Agent skill

Hivemind Graph

by activeloopai in activeloopai/hivemind

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/.

Apache-2.0Auto-check: notesAI & LLM Engineering

Install Hivemind Graph

skills CLI
$ npx skills add activeloopai/hivemind --skill hivemind-graph -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install activeloopai/hivemind hivemind-graph --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/activeloopai/hivemind.git skills-src && mkdir -p .claude/skills && cp -r skills-src/harnesses/codex/skills/hivemind-graph .claude/skills/hivemind-graph && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hivemind-graph
GitHub stars
1.6k
Token cost
~1.2k tokens
SKILL.md length
446 words
Files
1
Skills in repo
7
Repo updated
First seen
Licence
Apache-2.0

At a glance

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/.

  • Works in 5 steps: Broad? Start at index.md to see… → Looking for a symbol? find/ (or query/)… → Want relationships? show/ /… → …
  • The user asks structural questions about the codebase — what calls X?
  • SKILL.md covers When to use this skill, When NOT to use this skill, Path cheat sheet and Workflow, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Hivemind Graph is an agent skill from activeloopai/hivemind. 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 is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering. The repository describes itself as: Hivemind turns your traces into reusable skills across agents. The licence is Apache-2.0.

When your agent uses it

  • The user asks structural questions about the codebase — what calls X?
  • What does Y import?
  • Where is Z defined?
  • What is the architecture / which subsystems exist?

Example prompts

  • “what calls X?”
  • “what does Y import?”
  • “where is Z defined?”
  • “/hivemind-graph”

Requirements

  • Pre-approved tools (allowed-tools): Bash

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Broad? Start at index.md to see subsystems and the biggest files.
  2. Looking for a symbol? find/ (or query/) → pick the handle.
  3. Want relationships? show/ / neighborhood/ → callers/callees, imports.
  4. Tracing a flow? path//. Change impact? impact/.
  5. Need the actual code? Take the source_file:line and Read it — don't answer from the graph alone.

What it can do on your machine

Read from SKILL.md and the folder at commit e054fb1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hivemind Graph loads about 1.2k tokens when it runs. Until then it costs about 104 tokens; SKILL.md has 446 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~104
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from activeloopai/hivemind at commit e054fb1, republished under its Apache-2.0 licence (© activeloopai). 446 words, ~1,208 tokens.

Download SKILL.mdSave it as .claude/skills/hivemind-graph/SKILL.md (or your agent's skills folder).
name
hivemind-graph
description
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 is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).
allowed-tools
Bash

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 symbol you already located → use Read on the real source file. The graph gives location + relationships, not full source.
  • Code that isn't committed/built yet — the graph can lag uncommitted edits. If a file's mtime is newer than the build timestamp, read the live source.
  • Languages outside TypeScript, JavaScript, and Python (Go, Rust, …) — the extractor covers those three, with cross-file calls/imports resolved for named imports. For anything else, fall back to grep/read.

Path cheat sheet

bash
cat ~/.deeplake/memory/graph/index.md
#   Overview: node/edge counts, kind breakdown, top files by node count.

cat ~/.deeplake/memory/graph/query/<pattern>   # START HERE (the 2-in-1)
#   Search + expand the top matches with their 1-hop neighbors (callers,
#   callees, imports, heritage). Multi-token AND: query/<a>+<b>.

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>
#   <handle>: a digit from a prior find/ (e.g. 3).
#   <pattern>: a substring → unique node detail, or a candidate list.
#   Output: the node + its 1-hop neighbors grouped by edge relation.

cat ~/.deeplake/memory/graph/neighborhood/<file>
#   Every symbol in a file + its cross-file neighbors (callers/callees/imports).

cat ~/.deeplake/memory/graph/impact/<pattern>
#   Transitive dependents — the blast radius of changing a symbol.

cat ~/.deeplake/memory/graph/path/<from>/<to>
#   Shortest dependency path between two symbol patterns (trace a flow across files).

cat ~/.deeplake/memory/graph/layers      # architectural layers / subsystems
cat ~/.deeplake/memory/graph/tour        # deterministic guided walkthrough
Show full SKILL.md (190 more words)Show less

Workflow

  1. Broad? Start at index.md to see subsystems and the biggest files.
  2. Looking for a symbol? find/<name> (or query/<name>) → pick the handle.
  3. Want relationships? show/<handle> / neighborhood/<file> → callers/callees, imports.
  4. Tracing a flow? path/<from>/<to>. Change impact? impact/<symbol>.
  5. Need the actual code? Take the source_file:line and Read it — don't answer from the graph alone.

Anti-patterns (read these)

  • "Incoming (0)" does NOT mean dead code. Cross-file calls are resolved for named imports (TS/JS/Python), but instance-method dispatch (obj.method()), dynamic calls, and nested/inner functions are NOT — a zero-incoming symbol may still be reached via one of those. Confirm in the source before calling it unused.
  • The graph can be stale. It rebuilds at most once per rate-limit window. The SessionStart inject prints the build age; if it's old or you've just edited a file, prefer the live source for that file.
  • Don't try to build it. There is no user-facing build step in normal use; the hooks handle it. Just read the mount.
  • find/ is lexical, not semantic. It matches substrings, not meaning — find/auth won't surface login/credentials unless those strings appear in the id/label. Try multiple keywords if the first misses.

© activeloopai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in harnesses/codex/skills/hivemind-graph of activeloopai/hivemind.

Open the folder on GitHubat commit e054fb1

Compare with similar skills

Hivemind Graph next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hivemind Graph compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hivemind Graph this skillactiveloopai/hivemind1.6k—~1.2kAutomated safety check: NotesApache-2.0
Agent BuildershareAI-lab/learn-claude-code78k6 repos~1.2kAutomated safety check: PassMIT
Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
Peft Fine TuningOrchestra-Research/AI-Research-SKILLs13k9 repos~3.1kAutomated safety check: PassMIT
Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs13k9 repos~3.3kAutomated safety check: PassMIT
1passwordtrpc-group/trpc-agent-go1.8k13 repos~656Automated safety check: PassApache-2.0

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Questions about Hivemind Graph

What does Hivemind Graph do?

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Hivemind Graph is an agent skill from activeloopai/hivemind. Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/.

When should I use Hivemind Graph?

Hivemind Graph fits situations like: the user asks structural questions about the codebase — what calls X?; what does Y import?; where is Z defined?; what is the architecture / which subsystems exist?.

How do I install Hivemind Graph in Claude Code?

Run `npx skills add activeloopai/hivemind --skill hivemind-graph -a claude-code`. Or copy the skill folder (harnesses/codex/skills/hivemind-graph in activeloopai/hivemind) into .claude/skills/hivemind-graph in your project. Claude Code loads it when a task matches its description.

How do I install Hivemind Graph in Codex?

Run `npx skills add activeloopai/hivemind --skill hivemind-graph -a codex`. Or copy the skill folder (harnesses/codex/skills/hivemind-graph in activeloopai/hivemind) into .agents/skills/hivemind-graph in your project. Codex loads it when a task matches its description.

Can I use Hivemind Graph in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add activeloopai/hivemind --skill hivemind-graph -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hivemind-graph, .gemini/skills/hivemind-graph, .github/skills/hivemind-graph and .opencode/skills/hivemind-graph in your project.

What does Hivemind Graph need to run?

SKILL.md names no scripts, command-line tools or credentials: Hivemind Graph is instructions for the agent only. Its frontmatter pre-approves these tools: Bash.

Does Hivemind Graph access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Hivemind Graph safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Hivemind Graph use?

Hivemind Graph is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hivemind Graph use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hivemind Graph?

Skills that share tags, products or a category with Hivemind Graph: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), Peft Fine Tuning (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hivemind Graph?

activeloopai (a GitHub organization) maintains it in activeloopai/hivemind, which has 1,622 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on September 28, 2026.

Source: activeloopai/hivemind on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.