wanng-ide

Validates JSON syntax across the workspace. Use this skill to check for syntax errors in configuration files, memory files, or data assets.

Learned from arXiv paper GameDevBench: Evaluating Agentic Capabilities Through Game Development. Use this skill to scaffold Node.js experiments based on the paper method.

Suggests emoji reactions for text messages based on sentiment analysis (positive, negative, funny, neutral). Use to increase social engagement and human-likeness in conversations.

Generates an ASCII tree or JSON representation of a directory structure. Use when you need to visualize file hierarchies, document folder contents, or debug directory layouts.

Visualizes repository complexity by counting files, lines of code, and grouping by extension. Use to assess project size or growth.

Validates and executes Python solutions for CritPt benchmark problems. Use when the user asks to check a generated solution or run a test case.

Safely apply structured JSON patches (RFC 6902) to files. Use this skill when you need to update configuration files, package.json, or memory JSONs without rewriting the whole file or using brittle regex.

verify external URLs (http/https) for availability (200-399 status code).

Validates Markdown files for broken local links.

**Source Paper:** [Scaling Agentic Verifier for Competitive Coding](https://arxiv.org/abs/2602.09012) (ID: 4a4c4dae6a5145ebc4d62eb2d64b0f0f)

Patrol latest arXiv papers and auto-generate Node.js learned skills through hunter to extractor pipeline.

Runs HLE-oriented benchmark reward ingestion and curriculum generation for capability-evolver. Use when the user asks to optimize Humanity's Last Exam score, ingest question-level benchmark results, prioritize easy-first queues, or request an immediate benchmark progress result.

Validates Markdown files in the workspace for broken local links, missing file references, and basic syntax issues. Use to maintain documentation integrity and prevent broken references in MEMORY.md or SKILL.md files.

Orchestrates the continuous learning of new skills from arXiv papers. Use this to trigger a learning cycle, which fetches papers, extracts code/skills, and solidifies them.

Analyzes the evolution memory graph for stagnation patterns, recurring failures, and success plateaus. Generates actionable insights to guide future evolution cycles.

Automates the process of extracting reusable skill code from arXiv papers. Use this skill to turn paper insights into actual OpenClaw skills.

Perform structured HTTP/HTTPS requests (GET, POST, PUT, DELETE) with custom headers and JSON body support. Use for API testing, health checks, or interacting with REST services programmatically without relying on curl.

Wraps HLE benchmark questions in a structured Chain-of-Thought (CoT) reasoning process. Use when answering HLE questions to ensure strict step-by-step logic and format compliance.

Repair malformed JSON files by normalizing them through Node.js evaluation. Use this to fix trailing commas, single quotes, unquoted keys, or other common syntax errors in JSON files (e.g. config files, manually edited data).

Proactively discovers, ranks, and installs high-value ClawHub skills by mining unresolved user needs and agent context. Use when new tasks are unsolved, when capability gaps appear, when users ask for better tools, or as a scheduled patrol for continuous skill growth.