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Ce Brainstorm

OrganizationPopular
EveryInc
ce-brainstorm

Explore vague or ambitious ideas into a right-sized requirements-only unified plan. Use when the user wants to brainstorm or scope what to build. Not for executing already-specified work. Use ce-pov for a verdict on adopting a named external technology.

Overview

PublisherEveryInc
Repositorycompound-engineering-plugin
Skill namece-brainstorm
Stars
25.1K
Forks
2.1K
Bundled files
25
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 25 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by EveryInc on GitHub. Read the source before you install it.

Installation

Install the Ce Brainstorm AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/EveryInc/compound-engineering-plugin.git /tmp/compound-engineering-plugin
mkdir -p .claude/skills
cp -r /tmp/compound-engineering-plugin/skills/ce-brainstorm .claude/skills/ce-brainstorm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ce Brainstorm in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ce Brainstorm on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ce Brainstorm is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Brainstorm a Feature or Improvement

Brainstorming answers WHAT to build through dialogue; ce-plan then enriches the same unified plan artifact with HOW. This skill does not implement code. The current year is 2026, for dating the artifact.

Outcome: a result sized to the work that ce-plan can build on without inventing product behavior, scope boundaries, or success criteria: a chat paragraph for Lightweight work, or a requirements-only unified plan under <root>/plans/ when a file is earned.

Done, on the brainstorm path: that artifact is written and passes the Ready for Planning Check — or no file was written because the dialogue produced no decision that a later reader (the planner, a reviewer, or a future reader) needs recorded under a stable ID and the user asked for none — and Phase 4's handoff has been presented.

Lightweight work ends in chat. Phase 0.3 classifies the tier from the request and bounded inline reads before anything is dispatched; when the tier is uncertain, take the heavier one. Lightweight work — small, well-bounded, low ambiguity — ends in a chat paragraph with no file, no grounding scout, no approach generation, and no claim verifier. A file is earned only by a decision that a later reader needs recorded under a stable ID, or by the user asking for one.

Stop and route instead in three cases, decided by references/phase-0.md, not from memory. Each ends the run its own way, so the done condition above does not apply: non-software work, where references/universal-brainstorming.md replaces Phases 0.2–4; a verdict question about a named external candidate, where you offer the ce-pov handoff; and neither — quick help, a factual question, a single-step task — answered directly.

The feature description is what the invocation carries, whether the user wrote it or a calling skill passed it. If none came, ask the user what they want to explore and do not proceed until you have one.

mode:return-to-caller (a leading token a calling skill such as lfg sets): strip it, run the dialogue unchanged, and replace Phase 4 with the structured return references/handoff.md defines: no menu, no lfg or ce-plan invocation.

Artifact Root

Resolve <root> the first time you compose or read a <root>/ path, never earlier; a scratch-only or no-repo run that touches none skips this entirely.

Resolve the CE artifact root <root> before composing any artifact path.

  • Read docs_root from <repo-root>/.compound-engineering/config.yaml only (<repo-root> = git rev-parse --show-toplevel). Do not read it from config.local.yaml. Unset -> <root> is docs, exactly as before.
  • Validate a set value: a repo-relative directory whose real, symlink-resolved path stays inside the repo and is neither the repo root nor under .git/. Otherwise stop with an error naming docs_root and the value -- never fall back to docs.
  • Use <root> as the sole artifact location: create it if absent, compose each path as <root>/<subdir> with this skill's own subdirectory, and never also read docs.

brainstorm_output and brainstorm_model resolve by this rule instead:

Resolve ordinary CE yaml keys from the two repo files.

  • Read <repo-root>/.compound-engineering/config.local.yaml, then config.yaml (<repo-root> = git rev-parse --show-toplevel). Missing files are skipped. Gitignore does not change resolution.
  • Win with the first active (non-commented) value. For scalars, empty is unset; an invalid value continues to the next layer, then the skill default. For lists and maps, a present key — including an empty list or map — replaces the whole key.
  • Do not use this rule for docs_root — that key is config.yaml only.

Execution Flow

Phases run in this order. Each names the files it cannot run correctly without: read them when you reach it, and never do its work from this table alone.

PhaseRead firstWhat only those files carry
before the first question, and for the whole run — non-software route includedRead references/interaction-rules.mdthe Core Principles, and the Interaction Rules: one question per turn, ask only decisions the environment cannot settle, the blocking-question-tool default and the visual-probe gate that overrides it, when a question is genuinely open-ended, and the one ce-prototype routing test this skill states in full there
before treating a decision the conversation carries as settledRead references/settled-decisions.mdthe settlement test; skipping it re-asks a decided question or promotes an unexamined assertion
0.0 output modereferences/output-mode.mdthe OUTPUT_FORMAT precedence; the token-parsing convention
0.1–0.4 resume, classify, route, scopereferences/phase-0.mdresume scan; the stop-and-route classification; scope tiers; the coherent-work gate (is this one piece of work?); both tripwires (visual or spatial features; unfamiliar territory); the task list
1 understand the ideareferences/dialogue.mdcontext scan and grounding scout; opt-in Slack researcher; pressure test; blindspot and visual-probe gates; the conflict gate against existing CONCEPTS.md and verified code; Phase 1.3 exit condition
2–2.6 approaches, synthesis, verificationreferences/approaches.md, plus references/synthesis-summary.md before composing the synthesisapproach generation; model elevation; the scoping synthesis; the claim verifier
3 write the planreferences/plan-write.md, then references/brainstorm-sections.md and the rendering reference for the formatwhether a doc is warranted; the section contract; the Ready for Planning Check
4 handoffreferences/handoff.mdthe option set and its visibility conditions; the rendering-mode rule; per-selection dispatch, including what ce-plan is passed; closing summaries

These rules hold without any read:

OUTPUT_FORMAT is exclusive — markdown OR HTML, never both. The format is the first that applies: a request in this prompt, a preference the user stated earlier, config, then markdown, in every run including headless ones.

When a file is written on the brainstorm path the artifact contract does not change: write to <root>/plans/YYYY-MM-DD-HHMM-<type>-<topic>-plan.<md|html>, with HHMM from local wall-clock time at write; frontmatter carries artifact_contract: ce-unified-plan/v1 and product_contract_source: ce-brainstorm; the body is a Goal Capsule plus the Product Contract. Do not emit a Goal Launch Block or Reader Index. The non-software route writes none of this.

When a file is written, do not declare it written or enter Phase 4 while any check fails in the Ready for Planning Check; a chat result enters Phase 4 (the handoff) with no check to run. An improvised handoff menu is the other silent failure: it shows options that should be hidden and passes the wrong input to the next skill.

The Phase 1.1 grounding scout, the Phase 2.6 claim verifier, and the opt-in Slack researcher are tiered by task shape, never hardcoded to a model name; read references/model-tiers.md before dispatching one. Model elevation is a separate mechanism (references/reasoning-elevation.md).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ce Brainstorm AI skill do?

Explore vague or ambitious ideas into a right-sized requirements-only unified plan. Use when the user wants to brainstorm or scope what to build. Not for executing already-specified work. Use ce-pov for a verdict on adopting a named external technology.

Why use Ce Brainstorm on TypingMind?

Because you install it once and use it with any model. Ce Brainstorm is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ce Brainstorm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/EveryInc/compound-engineering-plugin/tree/main/skills/ce-brainstorm. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ce Brainstorm?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ce Brainstorm?

As many as you like. As long as a model supports skills, you can use Ce Brainstorm with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ce Brainstorm AI skill free?

Yes. It is published on GitHub by EveryInc under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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