clawiser

Initialize layered memory, configure memorySearch and cron jobs, and write HANDOFF.md routing rules.

2|Updated Apr 6, 2026
One-click install
npx skills add https://github.com/augustscl/awesome-xiawang-skills --skill clawiser-augustscl
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: clawiser
Source: https://github.com/augustscl/awesome-xiawang-skills/tree/main/clawiser
Command: npx skills add https://github.com/augustscl/awesome-xiawang-skills --skill clawiser-augustscl

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

ClaWiser fixes fragile agent memory, noisy transcripts, and ad-hoc workflows by installing a coordinated suite that ensures persistent, searchable memory, regular noise reduction, and structured project handoffs so agents stop forgetting context and acting impulsively.

Core Features & Use Cases

  • Memory foundation & health: bootstraps transcripts, projects, git, merge and auto-commit scripts, and verifies vector search readiness.
  • Retrieval & denoising: configures hybrid memory search (MMR, temporal decay, cache) and runs diagnosic plus automated noise-reduction workflows to improve recall quality.
  • Workflow modules: provides HDD (hypothesis-driven), SDD (scenario-driven), save-game/load-game for robust handoffs, and project-skill-pairing to keep skills organized.
  • Operational automation: installs cron checks, diagnostics, and child-agent initialization steps so complex setup runs reliably without manual orchestration.
  • Use case: initialize ClaWiser to turn raw session logs into compact, searchable project HANDOFFs, reduce noise from channel metadata, and establish routable rules for when to auto-save or restore project context.

Quick Start

Tell your agent to install and initialize ClaWiser by saying "安装 ClaWiser" or "运行 ClaWiser 初始化" to run the automatic setup and diagnostics.

Frequently Asked Questions about clawiser

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I maintain persistent agent memory across multi-session projects?

Agent memory loss happens when session context is not persisted or searchable. This Skill installs layered memory with vector search readiness, noise reduction, and structured HANDOFF.md files to ensure agents retain project context across multi-session workflows.

What's the best way to reduce noise in agent transcripts and channel metadata?

Reducing transcript noise requires automated denoising workflows and retrieval tuning. This Skill runs diagnostic scripts and configures hybrid memory search with MMR and temporal decay to filter channel metadata and improve recall quality.

How do I set up structured project handoffs for AI agents?

Structured project handoffs require routing rules and save-game mechanisms to restore context reliably. This Skill writes AGENTS.md routing rules and generates compact HANDOFF.md files, enabling reliable state restoration during workflow transitions.

Does this agent workflow automation tool require manual orchestration for setup?

No manual orchestration is required for workflow automation setup. This Skill installs cron checks, child-agent initialization, and auto-commit scripts, allowing complex memory configuration and diagnostics to run reliably without manual intervention.

When do I need hypothesis-driven debugging and scenario-driven planning for agent workflows?

Hypothesis-driven debugging and scenario-driven planning are needed when agents act impulsively or lose context during complex multi-step tasks. This Skill provides dedicated workflow modules to structure agent reasoning, ensuring robust handoffs and organized project-skill pairing.