Files
yao-meta-skill/scripts/context_sizer.py
T
2026-03-31 19:59:29 +08:00

95 lines
2.9 KiB
Python

#!/usr/bin/env python3
import argparse
import json
from pathlib import Path
TEXT_EXTS = {".md", ".txt", ".yaml", ".yml", ".json", ".py", ".sh", ".js", ".ts"}
def estimate_tokens(text: str) -> int:
# Fast heuristic suitable for local gating.
return max(1, len(text) // 4)
def read_text(path: Path) -> str:
try:
return path.read_text(encoding="utf-8")
except UnicodeDecodeError:
return path.read_text(encoding="utf-8", errors="ignore")
def classify(path: Path) -> str:
parts = set(path.parts)
if path.name == "SKILL.md":
return "skill_body"
if "references" in parts:
return "reference"
if "scripts" in parts:
return "script"
if "assets" in parts:
return "asset"
if path.suffix in TEXT_EXTS:
return "other_text"
return "binary_or_other"
def summarize(skill_dir: Path) -> dict:
files = []
total_tokens = 0
initial_tokens = 0
for path in sorted(skill_dir.rglob("*")):
if not path.is_file():
continue
kind = classify(path)
if kind in {"binary_or_other", "asset"} and path.suffix not in TEXT_EXTS:
size = path.stat().st_size
files.append({"path": str(path.relative_to(skill_dir)), "kind": kind, "bytes": size})
continue
text = read_text(path)
tokens = estimate_tokens(text)
record = {
"path": str(path.relative_to(skill_dir)),
"kind": kind,
"chars": len(text),
"estimated_tokens": tokens,
}
files.append(record)
total_tokens += tokens
if kind in {"skill_body", "other_text"}:
initial_tokens += tokens
return {
"skill_dir": str(skill_dir),
"estimated_initial_load_tokens": initial_tokens,
"estimated_total_text_tokens": total_tokens,
"warning": initial_tokens > 2000,
"files": files,
}
def main() -> None:
parser = argparse.ArgumentParser(description="Estimate context size for a skill package.")
parser.add_argument("skill_dir", help="Path to the skill directory")
parser.add_argument("--json", action="store_true", help="Emit machine-readable JSON")
args = parser.parse_args()
report = summarize(Path(args.skill_dir).resolve())
if args.json:
print(json.dumps(report, ensure_ascii=False, indent=2))
return
print(f"Skill: {report['skill_dir']}")
print(f"Estimated initial-load tokens: {report['estimated_initial_load_tokens']}")
print(f"Estimated total text tokens: {report['estimated_total_text_tokens']}")
print(f"Initial-load warning (>2000): {'YES' if report['warning'] else 'NO'}")
print("")
for file in report["files"]:
if "estimated_tokens" in file:
print(f"{file['kind']:12} {file['estimated_tokens']:6}t {file['path']}")
else:
print(f"{file['kind']:12} {file['bytes']:6}b {file['path']}")
if __name__ == "__main__":
main()