Agent skill

Graphify

by iPythoning in iPythoning/b2b-sdr-agent-template

Knowledge graph engine for B2B sales intelligence. An agent skill from iPythoning/b2b-sdr-agent-template.

Install Graphify

skills CLI

$ npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a claude-code

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

GitHub CLI

$ gh skill install iPythoning/b2b-sdr-agent-template graphify --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/iPythoning/b2b-sdr-agent-template.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/graphify .claude/skills/graphify && 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/

Paste into Claude Code

Install the "graphify" agent skill from https://github.com/iPythoning/b2b-sdr-agent-template/tree/main/skills/graphify into .claude/skills/graphify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphify", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/iPythoning/b2b-sdr-agent-template/tree/main/skills/graphify

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install iPythoning/b2b-sdr-agent-template graphify --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/iPythoning/b2b-sdr-agent-template.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/graphify .agents/skills/graphify && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "graphify" agent skill from https://github.com/iPythoning/b2b-sdr-agent-template/tree/main/skills/graphify into .agents/skills/graphify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphify", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install iPythoning/b2b-sdr-agent-template graphify --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/iPythoning/b2b-sdr-agent-template.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/graphify .cursor/skills/graphify && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "graphify" agent skill from https://github.com/iPythoning/b2b-sdr-agent-template/tree/main/skills/graphify into .cursor/skills/graphify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphify", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/iPythoning/b2b-sdr-agent-template.git --path skills/graphify

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install iPythoning/b2b-sdr-agent-template graphify --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/iPythoning/b2b-sdr-agent-template.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/graphify .gemini/skills/graphify && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "graphify" agent skill from https://github.com/iPythoning/b2b-sdr-agent-template/tree/main/skills/graphify into .gemini/skills/graphify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphify", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install iPythoning/b2b-sdr-agent-template graphify

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/iPythoning/b2b-sdr-agent-template.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/graphify .github/skills/graphify && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "graphify" agent skill from https://github.com/iPythoning/b2b-sdr-agent-template/tree/main/skills/graphify into .github/skills/graphify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphify", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install iPythoning/b2b-sdr-agent-template graphify --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/iPythoning/b2b-sdr-agent-template.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/graphify .opencode/skills/graphify && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "graphify" agent skill from https://github.com/iPythoning/b2b-sdr-agent-template/tree/main/skills/graphify into .opencode/skills/graphify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphify", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: graphify
GitHub stars: 190
Token cost: ~1.5k tokens
SKILL.md length: 459 words
Files: 1
Skills in repo: 4
Repo updated: Sep 29, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Knowledge graph engine for B2B sales intelligence. An agent skill from iPythoning/b2b-sdr-agent-template.

Works in 3 steps: Product Catalog Graph → Customer Intelligence Graph → Market Research Graph
Tasks that involve Knowledge graphs
SKILL.md covers Triggers, Prerequisites, Use Cases and Graph Query (runtime), plus 4 more sections
Calls python3 and pip

What it does

Graphify is an agent skill from iPythoning/b2b-sdr-agent-template. Knowledge graph engine for B2B sales intelligence. Builds queryable graphs from product catalogs, customer conversations, and market research. Powered by graphify.

Its SKILL.md is about 1.5k 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 Marketing & SEO, covering Knowledge graphs and Market research. The repository describes itself as: Open-source AI SDR template for B2B export. 10-stage sales pipeline, 10 cron jobs, 4-engine memory, multi-channel (WhatsApp+Telegram+Email). Built on OpenClaw. The licence is MIT.

When your agent uses it

Tasks that involve Knowledge graphs
Tasks that involve Market research

Example prompts

“/graphify”

Requirements

Python 3

Workflow steps

3 steps, taken from the step headings in SKILL.md.

Product Catalog Graph
Customer Intelligence Graph
Market Research Graph

What it can do on your machine

Read from SKILL.md and the folder at commit 6131928. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python3
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- github.com
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

Graphify loads about 1.5k tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 459 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~43
When it runs · the whole SKILL.md, loaded when a task matches: ~1.5k

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 passed

The automated check found no risky patterns in SKILL.md.

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 iPythoning/b2b-sdr-agent-template at commit 6131928, republished under its MIT licence (© iPythoning). 459 words, ~1,530 tokens.

Download SKILL.mdSave it as .claude/skills/graphify/SKILL.md (or your agent's skills folder).

name: graphify
description: Knowledge graph engine for B2B sales intelligence. Builds queryable graphs from product catalogs, customer conversations, and market research. Powered by graphify.

Graphify — Sales Intelligence Knowledge Graph

Build knowledge graphs from your product catalog, customer conversations, and market research to surface hidden connections, cross-sell opportunities, and competitive insights.

Based on graphify — adapted for B2B SDR context.

Triggers

Manual: "Build a knowledge graph of our products"
Manual: "Map customer relationships"
Manual: "Analyze competitive landscape"
Cron (optional): Weekly rebuild after lead-discovery updates

Prerequisites

bash

# Ensure graphify is installed
python3 -c "import graphify" 2>/dev/null || pip install graphifyy -q --break-system-packages 2>&1 | tail -3

Use Cases

1. Product Catalog Graph

Build a graph from product-kb/ to understand product relationships, shared certifications, overlapping target markets, and cross-sell paths.

When to use: Before quotation, during BANT qualification, when customer asks about related products.

bash

python3 -c "
import json
from graphify.extract import collect_files, extract
from graphify.build import build
from graphify.cluster import cluster, score_all
from graphify.analyze import god_nodes, surprising_connections
from pathlib import Path

# Extract from product catalog
files = collect_files(Path('product-kb'))
ast_result = extract(files)

# Build and analyze
G = build([ast_result])
communities, labels = cluster(G)
cohesion = score_all(G, communities)

gods = god_nodes(G, top_n=5)
surprises = surprising_connections(G, communities, top_n=5)

print('=== Core Products (God Nodes) ===')
for g in gods:
    print(f'  {g[\"label\"]} — {g[\"edges\"]} connections')

print('=== Surprising Connections ===')
for s in surprises:
    print(f'  {s[\"source\"]} ↔ {s[\"target\"]} [{s[\"confidence\"]}]')
"

Sales actions from graph insights:

God nodes = your anchor products → lead with these in cold outreach
Surprising connections = non-obvious cross-sell paths → "customers who buy X often need Y"
Communities = product families → bundle pricing opportunities

2. Customer Intelligence Graph

Build a graph from conversation histories and CRM data to map customer relationships, identify buying patterns, and find warm introduction paths.

Input sources:

ChromaDB conversation history (chroma:recall)
CRM records (Google Sheets)
Supermemory research notes (memory:search)

What to extract (semantic, not AST):

Companies → employees (decision makers, influencers)
Companies → products they bought or inquired about
Companies → companies (same industry, same region, competitors)
People → people (referrals, shared contacts)
Deals → products, timelines, objections

Sales actions from graph insights:

Cluster customers by behavior → tailor nurture campaigns per cluster
Find bridge nodes (customers who connect segments) → referral candidates
Detect isolated nodes (customers with no follow-up) → stalled lead recovery

3. Market Research Graph

Build a graph from lead-discovery research, competitor intel, and market signals stored in Supermemory.

What to extract:

Competitors → products, pricing, markets
Markets → trends, regulations, trade shows
Customers → competitors they also buy from
Regions → seasonal demand patterns

Sales actions from graph insights:

Surprising connections between markets → expansion opportunities
Competitor clusters → differentiation strategy
Market god nodes → priority regions for lead-discovery rotation

Show full SKILL.md (160 more words)Show less

Graph Query (runtime)

After building a graph, query it for specific sales intelligence:

bash

# BFS — broad context around a topic
python3 -m graphify query "hydraulic excavator certification" --budget 1500

# DFS — trace a specific relationship chain
python3 -m graphify query "Dubai customer fleet" --dfs --budget 1000

Use before:

Responding to product questions → query product graph for specs and relationships
Preparing quotations → find cross-sell opportunities in graph
Cold outreach → understand prospect's market context from research graph

Graph Export

bash

python3 -c "
from graphify.export import to_json, to_html
from graphify.build import build_from_json
from pathlib import Path
import json

data = json.loads(Path('graphify-out/graph.json').read_text())
G = build_from_json(data)

# Interactive HTML for owner dashboard
to_html(G, Path('graphify-out/graph.html'))

# JSON for programmatic access
to_json(G, Path('graphify-out/graph.json'))
"

HTML: Interactive vis.js graph — share with owner for pipeline visibility
JSON: Machine-readable — feed into reporting or CRM enrichment
Report: graphify-out/GRAPH_REPORT.md — god nodes, communities, knowledge gaps

Output Format (report to owner)

Product Knowledge Graph:
- X nodes · Y edges · Z communities
- Core products: [god nodes list]
- Cross-sell opportunities: [surprising connections]
- Knowledge gaps: [isolated products with missing specs]

Recommendation: Update product-kb for [gap products] to improve graph coverage.

Integration with Other Skills

Skill	How Graphify Helps
lead-discovery	Query market graph before searching → better targeting
quotation-generator	Query product graph → include related products in quote
chroma-memory	Feed conversation data → build customer intelligence graph
supermemory	Feed research notes → build market research graph
sdr-humanizer	Graph context → more relevant, personalized conversations

Rebuild Strategy

Product graph: Rebuild when product-kb/ changes (new products, updated specs)
Customer graph: Rebuild weekly from ChromaDB + CRM snapshots
Market graph: Rebuild after lead-discovery runs (daily 10:00 output)

Store graphs in graphify-out/ — survives across sessions, queryable anytime.

Files

Just SKILL.md in skills/graphify of iPythoning/b2b-sdr-agent-template.

Open the folder on GitHubat commit 6131928

Compare with similar skills

Graphify 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.

Graphify compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Graphify this skilliPythoning/b2b-sdr-agent-template	190	—	~1.5k	Automated safety check: Pass	MIT	8 days ago
Customer ResearchNexus-JPF/note-companion	869	5 repos	~3.2k	Automated safety check: Pass	MIT	4 days ago
Google Maps Reviews API Skillbrowser-act/skills	6.1k	1 repos	~1.4k	Automated safety check: Pass	MIT	1 mo ago
Entity Registryaaron-he-zhu/aaron-marketing-skills	2.9k	1 repos	~2.3k	Automated safety check: Pass	Apache-2.0	today
56 Retargeting Plan Globalminhnv0807/ai-business-skills	608	—	~2.8k	Automated safety check: Pass	MIT	25 days ago
Chief Customer Officer Advisorborghei/Claude-Skills	874	—	~2.1k	Automated safety check: Pass	MIT	yesterday

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Questions about Graphify

What does Graphify do?

Knowledge graph engine for B2B sales intelligence. An agent skill from iPythoning/b2b-sdr-agent-template. Graphify is an agent skill from iPythoning/b2b-sdr-agent-template. Knowledge graph engine for B2B sales intelligence.

When should I use Graphify?

Graphify fits situations like: tasks that involve Knowledge graphs; tasks that involve Market research.

How do I install Graphify in Claude Code?

Run `npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a claude-code`. Or copy the skill folder (skills/graphify in iPythoning/b2b-sdr-agent-template) into .claude/skills/graphify in your project. Claude Code loads it when a task matches its description.

How do I install Graphify in Codex?

Run `npx skills add iPythoning/b2b-sdr-agent-template --skill graphify -a codex`. Or copy the skill folder (skills/graphify in iPythoning/b2b-sdr-agent-template) into .agents/skills/graphify in your project. Codex loads it when a task matches its description.

Can I use Graphify 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 iPythoning/b2b-sdr-agent-template --skill graphify -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/graphify, .gemini/skills/graphify, .github/skills/graphify and .opencode/skills/graphify in your project.

What does Graphify need to run?

Going by SKILL.md and its folder, Graphify needs the command-line tools its instructions call (python3 and pip). Our summary lists: Python 3.

Does Graphify access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Graphify safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Graphify use?

Graphify is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Graphify use?

About 1.5k tokens (SKILL.md is roughly 6.1k 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 Graphify?

Skills that share tags, products or a category with Graphify: Customer Research (Nexus-JPF/note-companion, 869 stars), Google Maps Reviews API Skill (browser-act/skills, 6.1k stars), Entity Registry (aaron-he-zhu/aaron-marketing-skills, 2.9k stars) and 56 Retargeting Plan Global (minhnv0807/ai-business-skills, 608 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Graphify?

iPythoning (a GitHub user) maintains it in iPythoning/b2b-sdr-agent-template, which has 190 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on September 29, 2026.

Source: iPythoning/b2b-sdr-agent-template on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Graphify

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Graphify — Sales Intelligence Knowledge Graph

Triggers

Prerequisites

Use Cases

1. Product Catalog Graph

2. Customer Intelligence Graph

3. Market Research Graph

Graph Query (runtime)

Graph Export

Output Format (report to owner)

Integration with Other Skills

Rebuild Strategy

Files

Compare with similar skills

Similar skills

More from iPythoning/b2b-sdr-agent-template

Related

Questions about Graphify