SpellOut

Spell out your idea before AI builds it.

简体中文 · First card: try, install and troubleshoot · Settings

SpellOut / 说透 helps clarify a rough idea through question cards, free-text answers and guided follow-ups. A round contains 1 to 5 questions, shown one at a time. Balanced and deep presets default to a maximum of 3; users can raise the limit to 5. Choose minimal, balanced or deep questioning, or request a requirements interview before implementation.

New installations default to deep exploration. At first meaningful use, a setup card lets you choose how often and how deeply to ask; an explicit saved choice applies to later conversations on the same installation. Existing preferences are preserved. Trivial questions and fully specified instructions do not need a card. Global skill installation enables discovery across conversations, but invocation remains controlled by the host and assistant. See preferences.

Interaction is inspired by Claude Code's question cards. This independent project is not affiliated with OpenAI or Anthropic. Question quality depends on the model; a skill cannot lock host execution or guarantee understanding.

Try it, then install

Try the latest changes: select this repository's main branch → Code → Download ZIP. The published preview remains at Releases → v0.5.0 → Assets → spellout-source.tgz and does not contain the improvements below. Both downloads contain source, not a one-click app-store installer.

Run npm run demo in the source folder containing package.json, then open the printed address to try single choice, multiple choice and Other. Only Node.js is required; it needs no plugin installation or account, runs no AI and changes no settings. This command is available on main but is not yet included in the published v0.5.0 archive. The demo source on GitHub is not an interactive preview.

Follow the three-step first-use guide: download to a permanent folder → check and install → submit your first card in a new conversation. It includes prerequisites, a copyable first prompt, success criteria and troubleshooting.

Related MCP server: rubberduck-mcp

Install locally

0.5.0 is an incompatible update. Read migration and release notes first. Verify that the extracted package reports version 0.5.0 before installation.

Requires Node.js 22.12+, Codex CLI and an MCP Apps host. Extract source into a permanent folder and open a terminal at the level containing package.json:

npm run doctor
npm run setup

The first command only checks; the second asks for confirmation before installation. No separate npm install step is needed.

After inspection and confirmation, the wizard installs dependencies, runs tests, registers a missing MCP server and installs skills/spellout. A managed, unmodified skill can upgrade with a verified versioned backup in ~/.agents/skill-backups/, outside skill discovery. Edited or unrecognized differing files stop installation. The .spellout-install.json record contains the installed version and file hashes.

npm run doctor only checks and compares installed and repository versions. Old installations must be removed manually first; the wizard never deletes them. Use npm run setup -- --yes only for an intended unattended installation.

For manual setup, run npm ci, npm run configure, and npm test. Configuration prints a local registration command; inspect existing installations before running it. Use the wizard to install the managed skill. Update an existing plugin instead of adding duplicate MCP registrations.

Restart the host, start a task and ask: “Use SpellOut to clarify my requirements before implementation.” Verify the card appears, submit an answer and check the assistant reads it correctly.

Interaction and limits

• Select, multi-select or write in Other. Compatible needs use multi-select; single choice is reserved for mutually exclusive decisions or a required single priority. Use Back before submission.

• A small chevron opens settings and the requirements summary. Submitted cards collapse to Awaiting read, then Completed after the answer is acknowledged; this describes the question, not completion of the project.

• Adjust coverage, depth, frequency, diversity, challenge and round size; task settings and future defaults are separate.

• Answers save locally without an automatic follow-up message. Saving cannot restart an ended turn.

• The latest acknowledged answer returns processed: true to prevent repeated work after context compaction. This is not a transaction guaranteeing exactly-once external effects.

• A save timeout triggers a status check. Matching retries are idempotent.

• The demo uses scripted questions and in-memory answers; it does not run AI.

• Real Codex UI and phone Remote: not accepted for 0.5.0. DOM tests and responsive CSS do not prove mobile visibility. Use numbered conversation choices when cards are unavailable.

Privacy and development

No separate model API call or telemetry is added. Preferences and records stay local, subject to the host's conversation policies. npm run forget previews old records; deletion requires an explicit age cutoff and --yes. See privacy.

npm test covers the MCP server, card DOM, actual demo bridge, persistence, installation, cleanup and naming. npm run release builds a local dist/spellout-source.tgz from scripts/release-files.mjs. Machine configuration, dependencies, backups and bundled historical HTML snapshots are excluded. server/card.html is the shipped UI; runtime pages are cached by content hash. The script does not publish to GitHub.

See release checks and integrity checks. MIT; preserve LICENSE and NOTICE. Maintainer: Fan-dev-sktch.

Improvements on main (not yet in a new release archive)

One chevron exposes all question controls. Optional per-topic follow-up, coverage and alternatives counts have concrete limits; known requirements are not asked again. Help requests can be added to Other for this round. The editable requirements brief includes constraints and acceptance criteria and can be copied, including marked unsaved drafts. Feedback offers a local, inspectable status report; nothing is sent automatically. Model question quality and real mobile rendering require separate acceptance.