graphify
Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists.
Skill by rylsherdamz-rgb
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/rylsherdamz-rgb-graphify
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: writing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/graphify
What's inside
- Skill name
graphify- Description
- Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools. Use when you need to understand a new codebase, map project architecture, or build a navigable knowledge graph of any folder or repo.
- License
- MIT
- Instructions
- 675 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- body: 675 lines (spec recommends under 500)
- files: referenced but missing: references/github-and-merge.md, references/transcribe.md, references/extraction-spec.md, references/exports.md, references/update.md
Files (1)
- SKILL.md
SKILL.md (first lines)
# /graphify
Turn any folder of files into a navigable knowledge graph with community detection, an honest audit trail, and three outputs: interactive HTML, GraphRAG-ready JSON, and a plain-language GRAPH_REPORT.md.
## Usage
```
/graphify # full pipeline on current directory (HTML viz; add --obsidian for a vault)
/graphify <path> # full pipeline on specific path
/graphify https://github.com/<owner>/<repo> # clone repo then run full pipeline on it
/graphify https://github.com/<owner>/<repo> --branch <branch> # clone a specific branch
/graphify <url1> <url2> ... # clone multiple repos, build each, merge into one cross-repo graph
/graphify <path> --mode deep # thorough extraction, richer INFERRED edges
/graphify <path> --update # incremental - re-extract only new/changed files
/graphify <path> --directed # build directed graph (preserves edge direction: source→target)
/graphify <path> --whisper-model medium # use a larger Whisper model for better transcription accuracy
/graphify <path> --cluster-only # rerun clustering on existing graph
/graphify <path> --no-viz # skip visualization, just report + JSON
/graphify <path> --html # (HTML is generated by default - this flag is a no-op)
/graphify <path> --svg # also export graph.svg (embeds in Notion, GitHub)
/graphify <path> --graphml # export graph.graphml (Gephi, yEd)
/graphify <path> --neo4j # generate graphify-out/cypher.txt for Neo4j
/graphify <path> --neo4j-push bolt://localhost:7687 # push directly to Neo4j
/graphify <path> --falkordb # generate graphify-out/cypher.txt for FalkorDB
/graphify <path> --falkordb-push falkordb://localhost:6379 # push directly to FalkorDB
/graphify <path> --mcp # start MCP stdio server for agent access
/graphify <path> --watch # watch folder, auto-rebuild on code changes (no LLM needed)
/graphify <path> --wiki # build agent-crawlable wiki (index.md + one article per community)
/graphify <path> --obsidian --obsidian-dir ~/vaults/my-project # write vault to custom path (e.g. existing vault)
/graphify add <url> # fetch URL, save to ./raw, update graph
/graphify add <url> --author "Name" # tag who wrote it
/graphify add <url> --contributor "Name" # tag who added it to the corpus
/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 "AuthModule" "Database" # shortest path between two concepts
/graphify explain "SwinTransformer" # plain-language explanation of a node
```
## What graphify is for
Drop any folder of code, docs, papers, images, or video into graphify and get a queryable knowledge graph. Persistent across sessions, honest audit trail (EXTRACTED/INFERRED/AMBIGUOUS), community detection surfaces cross-document connections you wouldn't think to ask about.
## What You Must Do When Invoked
If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
**Fast path — existing graph:** Before doing anything else, check whether `graphify-out/graph.json` exists. The expected location is `graphify-out/graph.json` relative to the **current working directory** (i.e. the project root where you are running commands). If it exists AND the user's request is a natural-language question about the codebase (e.g. "How does X work?", "What calls Y?", "Trace the data flow through Z") and NOT an explicit rebuild command (`--update`, `--cluster-only`, or a bare path/URL that implies fresh extraction): **skip Steps 1–5 entirely and jump straight to `## For /graphify query`.** Run `graphify query "<question>"` immediately. Do not run detect. Do not check corpus size. Do not ask the user to narrow. The graph is already built — use it.
If no path was given, use `.` (current directory). Do not ask the user for a path.
If the path argument starts with `https://github.com/` or `http://github.com/`, treat it as a GitHub URL - run Step 0 before anything else, then continue with the resolved local path.
Follow these steps in order. Do not skip steps.
### Step 0 - GitHub repos and multi-path merge (only if a URL or several paths)
Only when the path is one or more `https://github.com/...` URLs, or several local subfolders to merge. See `references/github-and-merge.md` for the clone, cross-repo merge, and monorepo flow, then continue with the resolved local path. A plain local path skips this step.
### Step 1 - Ensure graphify is installed
```bash
# Detect the correct Python interpreter (handles uv tool, pipx, venv, system installs)
PYTHON=""
GRAPHIFY_BIN=$(which graphify 2>/dev/null)
# 1. uv tool installs — most reliable on modern Mac/Linux
if [ -z "$PYTHON" ] && command -v uv >/dev/null 2>&1; then
_UV_PY=$(uv tool run --from graphifyy python -c "import sys; print(sys.executable)" 2>/dev/null)
if [ -n "$_UV_PY" ]; then PYTHON="$_UV_PY"; fi
fi
# 2. Read shebang from graphify binary (pipx and direct pip installs)
if [ -z "$PYTHON" ] && [ -n "$GRAPHIFY_BIN" ]; then
_SHEBANG=$(head -1 "$GRAPHIFY_BIN" | tr -d '#!')
case "$_SHEBANG" in
*[!a-zA-Z0-9/_.@-]*) ;;
*) "$_SHEBANG" -c "import graphify" 2>/dev/null && PYTHON="$_SHEBANG" ;;
esac
fi
# 3. Fall back to python3
if [ -z "$PYTHON" ]; then PYTHON="python3"; fi
if ! "$PYTHON" -c "import graphify" 2>/dev/null; then
if command -v uv >/dev/null 2>&1; then
uv tool install --upgrade graphifyy -q 2>&1 | tail -3
_UV_PY=$(uv tool run --from graphifyy python -c "import sys; print(sys.executable)" 2>/dev/null)
if [ -n "$_UV_PY" ]; then PYTHON="$_UV_PY"; fi
else
"$PYTHON" -m pip install graphifyy -q 2>/dev/null \
|| "$PYTHON" -m pip install graphifyy -q --break-system-packages 2>&1 | tail -3
fi
fi
# Write interpreter path for all subsequent steps (persists across invocations)
mkdir -p graphify-out
"$PYTHON" -c "import sys; open('graphify-out/.graphify_python', 'w', encoding='utf-8').write(sys.executable)"
# Save scan root so `graphify update` (no args) knows where to look next time
echo "$(cd INPUT_PATH && pwd)" > graphify-out/.graphify_root
```
If the import succeeds, print nothing and move straight to Step 2.
**In every subsequent bash block, replace `python3` with `$(cat graphify-out/.graphify_python)` to use the correct interpreter.**
### Step 2 - Detect files
```bash
$(cat graphify-out/.graphify_python) -c "
import json
from graphify.detect import detect
from pathlib import Path
result = detect(Path('INPUT_PATH'))
print(json.dumps(result, ensure_ascii=False))
" > graphify-out/.graphify_detect.json
```
Replace INPUT_PATH with the actual path the user provided. Do NOT cat or print the JSON - read it silently and present a clean summary instead:
```
Corpus: X files · ~Y words
code: N files (.py .ts .go ...)
docs: N files (.md .txt ...)From rylsherdamz-rgb/stellar-forge, MIT.
More from rylsherdamz-rgb/stellar-forge
- 0.606score
stellar-forge
rylsherdamz-rgb
Eval-driven coding harness for building production Stellar dApps.
SkillBFreshness: B★ 17Claude Code +9 - 0.606score
ui-ux-pro-max
rylsherdamz-rgb
UI/UX design intelligence for web and mobile.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
stellar-mcp
rylsherdamz-rgb
MCP (Model Context Protocol) tools for Stellar development.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
standards
rylsherdamz-rgb
Stellar Ecosystem Proposals (SEPs), Core Advancement Proposals (CAPs), and ecosystem references.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
zk-proofs
rylsherdamz-rgb
Zero-knowledge proofs and privacy patterns on Stellar.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
assets
rylsherdamz-rgb
Stellar classic assets, trustlines, and Stellar Asset Contract (SAC) bridge to smart contracts.
SkillBFreshness: B★ 17Claude Code +9 - 0.598score
dapp
rylsherdamz-rgb
Stellar dApp / frontend development.
SkillBFreshness: B★ 17Claude Code +9 - 0.598score
agentic-payments
rylsherdamz-rgb
Agentic and machine-to-machine payments on Stellar.
SkillBFreshness: B★ 17Claude Code +9 - 0.598score
data
rylsherdamz-rgb
Querying Stellar chain data via Stellar SDK (preferred), Stellar RPC, and Horizon (legacy).
SkillBFreshness: B★ 17Claude Code +9 - 0.598score
smart-contracts
rylsherdamz-rgb
Stellar smart contract development (Rust, soroban-sdk).
SkillBFreshness: B★ 17Claude Code +9 - 0.594score
frontend-design
rylsherdamz-rgb
Create distinctive, production-grade Stellar dApp UI.
SkillBFreshness: B★ 17Claude Code +9 - 0.507score
design
claudekit
Comprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini AI), corporate identity program (50 deliverables…
SkillBFreshness: B★ 17Claude Code +9
Signals
- Stars
- 17
- Forks
- 2
- Open issues
- 8
- Last commit (this folder)
- Jul 29, 2026 (3 months ago)
- Last release
- Jul 30, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/rylsherdamz-rgb/stellar-forge
- Website
- stellarforge.xyz
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from rylsherdamz-rgb
- 0.606score
ui-ux-pro-max
rylsherdamz-rgb
UI/UX design intelligence for web and mobile.
SkillBFreshness: B★ 17Claude Code +9 - 0.606score
stellar-forge
rylsherdamz-rgb
Eval-driven coding harness for building production Stellar dApps.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
assets
rylsherdamz-rgb
Stellar classic assets, trustlines, and Stellar Asset Contract (SAC) bridge to smart contracts.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
standards
rylsherdamz-rgb
Stellar Ecosystem Proposals (SEPs), Core Advancement Proposals (CAPs), and ecosystem references.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
stellar-mcp
rylsherdamz-rgb
MCP (Model Context Protocol) tools for Stellar development.
SkillBFreshness: B★ 17Claude Code +9 - 0.601score
zk-proofs
rylsherdamz-rgb
Zero-knowledge proofs and privacy patterns on Stellar.
SkillBFreshness: B★ 17Claude Code +9
Cite this page
graphify skill. Agent Mart. https://agentmart.dev/skills/rylsherdamz-rgb-graphify (last updated 2026-10-24)