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README.md

logic-md

A Python SDK for parsing and validating LOGIC.md specifications — declarative reasoning configurations for AI agents.

Status: Alpha — parser and validator only.

Installation

pip install logic-md

Quick Start

from logic_md import parse, validate

# Parse a LOGIC.md file
with open("my-agent.logic.md") as f:
    content = f.read()

result = parse(content)
if result.ok:
    print(f"Parsed spec: {result.data['name']}")
else:
    print(f"Parse errors: {result.errors}")

# Validate the parsed spec
val_result = validate(result.data)
if val_result.ok:
    print("Spec is valid!")
else:
    for error in val_result.errors:
        print(f"Validation error at {error['path']}: {error['message']}")

API

parse(content: str) -> ParseResult

Extracts YAML frontmatter from a LOGIC.md file and returns a ParseResult:

  • ok: bool — True if parsing succeeded
  • data: dict — Parsed YAML frontmatter (if ok=True)
  • content: str — Markdown body after frontmatter
  • errors: list[str] — Error messages (if ok=False)

Example:

result = parse("---\nspec_version: '1.0'\nname: my-agent\n---\n# My Agent")
# result.ok = True
# result.data = {"spec_version": "1.0", "name": "my-agent"}
# result.content = "# My Agent"

validate(spec: dict) -> ValidationResult

Validates a parsed spec against the LOGIC.md JSON Schema and returns a ValidationResult:

  • ok: bool — True if spec is valid
  • data: dict — The validated spec (if ok=True)
  • errors: list[dict] — Validation errors with path, keyword, message (if ok=False)

Example:

result = validate({"spec_version": "1.0", "name": "my-agent"})
# result.ok = True
# result.data = {"spec_version": "1.0", "name": "my-agent"}

LogicSpec

A TypedDict type hint for the parsed/validated spec structure. Use for type hints:

from logic_md import LogicSpec

def process_spec(spec: LogicSpec) -> None:
    print(spec["name"])

Schema

The validator uses the canonical JSON Schema from the logic-md spec repository.

Links