Skip to content
Agentmart
Submit a tool

ddp-onboard

Initialize a dealership's DDP repository from completed discovery facts and take it through the synthetic implementation and smoke gate.

Skill by Profreshor

IndexedMIT
Write a review

Chalk Labs

Need help deploying ddp-onboard?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

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/profreshor-ddp-onboard

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.

We use your email only for this newsletter. Privacy

About

Initialize a dealership's DDP repository from completed discovery facts and take it through the synthetic implementation and smoke gate.

No 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/ddp-onboard

What's inside

Skill name
ddp-onboard
Description
Initialize a dealership's DDP repository from completed discovery facts and take it through the synthetic implementation and smoke gate.
License
MIT
Instructions
11 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

Use this skill when setting up a dealership's own DDP repository from a completed discovery document the dealership has reviewed.

1. Read [discovery](../../docs/discovery.md), [Architecture §21](../../ARCHITECTURE.md#21-onboarding-discovery-document-to-running-system), and both parts of completed discovery: the narrative and structured YAML. Keep credentials out of the document and require `development_data: synthetic`.
2. Run the documented dry run and initialization with `--template <checkout>`, then verify the generated source revision as described in [initialization](../../docs/discovery.md#initialize-locally). Complete [Git setup](../../docs/discovery.md#start-the-projects-git-history) before implementation so changed-file checks have a baseline and doctor can inspect template provenance.
3. Use the standard development container and its private Postgres service. Run `make setup`, `make build` and `build/ddp validate` in the new project checkout. Outside that container, establish a dedicated disposable Postgres instance and set `DDP_DEV_DATABASE_URL` and `TEST_DATABASE_URL` explicitly before database work. A new database on a shared cluster does not isolate roles. Use the development runtime or smoke gate’s component connections; reserve `ddp provision` for production bootstrap on its dedicated cluster.
4. Implement the declared synthetic path using the existing [Python job](../../docs/python-jobs.md), [model](../../docs/models.md), [route](../../docs/client-routes.md), and [custom page](../../docs/custom-pages.md) guidance. Account for every requested discovery behavior, including source semantics, schedules and output fields. Validate source values before committing writes. Add focused checks for requirements the smoke path does not cover; inspect failure state before retrying so recovery cannot hide damage. A passing smoke alone does not prove discovery is satisfied.
5. During edits, run `build/ddp check --changed --json`. Before review, run `build/ddp check --json`, then run `build/ddp smoke --json` explicitly when the full gate does not already execute the smoke path. For standalone migrations or jobs, verify `DATABASE_URL` and `JOB_DATABASE_URL` name the owned disposable database for standalone database commands, as documented in [the runtime commands](../../docs/commands.md#runtime-commands). The discovery-only project is expected to fail smoke until an ingest-to-page path exists; finish only when the path passes.

The production installer, Cloudflare access, backup/restore, and deployment gates remain separate. Do not claim production readiness from local initialization.

From Profreshor/Dealership-Data-Platform, MIT.

More from Profreshor/Dealership-Data-Platform

Signals

Stars
0
Forks
0
Open issues
0
Last commit (this folder)
Oct 9, 2026 (22 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from Profreshor

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get ddp-onboard running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying ddp-onboard?

CallGet help
Cite this page

ddp-onboard skill. Agent Mart. https://agentmart.dev/skills/profreshor-ddp-onboard (last updated 2026-10-24)