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@openhint/transpiler

v1.0.10

Published

The HINT engine — compiles markdown-native .hint specifications into deterministic, high-density prompts for AI agents.

Readme

@openhint/transpiler

The engine behind HINT — a markdown-native specification language for professionals who want to work with AI in a structured, strict way and get predictable results. It compiles human intent into deterministic, high-density prompts for AI agents; software code and legal documents are two of its vocabularies.

This package is the library; the command-line interface lives in @openhint/cli.

What it does

The transpiler has no built-in keyword vocabulary. It implements the structural pipeline —

paths ──► findHints ──► parseHints ──► compileHints ──► prompt string
                                            ▲
                            loadHintbooks ──┘

— and renders every block through instruction templates supplied by hintbooks, installable keyword vocabularies such as @openhint/hintbook-software-engineer.

Usage

import { compileHints, findProjectRoot, loadConfig, loadHintbooks, parseHints } from '@openhint/transpiler';

const projectRootPath = await findProjectRoot(process.cwd());
const config = await loadConfig(projectRootPath);

const hintbooks = await loadHintbooks(projectRootPath, config?.books ?? []);
const hints = await parseHints(projectRootPath, ['src/billing/invoice.ts'], false);

const prompt = await compileHints(hints, hintbooks, 'compile');

API

Pipeline

| Export | Purpose | | -------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | findHints(projectRootPath, paths) | Resolve paths (companions, folders, globs) into a HintFileData tree rooted at the project's _.hint, synthesizing missing folder hints. | | parseHints(projectRootPath, paths, dryRun) | Read and parse the tree into typed HintData blocks: heading keyword/name/{#id}, markdown bodies, nesting by heading depth, @include expansion. dryRun turns missing hint files into errors instead of skips. | | compileHints(hints, hintbooks, mode) | Render blocks through hintbook keywords (mode lookup with fallback to compile, synonym matching, exclude handling, {id} / {name} / {body} / {children} interpolation) and wrap the result in the mode's __header__ / __footer__. |

Hintbooks

| Export | Purpose | | --------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- | | resolveHintbookPaths(projectRootPath, book) | Resolve a book reference (file:// path, npm:// package, or bare path) to every contained folder holding a hintbook.json. | | loadHintbook(path) | Load one instruction folder into HintbookData — keywords keyed by file name, modes by .{mode}.md suffix, metadata from front matter. | | loadHintbooks(projectRootPath, books) | Resolve and load a books list; throws on entries that resolve to nothing. |

Project configuration

| Export | Purpose | | ---------------------------------------- | ---------------------------------------------------------------------------------------------- | | findProjectRoot(startPath) | Walk up to the nearest hint.yml / hint.yaml. | | findConfig, loadConfig, saveConfig | Locate, read, and write the project's ConfigData (name, description, books, ignore). | | CONFIG_INSTRUCTION | The AGENTS.md / CLAUDE.md workflow instruction block emitted by hint instruct. |

Constants for the running vocabulary (RUNNING_FILE, RUNNING_FOLDER, RUNNING_HEADER, RUNNING_FOOTER, RUNNING_SYSTEM), placeholders (PLACEHOLDER_ID, PLACEHOLDER_NAME, PLACEHOLDER_BODY, PLACEHOLDER_CHILDREN), book prefixes (URL_FILE_PREFIX, URL_NPM_PREFIX), and the default mode (INSTRUCTION_MODE_DEFAULT) are exported alongside the types HintData, HintFileData, HintbookData, InstructionData, ModeData, and ConfigData.

Documentation

License

MIT