Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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vibegit
memovai/memov 187
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autoresearch-finalize
Finalize an autoresearch session into clean, reviewable branches. Use when asked to "finalize autoresearch", "clean up experiments", or "prepare autoresearch for review".
davebcn87/pi-autoresearch 3,561
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autoresearch-create
Set up and run an autonomous experiment loop for any optimization target. Gathers what to optimize, then starts the loop immediately. Use when asked to "run autoresearch", "optimize X in a loop", "set up autoresearch for X", or "start experiments".
davebcn87/pi-autoresearch 3,561
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ref-hallucination-arena
Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.
agentscope-ai/OpenJudge 538
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bib-verify
Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bibliography entries for accuracy.
agentscope-ai/OpenJudge 538
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openjudge
Build custom LLM evaluation pipelines using the OpenJudge framework. Covers selecting and configuring graders (LLM-based, function-based, agentic), running batch evaluations with GradingRunner, combining scores with aggregators, applying evaluation strategies (voting, average), auto-generating graders from data, and analyzing results (pairwise win rates, statistics, validation metrics). Use when the user wants to evaluate LLM outputs, compare multiple models, design scoring criteria, or build an automated evaluation system.
agentscope-ai/OpenJudge 538
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auto-arena
Automatically evaluate and compare multiple AI models or agents without pre-existing test data. Generates test queries from a task description, collects responses from all target endpoints, auto-generates evaluation rubrics, runs pairwise comparisons via a judge model, and produces win-rate rankings with reports and charts. Supports checkpoint resume, incremental endpoint addition, and judge model hot-swap. Use when the user asks to compare, benchmark, or rank multiple models or agents on a custom task, or run an arena-style evaluation.
agentscope-ai/OpenJudge 538
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paper-review
Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline. Supports PDF files and LaTeX source packages (.tar.gz/.zip). Covers 10 disciplines: cs, medicine, physics, chemistry, biology, economics, psychology, environmental_science, mathematics, social_sciences. Use when the user asks to review, evaluate, critique, or assess a research paper, check references, or verify a BibTeX file.
agentscope-ai/OpenJudge 538
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claude-authenticity
Detect whether an API endpoint is backed by genuine Claude (not a wrapper, proxy, or impersonator) using 9 weighted rule-based checks that mirror the claude-verify project. Also extracts injected system prompts from providers that override Claude's identity. Fully self-contained — copy the code below and run, no extra packages beyond httpx. Use when the user wants to verify a Claude API key or endpoint, check if a third-party Claude service is authentic, audit API providers for Claude authenticity, test multiple models in parallel, or discover what system prompt a provider has injected.
agentscope-ai/OpenJudge 538
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rl-reward
Build RL reward signals using the OpenJudge framework. Covers choosing between pointwise and pairwise reward strategies based on RL algorithm, task type, and cost; aggregating multi-dimensional pointwise scores into a scalar reward; pairwise tournament reward for GRPO on subjective tasks (net win rate across group rollouts); generating preference pairs for DPO/RLAIF; and normalizing scores for training stability. Use when building reward models, scoring rollouts for GRPO/REINFORCE, generating preference data for DPO, or doing Best-of-N selection.
agentscope-ai/OpenJudge 538
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find-skills-combo
Discover and recommend **combinations** of agent skills to complete complex, multi-faceted tasks. Provides two recommendation strategies — **Maximum Quality** (best skill per subtask) and **Minimum Dependencies** (fewest installs). Use this skill whenever the user wants to find skills, asks "how do I do X", "find a skill for X", or describes a task that likely requires multiple capabilities working together. Also use when the user mentions composing workflows, building pipelines, or needs help across several domains at once — even if they only say "find me a skill". This skill supersedes simple single-skill search by decomposing the task into subtasks and assembling an optimal skill portfolio.
agentscope-ai/OpenJudge 538
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recall
Search agentmemory for past observations, sessions, and learnings about a topic. Use when the user says "recall", "remember", "what did we do", or needs context from past sessions.
rohitg00/agentmemory 755
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session-history
Show what happened in recent past sessions on this project. Use when user asks "what did we do last time", "session history", "past sessions", or wants an overview of previous work.
rohitg00/agentmemory 755
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forget
Delete specific observations or sessions from agentmemory. Use when user says "forget this", "delete memory", or wants to remove specific data for privacy.
rohitg00/agentmemory 755
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remember
Explicitly save an insight, decision, or learning to agentmemory's long-term storage. Use when the user says "remember this", "save this", or wants to preserve knowledge for future sessions.
rohitg00/agentmemory 755
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capabilities
Show what this NanoClaw instance can do — installed skills, available tools, and system info. Read-only. Use when the user asks what the bot can do, what's installed, or runs /capabilities.
qwibitai/nanoclaw 27,176
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status
Quick read-only health check — session context, workspace mounts, tool availability, and task snapshot. Use when the user asks for system status or runs /status.
qwibitai/nanoclaw 27,176
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slack-formatting
Format messages for Slack using mrkdwn syntax. Use when responding to Slack channels (folder starts with "slack_" or JID contains slack identifiers).
qwibitai/nanoclaw 27,176
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agent-browser
Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.
qwibitai/nanoclaw 27,176
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add-voice-transcription
Add voice message transcription to NanoClaw using OpenAI's Whisper API. Automatically transcribes WhatsApp voice notes so the agent can read and respond to them.
qwibitai/nanoclaw 27,176
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add-whatsapp
Add WhatsApp as a channel. Can replace other channels entirely or run alongside them. Uses QR code or pairing code for authentication.
qwibitai/nanoclaw 27,176
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add-reactions
Add WhatsApp emoji reaction support — receive, send, store, and search reactions.
qwibitai/nanoclaw 27,176
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qodo-pr-resolver
Review and resolve PR issues with Qodo - get AI-powered code review issues and fix them interactively (GitHub, GitLab, Bitbucket, Azure DevOps)
qwibitai/nanoclaw 27,176
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customize
Add new capabilities or modify NanoClaw behavior. Use when user wants to add channels (Telegram, Slack, email input), change triggers, add integrations, modify the router, or make any other customizations. This is an interactive skill that asks questions to understand what the user wants.
qwibitai/nanoclaw 27,176