Extract skill overview source helpers
This commit is contained in:
yaojingang
+10
-145
@@ -1,35 +1,25 @@
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#!/usr/bin/env python3
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import json
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import re
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from datetime import date
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from pathlib import Path
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from skill_ir_paths import find_skill_ir
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from skill_report_metrics import calculate_scorecard
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from skill_report_sources import (
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extract_title,
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load_json,
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load_yaml,
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package_entries,
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parse_frontmatter,
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parse_sections,
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summarize_logic,
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summarize_usage,
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)
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from skill_report_world_class import world_class_readiness, world_class_roadmap_item
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try:
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import yaml
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except ImportError: # pragma: no cover
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yaml = None
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SCRIPT_INTERFACE = "internal-module"
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SCRIPT_INTERFACE_REASON = "Imported by render_skill_overview.py to build the v2 report data model."
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KNOWN_ENTRIES = [
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("SKILL.md", "Skill entrypoint"),
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("README.md", "Human-readable usage guide"),
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("agents/interface.yaml", "Neutral interface metadata"),
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("manifest.json", "Lifecycle and portability metadata"),
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("references", "Extended guidance and reusable notes"),
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("scripts", "Deterministic helpers or local tooling"),
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("evals", "Trigger and quality checks"),
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("reports", "Generated evidence and overview artifacts"),
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]
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IGNORED_PACKAGE_PARTS = {".git", "__pycache__", ".venv", "venv", "node_modules", "dist"}
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REPORT_NAV_V2 = [
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{"label": "技能概述", "label_en": "Overview", "href": "overview"},
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{"label": "总览指标", "label_en": "Metrics", "href": "metrics"},
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@@ -43,131 +33,6 @@ REPORT_NAV_V2 = [
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]
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def parse_frontmatter(text: str) -> tuple[dict, str]:
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lines = text.splitlines()
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if not lines or lines[0].strip() != "---":
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return {}, text
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try:
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end_index = lines[1:].index("---") + 1
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except ValueError:
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return {}, text
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frontmatter_text = "\n".join(lines[1:end_index])
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body = "\n".join(lines[end_index + 1 :]).lstrip()
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if yaml is not None:
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data = yaml.safe_load(frontmatter_text) or {}
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return data if isinstance(data, dict) else {}, body
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data = {}
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for line in frontmatter_text.splitlines():
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if ":" not in line:
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continue
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key, value = line.split(":", 1)
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data[key.strip()] = value.strip().strip('"')
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return data, body
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def load_yaml(path: Path) -> dict:
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if not path.exists():
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return {}
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text = path.read_text(encoding="utf-8")
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if yaml is not None:
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payload = yaml.safe_load(text) or {}
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return payload if isinstance(payload, dict) else {}
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return {}
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def load_json(path: Path) -> dict:
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if not path.exists():
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return {}
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try:
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payload = json.loads(path.read_text(encoding="utf-8"))
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except json.JSONDecodeError:
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return {}
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return payload if isinstance(payload, dict) else {}
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def extract_title(body: str, fallback: str) -> str:
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for line in body.splitlines():
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if line.startswith("# "):
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return line[2:].strip()
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return fallback
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def parse_sections(body: str) -> dict[str, str]:
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sections: dict[str, list[str]] = {}
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current = "_preamble"
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sections[current] = []
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for line in body.splitlines():
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if line.startswith("## "):
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current = line[3:].strip()
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sections[current] = []
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continue
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sections[current].append(line)
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return {name: "\n".join(lines).strip() for name, lines in sections.items()}
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def extract_list_items(text: str) -> list[str]:
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items = []
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for line in text.splitlines():
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stripped = line.strip()
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if not stripped:
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continue
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ordered = re.match(r"^\d+\.\s+(.*)$", stripped)
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bullet = re.match(r"^[-*]\s+(.*)$", stripped)
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match = ordered or bullet
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if match:
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items.append(match.group(1).strip())
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return items
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def summarize_logic(sections: dict[str, str]) -> list[str]:
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for key in ("Compact Workflow", "Workflow", "How It Works", "Logic", "Quick Start"):
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if key in sections:
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items = extract_list_items(sections[key])
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if items:
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return items[:5]
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return extract_list_items(sections.get("_preamble", ""))[:5] or [
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"Understand the request",
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"Execute the main task",
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"Validate the result",
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]
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def summarize_usage(sections: dict[str, str], default_prompt: str, description: str) -> list[str]:
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for key in ("How To Use", "Quick Start", "Usage", "Runbook"):
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if key in sections:
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items = extract_list_items(sections[key])
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if items:
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return items[:5]
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usage = []
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if default_prompt:
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usage.append(default_prompt)
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usage.append(f"Use this skill when the request matches: {description}")
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return usage[:5]
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def package_entries(skill_dir: Path) -> list[dict]:
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items = []
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for rel_path, label in KNOWN_ENTRIES:
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target = skill_dir / rel_path
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if target.exists():
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kind = "folder" if target.is_dir() else "file"
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if target.is_dir():
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count = len(
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[
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path
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for path in target.rglob("*")
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if path.is_file()
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and not path.is_symlink()
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and not any(part in IGNORED_PACKAGE_PARTS for part in path.relative_to(target).parts)
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and path.suffix not in {".pyc", ".pyo"}
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]
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)
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else:
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count = 1
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items.append({"path": rel_path, "label": label, "kind": kind, "file_count": count})
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return items
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def context_payload(intent: dict) -> dict:
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context = intent.get("context", {}) if isinstance(intent, dict) else {}
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return context if isinstance(context, dict) else {}
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@@ -0,0 +1,154 @@
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#!/usr/bin/env python3
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"""Source loading and package scanning helpers for skill overview reports."""
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import json
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import re
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from pathlib import Path
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try:
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import yaml
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except ImportError: # pragma: no cover
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yaml = None
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SCRIPT_INTERFACE = "internal-module"
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SCRIPT_INTERFACE_REASON = "Imported by skill_report_model.py to load source files and scan overview package assets."
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KNOWN_ENTRIES = [
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("SKILL.md", "Skill entrypoint"),
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("README.md", "Human-readable usage guide"),
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("agents/interface.yaml", "Neutral interface metadata"),
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("manifest.json", "Lifecycle and portability metadata"),
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("references", "Extended guidance and reusable notes"),
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("scripts", "Deterministic helpers or local tooling"),
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("evals", "Trigger and quality checks"),
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("reports", "Generated evidence and overview artifacts"),
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]
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IGNORED_PACKAGE_PARTS = {".git", "__pycache__", ".venv", "venv", "node_modules", "dist"}
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def parse_frontmatter(text: str) -> tuple[dict, str]:
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lines = text.splitlines()
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if not lines or lines[0].strip() != "---":
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return {}, text
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try:
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end_index = lines[1:].index("---") + 1
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except ValueError:
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return {}, text
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frontmatter_text = "\n".join(lines[1:end_index])
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body = "\n".join(lines[end_index + 1 :]).lstrip()
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if yaml is not None:
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data = yaml.safe_load(frontmatter_text) or {}
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return data if isinstance(data, dict) else {}, body
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data = {}
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for line in frontmatter_text.splitlines():
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if ":" not in line:
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continue
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key, value = line.split(":", 1)
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data[key.strip()] = value.strip().strip('"')
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return data, body
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def load_yaml(path: Path) -> dict:
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if not path.exists():
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return {}
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text = path.read_text(encoding="utf-8")
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if yaml is not None:
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payload = yaml.safe_load(text) or {}
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return payload if isinstance(payload, dict) else {}
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return {}
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def load_json(path: Path) -> dict:
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if not path.exists():
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return {}
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try:
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payload = json.loads(path.read_text(encoding="utf-8"))
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except json.JSONDecodeError:
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return {}
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return payload if isinstance(payload, dict) else {}
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def extract_title(body: str, fallback: str) -> str:
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for line in body.splitlines():
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if line.startswith("# "):
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return line[2:].strip()
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return fallback
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def parse_sections(body: str) -> dict[str, str]:
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sections: dict[str, list[str]] = {}
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current = "_preamble"
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sections[current] = []
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for line in body.splitlines():
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if line.startswith("## "):
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current = line[3:].strip()
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sections[current] = []
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continue
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sections[current].append(line)
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return {name: "\n".join(lines).strip() for name, lines in sections.items()}
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def extract_list_items(text: str) -> list[str]:
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items = []
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for line in text.splitlines():
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stripped = line.strip()
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if not stripped:
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continue
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ordered = re.match(r"^\d+\.\s+(.*)$", stripped)
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bullet = re.match(r"^[-*]\s+(.*)$", stripped)
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match = ordered or bullet
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if match:
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items.append(match.group(1).strip())
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return items
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def summarize_logic(sections: dict[str, str]) -> list[str]:
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for key in ("Compact Workflow", "Workflow", "How It Works", "Logic", "Quick Start"):
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if key in sections:
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items = extract_list_items(sections[key])
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if items:
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return items[:5]
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return extract_list_items(sections.get("_preamble", ""))[:5] or [
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"Understand the request",
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"Execute the main task",
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"Validate the result",
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]
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def summarize_usage(sections: dict[str, str], default_prompt: str, description: str) -> list[str]:
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for key in ("How To Use", "Quick Start", "Usage", "Runbook"):
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if key in sections:
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items = extract_list_items(sections[key])
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if items:
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return items[:5]
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usage = []
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if default_prompt:
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usage.append(default_prompt)
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usage.append(f"Use this skill when the request matches: {description}")
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return usage[:5]
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def package_entries(skill_dir: Path) -> list[dict]:
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items = []
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for rel_path, label in KNOWN_ENTRIES:
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target = skill_dir / rel_path
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if target.exists():
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kind = "folder" if target.is_dir() else "file"
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if target.is_dir():
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count = len(
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[
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path
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for path in target.rglob("*")
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if path.is_file()
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and not path.is_symlink()
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and not any(part in IGNORED_PACKAGE_PARTS for part in path.relative_to(target).parts)
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and path.suffix not in {".pyc", ".pyo"}
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]
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)
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else:
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count = 1
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items.append({"path": rel_path, "label": label, "kind": kind, "file_count": count})
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return items
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