PromptDrive
Organize, share, and collaborate on AI prompts for ChatGPT, Claude, and Gemini in one team workspace
The core loop, save a prompt, file it in a folder, tag it, find it, fill in variables, copy it into a chat, is a small CRUD app around one SQLite table and ships in one sitting. What the subscription actually sells is the multiplayer part: shared folders with permissions, comments that let a team iterate on a prompt, and a Chrome extension that surfaces the library inside ChatGPT, Claude, and Gemini.
Build verification: not recorded. How we judge buildability
What you give up
- team sharing, comments, and permissions
- the Chrome extension inside ChatGPT, Claude, and Gemini
- running prompts against models from the same workspace with your own API keys
- public share links with unique URLs
- someone else's servers & support
Why people still pay
Teams pay for the shared workspace: private folders someone else maintains, comments that turn a prompt into a living document, permissions, and an extension that follows the team into whichever chat AI they use. A local library covers one person fine; the per-seat fee is really about keeping five people on the same page.
Your build guide
The stack, security requirements, and agent rules for a focused replacement.
Before you start
- A supported Node release, a writable local data directory and a separate backup location. Bind to localhost; remote use requires authentication and HTTPS first.
- Implementation components: Node.js, TypeScript and Express with server-rendered HTML and small browser modules. SQLite through better-sqlite3 with migrations, prepared statements and a single background worker.
- Scope boundary: team sharing, comments, and permissions; the Chrome extension inside ChatGPT, Claude, and Gemini
Use these project rules and optional skill references alongside the prompt. Review each skill before adding it to your agent; the AGENTS.md export includes the same guidance.
Optional external skill: web-design-guidelines — Review web interfaces for accessibility, keyboard focus, forms, navigation and interaction quality. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.
Optional external skill: sharp-edges — Review security-sensitive APIs and configuration for dangerous defaults and easy-to-misuse interfaces. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.
Project rule — data model: prompt templates, folders, tags, variable definitions, immutable versions and filled previews
Project rule — preserve this invariant: Template substitution cannot execute code; missing variables block final copy or remain visibly unresolved, and secrets are not stored as sample values.
Project rule — acceptance evidence: Fill a value containing braces and preserve it literally; editing a shared template creates a revision without changing earlier saved previews.
Implementation plan
Phase 1
Scope and fixtures. Implement this bounded workflow: Save reusable prompts, search them instantly and generate a form for declared template variables. Preview the filled text and copy it to the clipboard without sending it to any model by default. Record prerequisites, select representative user-owned fixtures and document the unsupported features: team sharing, comments, and permissions; the Chrome extension inside ChatGPT, Claude, and Gemini
Phase 2
Durable model. Model prompt templates, folders, tags, variable definitions, immutable versions and filled previews Add migrations or a versioned document format, explicit validation, stable IDs and a visible import-error report. Preserve this rule: Template substitution cannot execute code; missing variables block final copy or remain visibly unresolved, and secrets are not stored as sample values.
Phase 3
Complete the first useful path. Implement the workflow's input, review and output interface, with clear controls and explicit empty/error states. Use short SQLite transactions and persist job state before starting work. Give retries stable operation IDs; report incomplete or unknown results instead of silently repeating them.
Phase 4
Permissions and integration failure. Reject unexpected origins and unbounded request bodies even on localhost. Keep credentials outside the database export and redact sensitive text from logs. Request integration credentials and permissions only for the enabled feature; show a disconnected state instead of mock results.
Phase 5
Portable handoff. Use a consistent SQLite backup and an attachment manifest. Export portable JSON/CSV, then restore to a new directory without overwriting the original data. Include setup, operating limits, fixture walkthrough and shutdown/restart instructions in the README.
Phase 6
Acceptance scenarios. Fill a value containing braces and preserve it literally; editing a shared template creates a revision without changing earlier saved previews. Repeat the workflow after restart and with a denied permission or unavailable dependency; show recoverable failure rather than a success placeholder.
WORKING SLICE Save reusable prompts, search them instantly and generate a form for declared template variables. Preview the filled text and copy it to the clipboard without sending it to any model by default. Build this scoped PromptDrive-inspired workflow with a documented data model and visible failure states. Architecture - Node.js, TypeScript and Express with server-rendered HTML and small browser modules. - SQLite through better-sqlite3 with migrations, prepared statements and a single background worker. Prerequisites and limits A supported Node release, a writable local data directory and a separate backup location. Bind to localhost; remote use requires authentication and HTTPS first. Outside this release: team sharing, comments, and permissions; the Chrome extension inside ChatGPT, Claude, and Gemini Data model and correctness prompt templates, folders, tags, variable definitions, immutable versions and filled previews Invariant: Template substitution cannot execute code; missing variables block final copy or remain visibly unresolved, and secrets are not stored as sample values. Use short SQLite transactions and persist job state before starting work. Give retries stable operation IDs; report incomplete or unknown results instead of silently repeating them. Security and privacy Reject unexpected origins and unbounded request bodies even on localhost. Keep credentials outside the database export and redact sensitive text from logs. Recovery and export Use a consistent SQLite backup and an attachment manifest. Export portable JSON/CSV, then restore to a new directory without overwriting the original data. Implementation order 1. Phase 1 — Scope and fixtures. Implement this bounded workflow: Save reusable prompts, search them instantly and generate a form for declared template variables. Preview the filled text and copy it to the clipboard without sending it to any model by default. Record prerequisites, select representative user-owned fixtures and document the unsupported features: team sharing, comments, and permissions; the Chrome extension inside ChatGPT, Claude, and Gemini 2. Phase 2 — Durable model. Model prompt templates, folders, tags, variable definitions, immutable versions and filled previews Add migrations or a versioned document format, explicit validation, stable IDs and a visible import-error report. Preserve this rule: Template substitution cannot execute code; missing variables block final copy or remain visibly unresolved, and secrets are not stored as sample values. 3. Phase 3 — Complete the first useful path. Implement the workflow's input, review and output interface, with clear controls and explicit empty/error states. Use short SQLite transactions and persist job state before starting work. Give retries stable operation IDs; report incomplete or unknown results instead of silently repeating them. 4. Phase 4 — Permissions and integration failure. Reject unexpected origins and unbounded request bodies even on localhost. Keep credentials outside the database export and redact sensitive text from logs. Request integration credentials and permissions only for the enabled feature; show a disconnected state instead of mock results. 5. Phase 5 — Portable handoff. Use a consistent SQLite backup and an attachment manifest. Export portable JSON/CSV, then restore to a new directory without overwriting the original data. Include setup, operating limits, fixture walkthrough and shutdown/restart instructions in the README. 6. Phase 6 — Acceptance scenarios. Fill a value containing braces and preserve it literally; editing a shared template creates a revision without changing earlier saved previews. Repeat the workflow after restart and with a denied permission or unavailable dependency; show recoverable failure rather than a success placeholder. Acceptance Fill a value containing braces and preserve it literally; editing a shared template creates a revision without changing earlier saved previews. Use real source data or clearly labeled fixtures. Explain unsupported input and provider failures; do not fabricate analytics, delivery receipts, accuracy claims or security guarantees. Optional agent guidance Optional external skill: [web-design-guidelines](https://github.com/vercel-labs/agent-skills/blob/main/skills/web-design-guidelines/SKILL.md) — Review web interfaces for accessibility, keyboard focus, forms, navigation and interaction quality. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission. Optional external skill: [sharp-edges](https://github.com/trailofbits/skills/blob/main/plugins/sharp-edges/skills/sharp-edges/SKILL.md) — Review security-sensitive APIs and configuration for dangerous defaults and easy-to-misuse interfaces. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission. Project rule — data model: prompt templates, folders, tags, variable definitions, immutable versions and filled previews Project rule — preserve this invariant: Template substitution cannot execute code; missing variables block final copy or remain visibly unresolved, and secrets are not stored as sample values. Project rule — acceptance evidence: Fill a value containing braces and preserve it literally; editing a shared template creates a revision without changing earlier saved previews.
$ open in your agent (prompt prefilled, you press enter), copy the prompt or copy or download AGENTS.md
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PromptDrive pricing
team$5/mo per seat · monthly per user · $60/yr
free tierThe free Personal plan includes unlimited prompts, public sharing links, and the Chrome extension.
pricing source checked 2026-08-10 · pricing source ↗
Questions about PromptDrive
Can you build your own PromptDrive with AI?
The verdict is yes for the scoped workflow. The core loop, save a prompt, file it in a folder, tag it, find it, fill in variables, copy it into a chat, is a small CRUD app around one SQLite table and ships in one sitting. What the subscription actually sells is the multiplayer part: shared folders with permissions, comments that let a team iterate on a prompt, and a Chrome extension that surfaces the library inside ChatGPT, Claude, and Gemini.
What does the PromptDrive build prompt cover?
The prompt starts with this scope: Save reusable prompts, search them instantly and generate a form for declared template variables. Preview the filled text and copy it to the clipboard without sending it to any model by default. Full-product capabilities excluded from the comparison include: team sharing, comments, and permissions; the Chrome extension inside ChatGPT, Claude, and Gemini; running prompts against models from the same workspace with your own API keys. Follow the implementation plan and its prerequisites before expanding the build.
How do I use the prompt, AGENTS.md and agent skills?
Start with the PromptDrive prerequisites and stack, then copy the prompt into your coding agent. Save the project rules as AGENTS.md in the project root. Linked skills are optional packages or source instructions for specific tasks; review their current contents and install only those matching the chosen stack. A skill does not supply API credentials or verify the finished app.
How long will this PromptDrive project take?
The catalogue estimate is one sitting for the limited scope. Setup, integration approvals, debugging, deployment and ongoing maintenance can add time. This is an estimate, not a delivery guarantee.
What would I give up by replacing PromptDrive?
team sharing, comments, and permissions; the Chrome extension inside ChatGPT, Claude, and Gemini; running prompts against models from the same workspace with your own API keys; public share links with unique URLs; someone else's servers & support. Teams pay for the shared workspace: private folders someone else maintains, comments that turn a prompt into a living document, permissions, and an extension that follows the team into whichever chat AI they use. A local library covers one person fine; the per-seat fee is really about keeping five people on the same page.
What price is this guide comparing against?
The recorded Team plan is $5/mo per seat (monthly per user), checked 2026-08-10. Check the linked pricing source before buying. Building your own also has hosting, API and maintenance costs; the recorded amount is not a guaranteed saving.
What can I use instead of building PromptDrive?
Langfuse: An open source LLM engineering platform whose prompt management gives a team versioned, shared prompts, if you are happy running the whole stack for that one feature. Check each option's license, hosting needs and feature limits.