Query the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).
npx skills add https://github.com/activeloopai/hivemind --skill hivemind-graph
A deterministic, AST-derived map of the current repository — every function,
class, method, interface, type, enum, const, and module, plus the edges between
them (calls, imports, extends, implements, method_of).
The graph builds and refreshes automatically after each turn (gated by rate
limit + git diff). You never run a build command — just call the graph tools.
Set plugins.entries.hivemind.config.tuning.HIVEMIND_GRAPH_CWD in
~/.openclaw/openclaw.json to the git root of the project you want indexed
when the gateway's working directory is not the repo (then restart the gateway).
Use the graph as a fast INDEX to locate the few files/symbols that matter,
then use the host's read/exec tools on the real source. It is not a substitute
for reading source files.
Activate when the user asks a *structural / relational* question about the code:
pushSnapshot?" / "Who uses this function?"deeplake-pull.ts import?" / "What depends on X?"GraphSnapshot defined?" / "Find the function that handles Y."hivemind_graph_search({ pattern }) — search symbols by substring (ormulti-token AND with +, e.g. auth+handler). Returns matches with 1-hop
neighbors (callers, callees, imports). Start here.
hivemind_graph_neighborhood({ file }) — every symbol in a repo-relativefile path plus its cross-file neighbors.
hivemind_graph_search({ pattern: "<symbol>" }).hivemind_graph_neighborhood({ file: "src/hooks/capture.ts" }).source_file:line from the tool output withthe host read tool — don't answer from the graph alone.
dynamic calls are not fully resolved.
pattern is lexical, not semantic — try multiple keywords if the first misses.Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take activeloopai/hivemind-openclaw-hivemind-graph from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.