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Find leads on Reddit on auto pilot

Topic: agent

1,444 skills in this topic.

structured-itinerary-responses Present time-aware itineraries with clear actions and citations
inkeep/agents 1,070
weather-safety-guardrails Keep activity suggestions safe and respect local conditions
inkeep/agents 1,070
vibegit
memovai/memov 187
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
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
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
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
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
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
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
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
Copilot instruction layering instruction layering with reusable, conditional instruction files
rcarmo/agentbox 96
Docker image publishing multi-arch image publishing to GHCR via GitHub Actions
rcarmo/agentbox 96
Frontend bundling via Bun/Node Bundling via Bun/Node with Make targets for typecheck and bundling
rcarmo/agentbox 96
GitHub Actions CI patterns CI patterns that call Make targets
rcarmo/agentbox 96
Go project conventions Project conventions with module caching, linting, security checks, and tests via Make
rcarmo/agentbox 96
Python project conventions Project conventions for install, lint, test, format, and coverage via Make
rcarmo/agentbox 96
Tag-based releases GitHub releases with autogenerated notes
rcarmo/agentbox 96
Building Native macOS CLI Apps with SwiftUI Visualization CLI apps with SwiftUI visualization
rcarmo/agentbox 96
development workflow workflow patterns for planning, subagents, self-improvement, and verification
rcarmo/agentbox 96
go-naming Go naming conventions and best practices. Use this skill when working with Go code and need to name packages, files, directories, structs, interfaces, functions, variables, or constants. Provides comprehensive naming guidelines following Go community standards.
infiniflow/ragflow 77,804
tanstack-query-best-practices TanStack Query (React Query) best practices for data fetching, caching, mutations, and server state management. Activate when building data-driven React applications with server state.
infiniflow/ragflow 77,804
file-processing Data file processing utilities for CSV, JSON, and text files. Provides helpers for reading, transforming, and validating structured data.
baidu-baige/LoongFlow 408
skill-creator Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
baidu-baige/LoongFlow 408