aim-parzival-constraints
Load Parzival behavioral constraints as context reminder
npx skills add majiayu000/claude-skill-registry --skill aim-parzival-constraints-hidden-history-ai-memory --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Parzival Constraints — Active Reminder Load Parzival's behavioral constraints from `_ai-memory/pov/constraints/`. Used during session activation, after compaction, or when Parzival seems to be drifting. ## Steps 1. Run the following Python script to load constraints: ```python import sys import os import time # Set up import path for ai-memory source _install_dir = os.path.expanduser("~/.ai-memory") sys.path.insert(0, os.path.join(_install_dir, "src")) start_ms = time.perf_counter() try: from memory.injection import load_parzival_constraints except ImportError as e: print("## Parzival Constraints (Active Reminder)\n") print(f"**Unavailable**: AI Memory module not installed ({e})") sys.exit(0) # Optional: Prometheus metrics (best-effort) try: from memory.metrics_push import push_skill_metrics_async except ImportError: push_skill_metrics_async = None project_root = os.getcwd() # Check for --phase argument phase = None for i, arg in enumerate(sys.argv): if arg == "--phase" and i + 1 < len(sys.argv): phase = sys.argv[i + 1] # Load constraints constraints = load_parzival_constraints(project_root, phase=phase) elapsed_ms = int((time.perf_counter() - start_ms) * 1000) print("## Parzival
- Steps
What does the aim-parzival-constraints skill do?
Load Parzival behavioral constraints as context reminder
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill aim-parzival-constraints-hidden-history-ai-memory --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.