hivemind-graph
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).
Profile →npx skills add activeloopai/hivemind --skill hivemind-graph --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Hivemind Code 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`). It is queried as synthesized files under the Deeplake mount; there are no real files on disk and no network call in the read path. The graph **builds and refreshes automatically** (on Stop / SessionEnd, gated by a rate limit + git diff). You never run a build command — just read it. Use it as a fast **INDEX** to locate the few files/symbols that matter, then open them with `Read` to answer. It is not a substitute for the source. ## When to use this skill Activate when the user asks a *structural / relational* question about the code: - "What calls `pushSnapshot`?" / "Who uses this function?" - "What does `deeplake-pull.ts` import?" / "What depends on X?" - "Where is `GraphSnapshot` defined?" / "Find the function that handles Y." - "What are the main subsystems / the architecture here?" - "If I change this signature, what's affected?" → use `impact/<symbol>` (transitive blast radius) ## When NOT to use this skill - Reading the **body** of a sy
- When to use this skill
- When NOT to use this skill
- Path cheat sheet
- Workflow
- Anti-patterns (read these)
cat ~/.deeplake/memory/graph/index.md cat ~/.deeplake/memory/graph/query/<pattern> # START HERE (the 2-in-1) Search + expand the top matches with their 1-hop neighbors (callers, cat ~/.deeplake/memory/graph/find/<pattern> Case-insensitive substring search on node id + label (max 50 hits). Prints numbered handles [1] [2] ... saved for this worktree. cat ~/.deeplake/memory/graph/show/<handle-or-pattern> cat ~/.deeplake/memory/graph/neighborhood/<file> Every symbol in a file + its cross-file neighbors (callers/callees/imports). cat ~/.deeplake/memory/graph/impact/<pattern>
What does the hivemind-graph skill do?
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).
How do I install it?
Run `npx skills add activeloopai/hivemind --skill hivemind-graph --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From activeloopai/hivemind, a repository with 1,530 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.