Deep research over the Semantic Scholar Graph API. Covers endpoints missing from allenai's lookup skill — paper references (backward citations), recommendations, batch paper lookup (up to 500 IDs), snippet search, and multi-hop citation graph traversal (BFS forward/backward). Use when the user asks to build a citation…
Token-isolated deep research agent for academic papers. Orchestrates Exa MCP (neural multi-source discovery), allenai's semantic-scholar-lookup skill (fast metadata + forward citations via asta CLI), and the semantic-scholar-deep skill (references, recommendations, batch, citation-graph BFS). Use when the user asks…
View and configure settings for coding agents (Claude Code, Codex CLI, OpenCode, and others). Covers JSON settings for Claude Code, TOML for Codex CLI, and JSON/JSONC for OpenCode, including permissions, sandbox, model selection, profiles, feature flags, providers, hooks, subagents, and skills.
Search, find, discover, install, remove, update, review, deduplicate, list, move, optimise, and iterate on skills for AI coding agents. Use when user asks "find a skill for X", "install skill", "remove skill", "update skills", "list skills", "deduplicate skills", "why are two skills shown", "choose the canonical…
Maintain a project thesaurus (domain glossary) following DDD ubiquitous language principles. Use PROACTIVELY when naming anything: variables, functions, classes, modules, database fields, API endpoints, events, files, or directories. Also use when the user asks to "create thesaurus", "update glossary", "add term"…
Use when testing Windows 11 desktop apps (WinForms/WPF/UWP) via UFO UIA/Win32 automation MCP. Triggers on "test this Windows app", "QA the app", "run smoke test", "click the button", "fill the form", "check the UI", "Windows automation", "UFO QA", "verify the dialog", or any Windows desktop UI testing task. Not for…
Instructions for CodeAlive-AI/codealive-mcp, covering agent instructions, version control, development commands, installation and setup and using uv (recommended).
Instructions for CodeAlive-AI/codealive-mcp, a project described as: Context engine for large codebases, exposed through MCP. Gives AI coding agents precise repository context; benchmarked at frontier-agent quality with 25x lower model cost and 45% fewer tokens with semantic search.
MCP server "codealive-mcp" as configured in CodeAlive-AI/codealive-mcp. Runs in Docker (ghcr.io/codealive-ai/codealive-mcp:3.0.3). Needs 1 environment variable to run.
CodeAlive context engine for semantic code search and AI-powered codebase Q&A. Enables AI coding agents to understand entire codebases beyond just open files — search across all indexed repositories, trace cross-service dependencies, discover usage patterns, and get synthesized answers to architectural questions.…
Instructions for CodeAlive-AI/codealive-skills, covering codealive-skills — notes for ai coding agents, what the skill is not, architecture in one sentence, releasing and writing the skill description.
Instructions for CodeAlive-AI/codealive-skills, a project described as: Agent skills for CodeAlive — semantic code search and AI-powered codebase answers. Works with Claude Code, Codex, Antigravity, Cursor, OpenCode, Copilot, Windsurf, Gemini CLI, and other SKILL.md-compatible agents.
Iterative code exploration across indexed repositories using CodeAlive semantic search, grep, artifact fetch, and relationship inspection. Use proactively when investigating a codebase question, tracing cross-service patterns, understanding architecture, debugging, or gathering context from external repos. Almost…
Semantic search, grep, and Q&A across codebases and documentation indexed in CodeAlive. Use when the user mentions "CodeAlive", asks to list or get data sources, list indexed repositories, search code or docs across remote repos, fetch artifact content, or trace call graphs across repositories.
Find code with Exa — API usage examples, error fixes, library docs, and GitHub repositories. Use when you need a working code snippet, to resolve an error, find an open-source implementation, or pull up official docs for a language/framework. Runs a local script against the Exa API; no MCP server required.
Research companies with Exa semantic search — find competitors, funding, headcount, news, and build company lists. Use for competitor analysis, market mapping, sourcing companies by category/stage/geo, or 'find companies like X'. Runs a local script against the Exa API; no MCP server required.
Find financial filings with Exa — SEC filings (10-K, 10-Q, S-1), earnings reports, and annual reports. Use to pull a company's financials, compare results across periods, or locate a specific filing. Runs a local script against the Exa API; no MCP server required.
Build prospect lists with Exa — find target companies matching an ICP, then their decision-makers, then enrich with signals. Use for outbound sales lists, account mapping, and B2B prospecting. Multi-pass orchestration over the Exa API; no MCP server required.
Foundation for the Exa skill collection — how to call Exa (search, contents, answer, similar) from a local script with just an EXAAPIKEY, how to write good semantic queries, and how to orchestrate subagents for deep research. Read this first; the use-case skills (company, people, papers, code, news, finance, personal…