Use as stage 2 of the Butterbase journey, after journey-idea has written 01-idea.md. Translates the idea + capability map into a concrete Butterbase plan — tables (with columns/types/RLS shape), auth providers, function list (name + trigger), storage buckets, AI/RAG/realtime/durable usage, and the chosen frontend stack. In hackathon mode, ruthlessly cuts scope into a "ship now" vs "post-hackathon" split. Produces docs/butterbase/02-plan.md.
npx skills add https://github.com/butterbase-ai/butterbase-skills --skill journey-plan
Stage 2 of the guided journey. Turn the idea brief into an actionable Butterbase plan.
journey when current_stage: plan./butterbase-skills:plan.docs/butterbase/01-idea.md (must exist — if absent, bounce back to journey-idea).docs/butterbase/00-state.md (for hackathon_mode, hackathon_deadline).When the plan needs email, messaging, calendar, CRM, docs, or project-management integration:
butterbase-skills:integrations and call manage_integrations action: "list_available" to see what Composio covers for this app.When the plan needs payments:
butterbase-skills:payments.manage_billing unless the user's region forces a fallback (see the payments skill).Work through these sections in order. After each section, write the result to 02-plan.md before moving on. One question at a time per the spec's questioning discipline.
"Tables I'm seeing: users, orders, items. Missing any?" Then for each table: "<table>.<column>: should this be a uuid / text / int / timestamp / enum?". Confirm primary keys, foreign keys, indexes that are obvious (foreign-key columns)."Can user A see user B's <table> rows? ① no, strict isolation ② yes, public-read ③ only shared via explicit grant." Decide policy shape. In hackathon mode, prefer option ① and recommend manage_rls action: create_user_isolation."OAuth providers: ① Google only ② Google + GitHub ③ email/password too ④ none (anonymous app)." Also ask: "Need a demo / judge account seeded? (hackathon mode only)"."<name>: trigger = HTTP / cron / WebSocket? If cron: schedule? If HTTP: idempotency needed?"."Which objects (avatars, attachments, …)? Public-read or per-user?".6b. Agents. Only if create_agent is tagged in the idea. For each agent, capture:
name (slug), one-line purpose.query_table, insert_row, …), which functions (must exist in the Functions section), which MCP servers (URL + transport).safety_acknowledged_needed: true and set per-IP / per-user / per-app rate limits + daily_budget_usd.agents/<name>.json) rides along in the repo snapshot, so this matters for the publish stage too."Frontend: ① Vite + React ② Next.js ③ static HTML ④ none (API-only)." Write to 00-state.md frontend_stack.7b. Publish-as-template. Read publish_as_template from 00-state.md front-matter (set by journey-idea). If yes or unlisted, plan for it now:
butterbase_api_key) vs. require manual user input on clone.agents/*.json files need to be exported and committed (yes if Agents section is non-empty).butterbase repo push to upload the source tree as a snapshot — without it, cloners get an empty file tree.Ask: "Will your app's code use @butterbase/sdk only in the frontend, only server-side (functions, scripts), or both?" Record under Toolchain → SDK surfaces.
Ask: "Want to install @butterbase/cli for the local dev loop (logs, scaffolding, key rotation)? (yes/no — default yes)" Record under Toolchain → CLI usage.
"Ship now or post-hackathon?" Write the cut list into 02-plan.md's "Post-hackathon" section.00-state.md's checklist to read - [ ] <stage> (n/a) for that row. Also do this for rls if hackathon_mode: true (mark as (folded into schema)).10. Final approval. Show the user the assembled plan and ask: "Plan looks good? (yes / revise <section>)". Loop until yes.
02-plan.md format# Plan
## Tables
- `users` (id uuid pk, email text unique, created_at timestamp)
- `orders` (id uuid pk, user_id uuid fk→users.id, status enum[pending,paid,shipped], total int, created_at timestamp; index on user_id)
- ...
## RLS
- `orders`: user-isolation (create_user_isolation, owner column = user_id)
- ...
## Auth
- Providers: Google
- Demo user: yes (email [email protected], password set via seed)
## Functions
- `stripe-webhook` — HTTP, idempotency table `_processed_events`
- `daily-digest` — cron 0 9 * * * UTC
## Storage
- bucket: `avatars` (per-user, private; download via presigned URL)
## AI / RAG / realtime / durable
- (none)
## Agents
- `order-summariser` — purpose: summarise a user's recent orders on demand.
- Tools: builtin `query_table`, function `format-currency`.
- Visibility: authenticated. Rate: 60/hr per user. Daily budget: $5.
- Default model: claude-haiku-4-5-20251001.
- Spec file: `agents/order-summariser.json` (committed to repo).
- (omit section entirely if no agents)
## Publish-as-template
- Intent: yes / unlisted / no
- README outline: <bullet list of sections>
- Env vars cloners must supply: <list per function>
- Auto-mint eligible keys: `butterbase_api_key` (etc.)
- Agent specs to bundle: `agents/*.json`
- Snapshot push: `butterbase repo push` at end of journey-templates.
- (omit section entirely if publish_as_template = no)
## Frontend
- Vite + React
## Toolchain
- **SDK surfaces**: <client-side only | server-side only | both>
- Client-side: install `@butterbase/sdk` in the frontend; use `auth`, `db`, `storage`, `realtime`.
- Server-side: install `@butterbase/sdk` in functions / scripts; use the service-key flow for elevated access.
- **CLI usage**: <yes / no>
- Yes (default): use `butterbase` CLI for local scaffolding, log tailing (`butterbase logs <fn>`), function invocation, and key rotation.
- **Why both**: MCP tools provision and orchestrate; SDK + CLI are the runtime + dev loop.
## Build order
1. schema
2. rls (folded into schema in hackathon mode)
3. auth
4. storage
5. functions
6. ai (if used)
7. rag (if used)
8. realtime (if used)
9. durable (if used)
10. agents (if used — must come after functions, ai, and any MCP-server setup)
11. frontend
12. deploy
13. templates (optional — only if publish_as_template != no)
## Post-hackathon
- email notifications (deferred)
- admin dashboard (deferred)
docs/butterbase/02-plan.md.00-state.md: tick - [x] plan, set frontend_stack, set current_stage: preflight, annotate skipped build stages with (n/a).Generate Hugging Face Hub (huggingface_hub) release notes from cached PR JSON files. Use when asked to draft release notes from PR files.
> Find Earth2Studio models, data sources, and examples for a weather/climate use case. Do NOT use for writing inference code, downloading data, or installation.
> Guide installing Earth2Studio via uv or pip, selecting model extras, and configuring the environment. Do NOT use for writing inference code, choosing models, or PhysicsNeMo questions.
Tokenize, tag, and analyze natural language text using Apple's NaturalLanguage framework and translate between languages with the Translation framework. Use when adding language identification, sentiment analysis, named entity recognition, part-of-speech tagging, text embeddings, or in-app translation to iOS/macOS/visionOS apps.
Routes any legal task to the right LLM, like OpenRouter but for legal work and grounded in benchmarks instead of brand loyalty. Built from mid-2026 legal evals (legalbenchmarks.ai, Vals AI × Stanford LegalBench across 124 models, Harvey's Legal Agent Benchmark, the Atticus Project's CUAD/MAUD/ACORD) plus translation evidence (WMT25, SwiLTra-Bench, ArabLegalEval). Covers five verticals: contract drafting, info extraction, legal research, contract review, and legal translation (including Arabic/MENA). Each asks up to four questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then returns a primary model, a fallback, what to avoid, and what a human must verify. Core principle: capability is not controllability, so every route ends with a verification step. Not legal advice; a lawyer owns the output.
Generates standalone interactive HTML "deal cards" that translate complex regulations into negotiation-ready reference tools, systematically distinguishing mandatory obligations from negotiable implementation choices. Use when the user needs an interactive regulatory guide for (1) contract negotiation support, (2) client education or internal training, (3) regulatory briefings for commercial stakeholders, or (4) structured comparison between required and flexible compliance paths. Primary focus on EU digital regulation (Data Act, AI Act, CRA, DORA, NIS2, GDPR) but the structural pattern transfers to any regulation where separating hard obligations from implementation choice is the point. Supports bilingual output where the jurisdiction calls for it.
> Pick the right LLM for CONTRACT DRAFTING — generating, redlining, or rewriting contract language from instructions. Vendor-neutral routing grounded in mid-2026 legal benchmarks (legalbenchmarks.ai Contract Drafting). Asks up to 4 quick questions (cost, speed, accuracy/ stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model should I use to draft this clause/agreement", "best AI for drafting contracts", "route this drafting task", or is about to generate/redline contract text and hasn't fixed a model.
Draft matter status reports from emails, call notes, and updates. Internal and client-facing formats, RAG logic, variance commentary, escalation flags. Use when asked to draft a status report, write a project update, summarise matter progress, prepare a client report, create a weekly or monthly update, convert emails into a status summary, or produce any kind of matter reporting. Also triggers when the user pastes email threads and asks what the status is, or needs to turn internal updates into client-facing reports.
Take butterbase-ai/journey-plan from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.