refactor(ux): consolidate BMAD skills, update design system, and clean up Prisma generated client
This commit is contained in:
Sepehr Ramezani
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#!/usr/bin/env python3
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"""Deterministic pre-pass for sanctum architecture scanner.
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Extracts structural metadata from a memory agent's sanctum architecture
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that the LLM scanner can use instead of reading all files itself. Covers:
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- SKILL.md content line count (non-blank, non-frontmatter)
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- Template file inventory (which of the 6 standard templates exist)
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- CREED template section inventory
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- BOND template section inventory
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- Capability reference frontmatter fields
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- Init script parameter extraction (SKILL_NAME, TEMPLATE_FILES, EVOLVABLE)
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- First-breath.md section inventory
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- PULSE template presence and sections
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Only runs for memory agents (agents with assets/ containing template files).
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"""
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# /// script
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# requires-python = ">=3.9"
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# dependencies = []
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# ///
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from __future__ import annotations
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import argparse
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import json
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import re
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import sys
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from datetime import datetime, timezone
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from pathlib import Path
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STANDARD_TEMPLATES = [
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"INDEX-template.md",
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"PERSONA-template.md",
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"CREED-template.md",
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"BOND-template.md",
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"MEMORY-template.md",
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"CAPABILITIES-template.md",
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]
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OPTIONAL_TEMPLATES = [
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"PULSE-template.md",
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]
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CREED_REQUIRED_SECTIONS = [
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"The Sacred Truth",
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"Mission",
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"Core Values",
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"Standing Orders",
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"Philosophy",
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"Boundaries",
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"Anti-Patterns",
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"Dominion",
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]
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FIRST_BREATH_CALIBRATION_SECTIONS = [
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"Save As You Go",
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"Pacing",
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"Chase What Catches",
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"Absorb Their Voice",
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"Show Your Work",
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"Hear the Silence",
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"The Territories",
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"Wrapping Up",
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]
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FIRST_BREATH_CONFIG_SECTIONS = [
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"Save As You Go",
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"Discovery",
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"Urgency",
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"Wrapping Up",
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]
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def count_content_lines(file_path: Path) -> int:
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"""Count non-blank, non-frontmatter lines in a markdown file."""
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content = file_path.read_text()
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# Strip frontmatter
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stripped = re.sub(r"^---\s*\n.*?\n---\s*\n", "", content, count=1, flags=re.DOTALL)
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lines = [line for line in stripped.split("\n") if line.strip()]
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return len(lines)
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def extract_h2_h3_sections(file_path: Path) -> list[str]:
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"""Extract H2 and H3 headings from a markdown file."""
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sections = []
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if not file_path.exists():
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return sections
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for line in file_path.read_text().split("\n"):
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match = re.match(r"^#{2,3}\s+(.+)", line)
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if match:
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sections.append(match.group(1).strip())
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return sections
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def parse_frontmatter(file_path: Path) -> dict:
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"""Extract YAML frontmatter from a markdown file."""
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meta = {}
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content = file_path.read_text()
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match = re.match(r"^---\s*\n(.*?)\n---", content, re.DOTALL)
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if not match:
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return meta
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for line in match.group(1).strip().split("\n"):
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if ":" in line:
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key, _, value = line.partition(":")
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meta[key.strip()] = value.strip().strip("'\"")
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return meta
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def extract_init_script_params(script_path: Path) -> dict:
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"""Extract agent-specific configuration from init-sanctum.py."""
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params = {
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"exists": script_path.exists(),
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"skill_name": None,
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"template_files": [],
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"skill_only_files": [],
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"evolvable": None,
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}
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if not script_path.exists():
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return params
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content = script_path.read_text()
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# SKILL_NAME
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match = re.search(r'SKILL_NAME\s*=\s*["\']([^"\']+)["\']', content)
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if match:
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params["skill_name"] = match.group(1)
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# TEMPLATE_FILES
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tmpl_match = re.search(
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r"TEMPLATE_FILES\s*=\s*\[(.*?)\]", content, re.DOTALL
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)
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if tmpl_match:
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params["template_files"] = re.findall(r'["\']([^"\']+)["\']', tmpl_match.group(1))
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# SKILL_ONLY_FILES
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only_match = re.search(
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r"SKILL_ONLY_FILES\s*=\s*\{(.*?)\}", content, re.DOTALL
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)
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if only_match:
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params["skill_only_files"] = re.findall(r'["\']([^"\']+)["\']', only_match.group(1))
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# EVOLVABLE
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ev_match = re.search(r"EVOLVABLE\s*=\s*(True|False)", content)
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if ev_match:
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params["evolvable"] = ev_match.group(1) == "True"
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return params
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def check_section_present(sections: list[str], keyword: str) -> bool:
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"""Check if any section heading contains the keyword (case-insensitive)."""
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keyword_lower = keyword.lower()
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return any(keyword_lower in s.lower() for s in sections)
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def main():
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parser = argparse.ArgumentParser(
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description="Pre-pass for sanctum architecture scanner"
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)
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parser.add_argument("skill_path", help="Path to the agent skill directory")
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parser.add_argument(
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"-o", "--output", help="Output JSON file path (default: stdout)"
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)
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args = parser.parse_args()
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skill_path = Path(args.skill_path).resolve()
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if not skill_path.is_dir():
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print(f"Error: {skill_path} is not a directory", file=sys.stderr)
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sys.exit(2)
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assets_dir = skill_path / "assets"
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references_dir = skill_path / "references"
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scripts_dir = skill_path / "scripts"
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skill_md = skill_path / "SKILL.md"
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# Check if this is a memory agent (has template files in assets/)
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is_memory_agent = assets_dir.exists() and any(
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f.name.endswith("-template.md") for f in assets_dir.iterdir() if f.is_file()
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)
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if not is_memory_agent:
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result = {
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"timestamp": datetime.now(timezone.utc).isoformat(),
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"skill_path": str(skill_path),
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"is_memory_agent": False,
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"message": "Not a memory agent — no sanctum templates found in assets/",
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}
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output_json(result, args.output)
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return
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# SKILL.md analysis
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skill_analysis = {
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"exists": skill_md.exists(),
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"content_lines": count_content_lines(skill_md) if skill_md.exists() else 0,
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"sections": extract_h2_h3_sections(skill_md) if skill_md.exists() else [],
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}
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# Template inventory
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template_inventory = {}
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for tmpl in STANDARD_TEMPLATES:
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tmpl_path = assets_dir / tmpl
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template_inventory[tmpl] = {
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"exists": tmpl_path.exists(),
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"sections": extract_h2_h3_sections(tmpl_path) if tmpl_path.exists() else [],
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"content_lines": count_content_lines(tmpl_path) if tmpl_path.exists() else 0,
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}
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for tmpl in OPTIONAL_TEMPLATES:
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tmpl_path = assets_dir / tmpl
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template_inventory[tmpl] = {
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"exists": tmpl_path.exists(),
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"optional": True,
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"sections": extract_h2_h3_sections(tmpl_path) if tmpl_path.exists() else [],
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"content_lines": count_content_lines(tmpl_path) if tmpl_path.exists() else 0,
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}
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# CREED section check
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creed_path = assets_dir / "CREED-template.md"
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creed_sections = extract_h2_h3_sections(creed_path) if creed_path.exists() else []
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creed_check = {}
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for section in CREED_REQUIRED_SECTIONS:
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creed_check[section] = check_section_present(creed_sections, section)
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# First-breath analysis
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first_breath_path = references_dir / "first-breath.md"
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fb_sections = extract_h2_h3_sections(first_breath_path) if first_breath_path.exists() else []
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# Detect style: calibration has "Absorb Their Voice", configuration has "Discovery"
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is_calibration = check_section_present(fb_sections, "Absorb")
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is_configuration = check_section_present(fb_sections, "Discovery") and not is_calibration
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fb_style = "calibration" if is_calibration else ("configuration" if is_configuration else "unknown")
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expected_sections = (
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FIRST_BREATH_CALIBRATION_SECTIONS if is_calibration else FIRST_BREATH_CONFIG_SECTIONS
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)
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fb_check = {}
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for section in expected_sections:
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fb_check[section] = check_section_present(fb_sections, section)
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first_breath_analysis = {
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"exists": first_breath_path.exists(),
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"style": fb_style,
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"sections": fb_sections,
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"section_checks": fb_check,
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}
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# Capability frontmatter scan
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capabilities = []
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if references_dir.exists():
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for md_file in sorted(references_dir.glob("*.md")):
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if md_file.name == "first-breath.md":
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continue
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meta = parse_frontmatter(md_file)
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if meta:
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cap_info = {
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"file": md_file.name,
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"has_name": "name" in meta,
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"has_code": "code" in meta,
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"has_description": "description" in meta,
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"sections": extract_h2_h3_sections(md_file),
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}
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# Check for memory agent patterns
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cap_info["has_memory_integration"] = check_section_present(
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cap_info["sections"], "Memory Integration"
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)
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cap_info["has_after_session"] = check_section_present(
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cap_info["sections"], "After"
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)
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cap_info["has_success"] = check_section_present(
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cap_info["sections"], "Success"
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)
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capabilities.append(cap_info)
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# Init script analysis
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init_script_path = scripts_dir / "init-sanctum.py"
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init_params = extract_init_script_params(init_script_path)
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# Cross-check: init TEMPLATE_FILES vs actual templates
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actual_templates = [f.name for f in assets_dir.iterdir() if f.name.endswith("-template.md")] if assets_dir.exists() else []
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init_template_match = set(init_params.get("template_files", [])) == set(actual_templates) if init_params["exists"] else None
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# Cross-check: init SKILL_NAME vs folder name
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skill_name_match = init_params.get("skill_name") == skill_path.name if init_params["exists"] else None
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# Findings
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findings = []
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if skill_analysis["content_lines"] > 40:
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findings.append({
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"severity": "high",
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"file": "SKILL.md",
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"message": f"Bootloader has {skill_analysis['content_lines']} content lines (target: ~30, max: 40)",
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})
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for tmpl in STANDARD_TEMPLATES:
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if not template_inventory[tmpl]["exists"]:
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findings.append({
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"severity": "critical",
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"file": f"assets/{tmpl}",
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"message": f"Missing standard template: {tmpl}",
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})
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for section, present in creed_check.items():
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if not present:
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findings.append({
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"severity": "high",
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"file": "assets/CREED-template.md",
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"message": f"Missing required CREED section: {section}",
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})
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if not first_breath_analysis["exists"]:
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findings.append({
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"severity": "critical",
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"file": "references/first-breath.md",
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"message": "Missing first-breath.md",
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})
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else:
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for section, present in first_breath_analysis["section_checks"].items():
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if not present:
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findings.append({
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"severity": "high",
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"file": "references/first-breath.md",
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"message": f"Missing First Breath section: {section}",
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})
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if not init_params["exists"]:
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findings.append({
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"severity": "critical",
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"file": "scripts/init-sanctum.py",
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"message": "Missing init-sanctum.py",
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})
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else:
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if skill_name_match is False:
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findings.append({
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"severity": "critical",
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"file": "scripts/init-sanctum.py",
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"message": f"SKILL_NAME mismatch: script has '{init_params['skill_name']}', folder is '{skill_path.name}'",
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})
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if init_template_match is False:
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findings.append({
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"severity": "high",
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"file": "scripts/init-sanctum.py",
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"message": "TEMPLATE_FILES does not match actual templates in assets/",
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})
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result = {
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"timestamp": datetime.now(timezone.utc).isoformat(),
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"skill_path": str(skill_path),
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"is_memory_agent": True,
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"skill_md": skill_analysis,
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"template_inventory": template_inventory,
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"creed_sections": creed_check,
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"first_breath": first_breath_analysis,
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"capabilities": capabilities,
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"init_script": init_params,
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"cross_checks": {
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"skill_name_match": skill_name_match,
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"template_files_match": init_template_match,
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},
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"findings": findings,
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"finding_count": len(findings),
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"critical_count": sum(1 for f in findings if f["severity"] == "critical"),
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"high_count": sum(1 for f in findings if f["severity"] == "high"),
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}
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output_json(result, args.output)
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def output_json(data: dict, output_path: str | None) -> None:
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"""Write JSON to file or stdout."""
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json_str = json.dumps(data, indent=2)
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if output_path:
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Path(output_path).parent.mkdir(parents=True, exist_ok=True)
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Path(output_path).write_text(json_str + "\n")
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print(f"Wrote: {output_path}", file=sys.stderr)
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else:
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print(json_str)
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if __name__ == "__main__":
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main()
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