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Core library for the Score portable AI knowledge format

Project description

score-core

Core library for the Score portable AI knowledge format.

Score is a human-readable, LLM-agnostic format for encoding organisational knowledge as portable skill files. score-core provides the schema, parser, serialiser, validator, library validator, Context API models, and Recording models that any Score-compatible tool needs.

Full format specification: score_spec.md Writing skills: WRITING_SKILLS.md

Install

pip install score-core

Quickstart

Validate a skill file

score validate path/to/my-skill.md
score validate path/to/skills/ --strict

Validate programmatically

from score import parse_skill_file, validate_skill

skill = parse_skill_file("path/to/my-skill.md")
payload = {
    "name": skill.name,
    "description": skill.description,
    "version": skill.version,
    "owner": skill.owner,
    "triggers": list(skill.triggers),
    "tags": list(skill.tags),
    "active": skill.active,
    "created": skill.created,
    "updated": skill.updated,
    "body": skill.body,
}

result = validate_skill(payload)
if not result["valid"]:
    for error in result["errors"]:
        print(f"error: {error['field']}{error['message']}")
for warning in result["warnings"]:
    print(f"warning: {warning['field']}{warning['message']}")

Work with the Pydantic model

from score import parse_skill_file_pydantic, validate_skill_file

skill_file = parse_skill_file_pydantic("path/to/my-skill.md")
result = validate_skill_file(skill_file)
print(result)  # ValidationResult(valid=True, errors=[], warnings=[...], ...)

Library validation

from score import validate_library

skills = [...]  # list of full skill dicts
report = validate_library(skills)
print(report["summary"]["overall_health"])  # "good" | "warning" | "critical"

Migrate existing skills to v0.1.1

score migrate path/to/skills/ --to 0.1.1           # dry run
score migrate path/to/skills/ --to 0.1.1 --apply   # write changes

CLI commands

Command Purpose
score validate <path> Validate a single file or directory
score library-check <dir> Full library report (overlaps, coverage)
score governance-init <dir> Report skills missing v0.1.1 governance fields
score verify-recording <file> Verify Recording hash chain integrity
score migrate <dir> --to 0.1.1 Add safe defaults for new spec fields

What's in the package

  • score.schema — Pydantic models (SkillFile, UITheme, ExecutionHints) and field constants
  • score.parser.mdSkill (runtime dataclass) and SkillFile (Pydantic)
  • score.serialiserSkill.md with YAML frontmatter
  • score.validator — three-tier validation (errors, warnings, hints)
  • score.library_validator — cross-skill checks and fix proposal
  • score.context_api — request/response models for the Score Context API
  • score.recording — audit log entry models and hash chain utilities
  • score.cliscore command-line interface

Relationship to Maestro

Maestro is the commercial skill management product built on the Score format. score-core is the shared library that Maestro and any other Score-compatible tool import. Maestro uses score-core internally; it is not a Maestro dependency.

Version

Current: 0.1.0 — supports Score format v0.1.1 with governance metadata fields.

Licence

MIT. See LICENCE.

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