feat: add skill usage counter to insights page
- Add api/skill_usage.py for .usage.json read/write with atomic updates - Track skill_view (view_count), skill_manage (use_count), skill_patch (patch_count) invocations per SSE stream completion - Add GET /api/skills/usage endpoint returning per-skill usage stats - Render Skill Usage card in Insights panel after LLM Wiki card - Add i18n keys for en, zh, zh-Hant, ja, it locales - Add 17 tests covering read/increment logic, API route, and streaming hook
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112
api/skill_usage.py
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112
api/skill_usage.py
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# ── Skill usage counter (file-based, best-effort) ──
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import json
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import logging
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import os
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import threading
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import time
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from pathlib import Path
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logger = logging.getLogger(__name__)
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_SKILL_TOOL_NAMES = frozenset({"skill_view", "skill_manage", "skill_patch"})
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_USAGE_FILE = ".usage.json"
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def read_skill_usage(skills_dir: Path) -> dict:
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"""Read the current .usage.json.
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Returns the raw nested dict ``{skill_name: {use_count: N, view_count: N, ...}}``
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or an empty dict when the file does not exist or is corrupt.
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"""
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usage_path = skills_dir / _USAGE_FILE
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if not usage_path.exists():
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return {}
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try:
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raw = usage_path.read_text(encoding="utf-8")
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data = json.loads(raw)
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if isinstance(data, dict):
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return data
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logger.debug("Unexpected .usage.json format, resetting: %s", raw[:200])
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return {}
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except (json.JSONDecodeError, OSError) as exc:
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logger.debug("Failed to read .usage.json: %s", exc)
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return {}
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def _ensure_skill_entry(usage: dict, name: str) -> dict:
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"""Return the metadata dict for *name*, creating a default one if missing."""
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entry = usage.get(name)
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if not isinstance(entry, dict):
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entry = {"use_count": 0, "view_count": 0, "patch_count": 0}
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usage[name] = entry
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return entry
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def increment_skill_usage(skills_dir: Path, tool_calls: list[dict]) -> None:
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"""Scan *tool_calls* for skill_view/skill_manage invocations and bump
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the corresponding counters in .usage.json atomically.
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- ``skill_view`` → increments ``view_count``, sets ``last_viewed_at``
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- ``skill_manage`` → increments ``use_count``, sets ``last_used_at``
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This is a best-effort helper — failures are logged at DEBUG level and
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silently swallowed so they never block the calling stream handler.
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"""
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if not tool_calls:
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return
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updates: list[tuple[str, str]] = []
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for tc in tool_calls:
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if not isinstance(tc, dict):
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continue
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tname = tc.get("name") or tc.get("tool_name") or ""
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if tname not in _SKILL_TOOL_NAMES:
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continue
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args = tc.get("args") or tc.get("input") or {}
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if isinstance(args, dict):
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skill_name = args.get("name")
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if skill_name and isinstance(skill_name, str):
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if tname == "skill_view":
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action = "view"
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elif tname == "skill_patch":
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action = "patch"
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else:
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action = "use"
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updates.append((skill_name, action))
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if not updates:
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return
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usage = read_skill_usage(skills_dir)
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now = time.time()
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for name, action in updates:
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entry = _ensure_skill_entry(usage, name)
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if action == "use":
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entry["use_count"] = entry.get("use_count", 0) + 1
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entry["last_used_at"] = now
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elif action == "patch":
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entry["patch_count"] = entry.get("patch_count", 0) + 1
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entry["last_patched_at"] = now
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else:
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entry["view_count"] = entry.get("view_count", 0) + 1
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entry["last_viewed_at"] = now
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usage_path = skills_dir / _USAGE_FILE
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tmp_path = usage_path.with_suffix(
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f".tmp.{os.getpid()}.{threading.current_thread().ident}"
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)
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try:
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tmp_path.write_text(
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json.dumps(usage, ensure_ascii=False, indent=2, sort_keys=True),
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encoding="utf-8",
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)
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tmp_path.replace(usage_path)
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except OSError as exc:
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logger.debug("Failed to atomically write .usage.json: %s", exc)
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try:
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tmp_path.unlink(missing_ok=True)
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except OSError:
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pass
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