@gaodes/pi-graphify

Turn any folder of files (code, docs, papers, images, video) into a queryable knowledge graph with community detection, an honest audit trail, and three outputs: interactive HTML, GraphRAG-ready JSON, and a plain-language GRAPH_REPORT.md.

Source · npm

Inspired by graphify — the AI coding assistant skill. This extension wraps graphify's Python CLI for native Pi integration.

It also bundles a graphify skill (skills/graphify/SKILL.md) for full-pipeline orchestration. Use /skill:graphify when you want the guided multi-step workflow; use the tools and /graphify command for fast operational calls.

Tools

Tool	Description
graphify_build	Build a knowledge graph from a directory (full pipeline: detect → extract → cluster → visualize)
graphify_query	Query the graph — BFS for broad context, DFS for tracing specific paths
graphify_path	Find the shortest path between two concepts in the graph
graphify_explain	Plain-language explanation of a node — everything connected to it
graphify_add	Fetch a URL and add it to the corpus, then update the graph
graphify_update	Incremental update — re-extract only changed files
graphify_watch	Watch a directory for changes, auto-rebuild graph on code edits
graphify_cluster	Re-run community detection on an existing graph (no re-extraction)
graphify_extract	Headless LLM extraction for CI — defaults to deepseek; also supports claude, kimi, openai, gemini, ollama, bedrock, claude-cli
graphify_export_callflow	Generate self-contained Mermaid architecture/call-flow HTML from graph.json
graphify_upgrade	Check for and install graphifyy CLI updates via uv

Commands

Command	Description
/graphify	Single entry point with autocomplete for all subcommands and flags

Subcommands and flags

/graphify <path>                              # build graph (full pipeline, semantic backend defaults to deepseek)
/graphify <path> --mode deep                  # thorough extraction, richer INFERRED edges
/graphify <path> --update                     # incremental — re-extract only changed files
/graphify <path> --cluster-only               # rerun clustering on existing graph
/graphify <path> --no-viz                     # skip visualization, just report + JSON
/graphify <path> --obsidian                   # generate Obsidian vault
/graphify <path> --svg                        # export graph.svg
/graphify <path> --graphml                    # export for Gephi / yEd
/graphify <path> --neo4j                      # generate cypher.txt for Neo4j
/graphify <path> --callflow                   # generate callflow architecture HTML

/graphify query "<question>"                  # BFS traversal — broad context
/graphify query "<question>" --dfs            # DFS — trace a specific path
/graphify query "<question>" --budget 1500    # cap answer at N tokens
/graphify path "ConceptA" "ConceptB"          # shortest path between two concepts
/graphify explain "ConceptName"               # plain-language explanation of a node
/graphify add <url>                           # fetch URL, save to ./raw, update graph
/graphify add <url> --author "Name"           # tag who wrote it
/graphify update <path>                       # incremental update
/graphify watch <path>                        # watch folder, auto-rebuild on changes
/graphify cluster                             # rerun clustering on existing graph
/graphify hook install                        # install git hooks for auto-rebuild
/graphify hook uninstall                      # remove git hooks
/graphify hook status                         # check hook status
/graphify extract <path>                      # headless LLM extraction for CI
/graphify extract <path> --backend claude     # specify LLM backend
/graphify extract <path> --backend kimi       # Kimi AI backend
/graphify extract <path> --backend openai     # OpenAI backend
/graphify extract <path> --backend gemini     # Google Gemini backend
/graphify extract <path> --backend ollama     # Ollama (local) backend
/graphify extract <path> --backend bedrock    # AWS Bedrock backend
/graphify extract <path> --max-workers 4      # limit parallel workers
/graphify extract <path> --token-budget 4096  # cap tokens per LLM call
/graphify extract <path> --api-timeout 300    # HTTP timeout in seconds
/graphify extract <path> --backend deepseek   # DeepSeek backend (default)
/graphify extract <path> --backend claude-cli  # route through Claude Code CLI
/graphify extract <path> --resolution 2.0      # Leiden clustering resolution
/graphify extract <path> --exclude-hubs 0.05   # exclude top-P% hub nodes
/graphify extract <path> --exclude '*.min.js'  # runtime exclusion patterns
/graphify upgrade                            # check for graphifyy CLI updates
/graphify upgrade --install                  # install latest graphifyy version
/graphify uninstall                           # remove graphify from all platforms
/graphify uninstall --purge                   # also delete graphify-out/

Prerequisites

• Python 3.10+
• graphifyy package (auto-installed on first run): pip install graphifyy or uv tool install graphifyy

Install

pi install @gaodes/pi-graphify

Configuration

Key: pi-graphify in prime-settings.json (legacy graphify key auto-migrates on load).

Setting	Type	Default	Description
enabled	boolean	true	Enable/disable the extension
pythonPath	string	"python3"	Path to Python interpreter
outputDir	string	"graphify-out"	Output directory name
semanticBackend	string	"deepseek"	Default semantic extraction backend for builds/extracts
autoContext.enabled	boolean	true	Enable Graphify auto-context hooks
autoContext.sessionSummary	boolean	true	Inject architecture orientation at session start
autoContext.augmentSearchResults	boolean	true	Enable Graphify augmentation of tool results (hints + intent-aware suggestions)
autoContext.intentSuggestions	boolean	true	Generate intent-aware suggested queries in tool-result hints
autoContext.autoQuery	boolean	false	Run actual graphify queries on high-confidence intents (off by default)
autoContext.includeReport	boolean	true	Include GRAPH_REPORT.md content in session orientation
autoContext.includeWiki	boolean	true	Include wiki/index.md in session orientation
autoContext.reportMaxChars	number	6000	Max characters read from report/wiki files
autoContext.queryBudget	number	1200	Budget hint for graphify_query follow-up usage
autoContext.maxSessionAugments	number	8	Max tool-result augmentations per session
autoContext.maxAugmentChars	number	1200	Hard bound on appended context characters
autoContext.minToolResultLines	number	8	Minimum lines in tool result to trigger augmentation
autoContext.triggerTools	string[]	(see defaults)	Tool names that trigger augmentation
autoContext.triggerPatterns	string[]	(see defaults)	Input patterns that trigger architecture-level hints

Auto-context behavior

When graphify-out/graph.json exists in the current project, pi-graphify provides architecture-level context to the agent. This complements GitNexus (which provides symbol-level call-graph intelligence).

• Session orientation — injects a concise [Graphify active] prompt with suggested queries and report summary when sessionSummary is enabled
• Intent-aware tool hints — classifies tool results by intent (broad search, high-value file reads, architecture terms) and appends relevant Graphify suggestions
• Optional auto-query — when autoQuery is enabled, runs bounded graphify query on high-confidence intents (disabled by default to avoid cost/noise)
• Session budgets — enforces max augmentations per session and hard character limits
• Deduplication — caches augmented and empty results to avoid repeated noise

Settings profiles

Quiet — session hint only:

{ "pi-graphify": { "autoContext": { "sessionSummary": true, "augmentSearchResults": false, "autoQuery": false } } }

Balanced (default) — architecture hints without auto-query:

{ "pi-graphify": { "autoContext": { "sessionSummary": true, "intentSuggestions": true, "augmentSearchResults": true, "autoQuery": false, "maxSessionAugments": 8 } } }

Proactive — auto-query on high-confidence intents:

{ "pi-graphify": { "autoContext": { "sessionSummary": true, "intentSuggestions": true, "augmentSearchResults": true, "autoQuery": true, "maxSessionAugments": 12, "maxAugmentChars": 1800 } } }

Graphify vs GitNexus

Aspect	Graphify	GitNexus
Scope	Architecture, concepts, communities, docs	Symbols, call graphs, execution flows
Best for	"What is this system made of?"	"What calls this, and what breaks?"
Augmentation	Session orientation + intent-aware hints	Pre-commit impact analysis + code context
Trigger	Broad search, overview files, architecture	Code edits, symbol lookups
Query tools	graphify_query, graphify_explain	gitnexus_query, gitnexus_impact

Use Graphify when exploring system shape and cross-cutting concepts. Use GitNexus when tracing code paths and assessing change impact.

• This is Pi-native behavior in this extension; the Graphify skill is installed by graphify install --platform pi to the global Pi skills directory (~/.pi/agent/skills/graphify/SKILL.md). Auto-reinstalled on upgrade via graphify_upgrade.
• Auto-context hooks stay idle in projects where <outputDir>/graph.json is missing.

Git tracking policy

The extension's .gitignore ignores the entire graphify-out/ directory. Graph output is regenerated on each build and should not be committed to the repository.

If you want to track graph output for documentation purposes, override in your project's .gitignore:

!graphify-out/
!graphify-out/graph.json

Note: Earlier versions of pi-graphify tracked graphify-out/ files and selectively ignored cache/temp entries. As of v0.1.6, the entire directory is ignored for cleaner repository state.

Reliability

All child-process invocations run through a bounded exec adapter that caps stdout/stderr at 1 MiB by default. This prevents V8 heap exhaustion when graph operations produce multi-MB output — the root cause of the exit-code 32102 (OOM) crash in earlier versions.

Key safety features:

• Output budgets: 256 KiB for queries, 1 MiB for general operations, 2 MiB for JSON parsing
• Thin CLI layer: all graph operations delegate directly to the graphify CLI, avoiding inline Python script overhead and ensuring automatic upstream compatibility
• Signal-death handling: child processes killed by signals are reported as failures (exit code 1), not silent successes
• LRU cache bounding: auto-context augmentation caches cap at 256 entries

Source

• Canonical: ~/agents/primecodex/packages/pi-graphify/
• GitLab: agents/primecodex/packages/pi-graphify
• GitHub: github.com/gaodes/pi-graphify