reference external docs when they exist	Duplicate info from variable/function names
Preserve ALL existing code	Reformat, refactor, add docstrings/types

Comment Style

# ════════════════════════════════════════
# Purpose: [what this file does]
# Architecture: [data/control flow sketch]
# Invariants: [key guarantees]
# ════════════════════════════════════════

# ── N. Section Name
# [What + Why + Gotchas as relevant, 2-6 lines]

Dual Audience

• LLMs (primary): Capture decisions not in code (why X not Y, constraints, framework gotchas). Enable re-entry without external docs.
• Humans (secondary): Section headers as navigation, architecture sketch, gotcha prevention.