Graphify AI编码助手

Prerequisites

macOS quick install (Homebrew):

brew install python@3.12 uv

Windows quick install:

winget install astral-sh.uv

Ubuntu/Debian: ```bash sudo apt install python3.12 python3-pip pipx

or install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh ```

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Install

[!IMPORTANT] Official package: The PyPI package is graphifyy (double-y). Other graphify* packages on PyPI are not affiliated. The CLI command is still graphify.

The official source repository is Graphify-Labs/graphify.

Step 1 — install the package:

```bash

Baked into the git hooks (see Team setup):

viz_node_limit=0 ```

The declaration controls file classification, extractor selection and language-specific grammar and resolution, and the AST cache: a file re-parsed under a different language never reuses the old entry. Original source paths and physical format conventions, such as Fortran .F90 preprocessing and C/C++ header/implementation pairing, are preserved. Optional language backends must still be installed. A typo is reported once on stderr and the scan continues with graphify's defaults.

Adding, changing, or removing a language declaration invalidates affected incremental manifest entries even when the source bytes have not changed. graphify watch recognizes declared source extensions and root .graphifyrc changes, including atomic replacement; configuration changes schedule an AST rebuild and flag semantic work for the next extraction. The same configuration is read by graphify extract, graphify update, the hooks, the MCP server, and the /graphify skill.

Extensionless local JS/TS imports can also resolve declared suffixes. Native suffixes retain precedence within file and directory-index lookup, and file candidates are tried before directory indexes. Python module and package lookups also support declared Python suffixes, while retaining native .py precedence.

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Team setup

Commit or share the graph so your whole team queries the same context, and review pull requests with graph context. See Share context with your team and Review pull requests.

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Building on graphify

Building something in the graphify ecosystem? That is encouraged. If your project uses "graphify" in its name (for example graphify-dashboard or graphify-action), please add a short note to your README clarifying that it is community-built and not affiliated with or endorsed by Graphify Labs. "graphify" and the graphify logo are marks of Graphify Labs; please do not use them in a way that implies official status.

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Recommended (isolated env; if 'graphify' isn't found after, run: uv tool update-shell):

uv tool install graphifyy

Project configuration

Create a .graphifyrc in the scan root for settings that belong to the project rather than to one run. One key=value per line; lines beginning with # are comments.

Ambiguous extensions. Some extensions mean different languages in different projects: .inc is PHP on pfSense, Pascal in a Delphi tree, SQL or assembly elsewhere; .h is C or C++; .m is Objective-C or MATLAB. graphify has to pick one global default, and when it picks wrong the file does not fail — it parses as the wrong language and yields a handful of incidental nodes, so the graph looks populated while the real symbols are missing. Declare what the extension means in your repo:

```

Environment variables

Backends, API keys, hook behavior, and tuning are controlled by environment variables. Full table: Configuration.

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CLI skills or MCP instructions?

The instructions installed by graphify install and those supplied with a Graphify MCP connection describe different ways to query a graph:

Both encourage scoped graph queries before broad source searches. Choose the instructions that match the tools your assistant can actually access; neither block establishes a universal precedence rule for your assistant's instruction files. If you use both integrations, identify which graph each queries and choose a primary query path instead of copying two unconditional instruction blocks into AGENTS.md.

graphify install installs the local assistant integration; it does not establish an MCP connection. An MCP client does not need to run local CLI queries to use its connected server. A locally hosted server still needs its own Graphify installation and graph, while a hosted connection may serve a graph that is not present in the client's working directory. If the expected tools are missing, check the relevant CLI installation or MCP connection rather than treating the other setup's instructions as interchangeable.

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Full command reference

Every command and flag, with examples: CLI reference.

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Or an extension graphify already knows:

language.tpl=.ts

Alternatives:

pipx install graphifyy pip install graphifyy # may need PATH setup — see note below

**Step 2 — register the skill with your AI assistant:**

That's it. Open your AI assistant and type `/graphify .`

To install the assistant skill into the current repository instead of your user
profile, add `--project`:

Project-scoped installs write under the current directory, for example .claude/skills/graphify/SKILL.md or .agents/skills/graphify/SKILL.md (plus a references/ sidecar the skill loads on demand), and print a git add hint for files that can be committed. Per-platform commands that support project-scoped installs accept the same flag, for example graphify claude install --project or graphify codex install --project.

[!TIP] Hitting command not found, a pip-on-Mac/Windows issue, PowerShell quoting, uvx usage, git-hook PATH quirks, or strict mode? See Installation and Troubleshooting.

<details> <summary><b>Pick your platform</b> (20+ assistants, click to expand)</summary>

Codex users also need multi_agent = true under [features] in ~/.codex/config.toml for parallel extraction. CodeBuddy uses the same Agent tool and PreToolUse hook mechanism as Claude Code. Factory Droid uses the Task tool for parallel subagent dispatch. OpenClaw and Aider use sequential extraction (parallel agent support is still early on those platforms). Trae uses the Agent tool for parallel subagent dispatch and does not support PreToolUse hooks, so AGENTS.md is the always-on mechanism.

--platform agents (alias --platform skills) targets the generic cross-framework Agent-Skills locations: the spec's user-global ~/.agents/skills/ (read by npx skills and spec-compliant frameworks) for a global install, and ./.agents/skills/ for a project (--project) install. The bare graphify install stays single-platform (Claude Code) by design — use the named agents platform when you want the skill discoverable by any framework that reads .agents/skills.

Codex uses $graphify instead of /graphify.

</details>

<details> <summary><b>Optional extras</b> (install only what you need)</summary>

</details>

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Troubleshooting

Common install and extraction issues and their fixes: Troubleshooting.

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