setup

An interactive setup workflow that detects a codebase, configures a knowledge-base connection, creates project-specific instructions, optionally adds documents, and checks the result. A knowledge base stores documents for later lookup.

In plain words
What is it for?
Use it to try a local example knowledge base or connect one to a real codebase, configure the agent, add documents, and verify access.
Why use it?
It guides a new user from an unconfigured project to a working setup without requiring them to know each configuration step.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/wrannaman/agentic-engineering/setup
Any agent
npx skills add wrannaman/agentic-engineering --skill setup
Clone the repo
git clone --depth 1 https://github.com/wrannaman/agentic-engineering

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,489 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00033 $0.03489
Opus 5 $0.00016 $0.01744
Sonnet 5 $0.00007 $0.00698
Haiku 4.5 $0.00003 $0.00349

Measured yesterday against content hash 45b22edc7654, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

setup scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Verify: `curl -H "Authorization: Bearer $TOKEN" $URL/health`
skills/core/setup/SKILL.md · 435 lines

How it starts

The opening of the file, as written. The whole thing — 435 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Setup

From zero to working agentic engineering in one session.

Walk a new user through the entire stack: detect their codebase, deploy or connect to a KB server, write project-specific configuration, optionally seed the KB, and verify it all works.

The agent does the work. The user answers questions and confirms.

Process

Step 0: Quick or Full?

Before anything else, ask ONE question:

What are you looking to do?

  1. Just try it out — get a local KB running with the example docs in 2 minutes
  2. Set this up for real — connect to my codebase, configure everything properly

If "just try it out" (the quick path):

Skip everything and do this:

cd apps/kb-server
python -m venv .venv && source .venv/bin/activate
pip install -e .
REPOS="kb:../../examples/seed-kb" python -m src.server &

Then configure the agent to connect:

# For Claude Code:
claude mcp add --transport http kb http://localhost:8080/mcp

Done. Say:

KB server running at http://localhost:8080 with 5 example docs.
Try: list_documents() to see what's in the KB.

When you're ready to add your own docs, just drop markdown files into
examples/seed-kb/ (or any folder) and hit localhost:8080/api/sync.

Run /setup again and pick option 2 when you want the full configuration.

That's the entire quick path. No more questions. They're up and running.

If "set this up for real": Continue to Step 1.

Step 1: Where Am I?

First, figure out if the user is in the agentic-eng repo or in their own project:

# Check if we're in the agentic-eng repo itself
ls apps/kb-server/src/server.py 2>/dev/null && ls skills/core/plan/SKILL.md 2>/dev/null

If we're in the agentic-eng repo:

They just cloned it. They need to:

  1. Start the KB server (done in Step 0 quick path, or Step 2 full path)
  2. Install skills into their agent
  3. Then go to their actual project and configure it
It looks like you're in the agentic-eng repo itself — not a project you want to configure.

Let's get you set up:
  1. ✅ Start the KB server (done — or we'll do it in Step 2)
  2. Install skills: cd skills && ./install.sh
  3. Go to your project: cd /path/to/your/project
  4. Run /setup again from there to configure your project

What's the path to the project you want to configure?

Read the full file on GitHub · 435 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 435 lines · 33 tokens per session scan A 45b22edc7654

Subscribe to this mod's changes

setup is a skill published in the GitHub repository wrannaman/agentic-engineering (2 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 3,489 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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