Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Automatically evaluates and approves agent outputs based on clarity, conciseness, actionability, and structure using a rule-based system.
Automatically evaluates and approves agent outputs based on clarity, conciseness, actionability, and structure using a rule-based system.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Automatically review agent output quality before sending to user. Checks: clarity, conciseness, actionability, structure Simple rule-based engine (no API cost) Exit code 0 = approved, 1 = needs improvement
Pipe output to reviewer: echo "Your response text" | node skills/self-review/index.js Or integrate into agent pipeline (AGENTS.md step 6).
Edit skills/self-review/index.js to adjust thresholds.
For LLM-based review, see self-review-llm skill (separate package). Author: dvinci达芬奇 (self-evolved) Version: 1.0.0 Tags: quality, automation, token-optimization
Long-tail utilities that do not fit the current primary taxonomy cleanly.
Largest current source with strong distribution and engagement signals.