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Topic: agent

1,444 skills in this topic.

code-analysis Code review and debugging assistant. Identifies bugs, performance issues, security vulnerabilities, and suggests optimizations.
baidu-baige/LoongFlow 408
loongflow PEES (Plan-Execute-Evaluate-Summary) iterative problem-solving methodology with LoongFlow engine for complex tasks. Use when tasks need structured iteration, optimization, evolution, or when user mentions loongflow/PEES/PES.
baidu-baige/LoongFlow 408
memos-local Persistent local memory for OpenClaw agents. Use when users say: - "install memos" - "install MemOS" - "setup memory" - "add memory plugin" - "openclaw memory" - "memos onboarding" - "memory not working" - "configure memory" - "enable memory" - "upgrade MemOS" - "update memory plugin"
MemTensor/MemOS 8,297
browserwing-admin Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.
MemTensor/MemOS 8,297
browserwing-executor Control browser automation through HTTP API. Supports page navigation, element interaction (click, type, select), data extraction, accessibility snapshot analysis, screenshot, JavaScript execution, and batch operations.
MemTensor/MemOS 8,297
memos-memory-guide Use the MemOS Local memory system to search and use the user's past conversations. Use this skill whenever the user refers to past chats, their own preferences or history, or when you need to answer from prior context. When auto-recall returns nothing (long or unclear user query), generate your own short search query and call memory_search. Available tools: memory_search, memory_get, memory_write_public, memory_share, memory_unshare, task_summary, skill_get, skill_search, skill_install, skill_publish, skill_unpublish, network_memory_detail, network_skill_pull, network_team_info, memory_timeline, memory_viewer.
MemTensor/MemOS 8,297
ask-user-question Ask users questions via the UI. Use when you need clarification, user preferences, or confirmation before proceeding. The user CANNOT see CLI output - this tool is the ONLY way to communicate with them.
MemTensor/MemOS 8,297
dev-browser Browser automation with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website", "log into", or any browser interaction request.
MemTensor/MemOS 8,297
safe-file-deletion Enforces explicit user permission before any file deletion. Activates when you're about to use rm, unlink, fs.rm, or any operation that removes files from disk. MUST be followed for all delete operations.
MemTensor/MemOS 8,297
add-new-entry Workflow and tools for adding new entries from temp.md to the section files. Includes legend format, section reference, code tools, and common pitfalls. USE FOR: Adding new resources to the knowledge base. DO NOT USE FOR: Editing existing entries or restructuring sections.
kimtth/awesome-azure-openai-llm 398
classify-temp-entries-to-section Classification guidelines for entries in temp_entries.md. Each entry have its own title with the markdown file name and section name in temp_entries.md. USE FOR: Classifying new entries in temp_entries.md into *.md in the section files. DO NOT USE FOR: 1) Adding new entries to temp_entries.md; 2) Moving entries between sections.
kimtth/awesome-azure-openai-llm 398
update-app-count Workflow for updating the popular LLM applications pool (section/x_llm_apps.md) using get_app_list_by_github_star.py. Covers full refresh, alternate exports, topic tuning, and common pitfalls. USE FOR: Refreshing the ranked GitHub applications list linked from applications.md. DO NOT USE FOR: Hand-curating application entries inside applications.md or adding GitHub star badges to the generated file.
kimtth/awesome-azure-openai-llm 398
update-cite-count Guidelines for updating citation counts for papers in the section files using the `update_citation_counts.py` tool. USE FOR: Updating citation counts for papers listed in the section files to keep information current. DO NOT USE FOR: 1) Adding new papers to the section files; 2) Classifying entries into sections.
kimtth/awesome-azure-openai-llm 398
update-llm-pool Workflow for updating the LLM landscape paper pool (section/x_llm_papers.md) using fetch_llm_papers.py. Covers full re-fetch, resume from checkpoint, and adding new topics. USE FOR: Refreshing citation counts, expanding topic coverage. DO NOT USE FOR: Adding hand-curated entries to section files (use add-new-entry), updating RAG/Agent citation sections in best_practices.md (use update-cite-count).
kimtth/awesome-azure-openai-llm 398
frontman-dev AI-powered visual frontend editing in your browser. Click any element in your running app, describe changes in plain English, and get real source file edits with instant hot reload. Works with Next.js, Astro, and Vite.
frontman-ai/frontman 262
add-model Add a new language model to the Giselle codebase. Use when the user wants to add, register, or integrate a new LLM model (OpenAI, Anthropic, Google) into the system.
giselles-ai/giselle 510
workspace-dispatch Single-agent mission orchestrator. Decomposes a mission into tasks, spawns one worker per task using the default model, verifies exit criteria, and chains tasks with retry. No critic pattern — each worker self-verifies. Simple, fast, works with any model config.
outsourc-e/clawsuite 306
workspace-dispatch Autonomous multi-agent mission orchestrator. Decomposes a mission into tasks, spawns sub-agents for each step, reviews output against exit criteria, and chains tasks automatically with retry. State persists to disk so missions survive context loss. Triggered by the Conductor UI or by direct user request.
outsourc-e/clawsuite 306
pr-writing-review Extract and analyze writing improvements from GitHub PR review comments. Use when asked to show review feedback, style changes, or editorial improvements from a GitHub pull request URL. Handles both explicit suggestions and plain text feedback. Produces structured output comparing original phrasing with reviewer suggestions to help refine future writing.
evalstate/fast-agent 3,743
session-investigator Investigate fast-agent session and history files to diagnose issues. Use when a session ended unexpectedly, when debugging tool loops, when correlating sub-agent traces with main sessions, or when analyzing conversation flow and timing. Covers session.json metadata, history JSON format, message structure, tool call/result correlation, and common failure patterns.
evalstate/fast-agent 3,743
wren-mcp-setup Set up Wren Engine MCP server via Docker and register it with an AI agent. Covers pulling the Docker image, running the container with docker run, mounting a workspace, configuring connection info via the Web UI (with Docker host hint), registering the MCP server in Claude Code (or other MCP clients) using streamable-http transport, and starting a new session to interact with Wren MCP. Trigger when a user wants to run Wren MCP in Docker, configure Claude Code MCP, or connect an AI client to a Dockerized Wren Engine.
Canner/wren-engine 639
wren-project Save, load, and build Wren MDL manifests as YAML project directories for version control. Use when a user wants to persist an MDL as human-readable YAML files, load a YAML project back into MDL JSON, or compile a YAML project to a deployable mdl.json file.
Canner/wren-engine 639
wren-quickstart End-to-end quickstart for Wren Engine — create a workspace, generate an MDL from a live database, save it as a versioned project, start the Wren MCP Docker container, and verify the setup with a health check. Trigger when a user wants to set up Wren Engine from scratch, onboard a new data source, or get started with Wren MCP. Requires dependent skills already installed (use /wren-usage to install them first).
Canner/wren-engine 639
wren-sql Write and correct SQL queries targeting Wren Engine — covers MDL query rules, filter strategies, data types (ARRAY, STRUCT, JSON/VARIANT), date/time functions, Calculated Fields, BigQuery dialect quirks, and error diagnosis. Use when generating or debugging SQL for any Wren Engine data source.
Canner/wren-engine 639