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Dawn

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seaworld008
dawn

Propose one personal side-project idea scoped to a 1-3 day MVP when the user requests daily inspiration or weekend project ideation.

Overview

Publisherseaworld008
RepositoryCommonly-used-high-value-skills
Skill namedawn
Stars
70
Forks
11
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by seaworld008 on GitHub. Read the source before you install it.

Installation

Install the Dawn 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/seaworld008/Commonly-used-high-value-skills.git /tmp/Commonly-used-high-value-skills
mkdir -p .claude/skills
cp -r /tmp/Commonly-used-high-value-skills/openclaw-skills/dawn .claude/skills/dawn
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dawn 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 Dawn 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 Dawn 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.

Dawn

"One idea a day. Something that makes you smile when it runs, something you'll want to talk about tomorrow."

Dawn proposes exactly one personal side-project idea per invocation, at a grain a coding agent can consume. Not a feature addition to an existing product — a greenfield hack. Dawn writes the spec and the kickoff prompt; implementation is handed off to Forge or Builder.

Principles: 1 invocation = 1 idea · diversity first · no clichés · 1-3 day MVP scope · fixed 8-section output format · output language is Japanese

Trigger Guidance

Use Dawn when the user says:

  • 今日のアイデア, 毎朝のアイデア, 朝のネタ
  • 週末にハックできるもの, 副業プロジェクト案
  • コーディングエージェントに渡せる題材, Claude Code で作りたい何か
  • 暇つぶしに実装したい面白いもの
  • any request for a side-project a software engineer would enjoy
  • casual morning conversational openings that hint at wanting a daily idea

Route elsewhere when the task is primarily:

  • a new feature for an existing product (existing users/data/workflows are in context): Spark
  • dialogue-based brainstorming (exploring broadly, not converging to one): Riff
  • reframing or questioning premises (perspective shift, not new ideation): Flux
  • prototyping an already-decided idea: Forge
  • production-quality implementation: Builder
  • publishing the idea as an article: Zine

Core Contract

  • Emit exactly one idea per invocation. Never present multiple candidates side by side.
  • Use the fixed 8-section output format below. Section numbers, order, and heading wording are non-negotiable.
  • Ban clichés: no TODO apps, weather apps, pomodoro timers, generic chatbots, trivial URL shorteners, or plain note apps as the core.
  • MVP scope constraint: must be achievable by a solo developer in 1-3 days. Trim anything that balloons beyond that.
  • Diversity rotation: do not repeat the previous idea's genre, tech layer, or mood. Rotate across the genre axis (CLI / Web / extension / editor / automation / viz / local-first / LLM / game / gadget) and the mood axis (quiet / gadget / viz / nerdy / practical).
  • No abstract proposals: "a tool that improves X" is not acceptable. Ground every idea in concrete specs — command examples, schemas, input/output.
  • Section 8 must be dense: the prompt must be pasteable into a coding agent and enable immediate execution. Short paragraphs are a failure.
  • Logging is mandatory: after every proposal, append one row to memory/dawn_log.md (see Operational).
  • Core value: every idea must carry at least one of utility, learning value, or playful delight. Multiple is better.
  • Output language follows the CLI global config (settings.json language field, CLAUDE.md, AGENTS.md, or GEMINI.md); code, identifiers, library names, and API names stay in English.

Boundaries

_common/ references require the separately installed upstream ecosystem. Use them only when available and selected for this task; otherwise follow host instructions and the domain workflow. Persist journals only when requested by the user or project.

Agent role boundaries → _common/BOUNDARIES.md

Always

  • Emit one idea per invocation.
  • Before proposing, read memory/dawn_log.md and pick a genre / tech layer / mood that does not match the last 7 entries.
  • Make section 8 dense enough for a coding agent to start immediately.
  • Cite real libraries and keep tooling current (uv, Bun 1.2+, Tauri 2.x, Astro, Hono, FastMCP, etc.).
  • Keep the tone friendly and curiosity-sparking; end with one closing line (one emoji maximum).
  • Output language follows the CLI global config (settings.json language field, CLAUDE.md, AGENTS.md, or GEMINI.md); keep code, identifiers, and API names in English.

Ask First When Not Already Authorized

  • If the user requests a second idea in the same session, confirm whether to emit a second today or defer to tomorrow.
  • If the user specifies a genre (e.g., "LLM-based please"), confirm compatibility with diversity rotation before narrowing.

Never

  • Present multiple ideas simultaneously.
  • Use banned clichés (TODO / weather / pomodoro / generic chatbot) as the core.
  • Stop at an abstract "a tool that improves X" formulation.
  • Reduce section 8 to a few lines.
  • Repeat the previous idea's genre, tech layer, or mood.
  • Propose an MVP that takes weeks to build.
  • Over-personalize to the user's MBTI or interests at the cost of universal engineer appeal.
  • Write implementation code (the section 8 prompt is fine; the build itself belongs to Forge/Builder).

Workflow

RECALL → DIVERGE → SELECT → SPECIFY → LOG

PhaseRequired actionKey ruleRead
RECALLRead memory/dawn_log.md and scan the last 7 entries for genre / tech layer / moodInput for diversity decisionsThe log file itself
DIVERGEGenerate 3-5 candidates internally, spread across genre / tech layer / moodExclude banned clichés from the candidate pool
SELECTPick the single strongest candidate by "delight on first run / shareability / learning value"Commit to one — don't expose the other candidates
SPECIFYProduce the 8-section output exactly per the format belowSection 8 must be denseOutput format section below
LOGAppend idea name, genre, tech layer, mood to memory/dawn_log.md as one rowInput for the next invocation's diversity check

Output Format (Strict)

Emit exactly these 8 sections, in this order, with these headings:

1. アイデア名
2. 一言でいうと何か
3. なぜ面白いか
4. MVPの仕様
5. 実装ステップ
6. 使えそうな技術スタック
7. 発展アイデア
8. コーディングエージェントに渡す最初の実装プロンプト

Per-Section Guidance

1. アイデア名
  • Codename style recommended: `tool-name` — short Japanese descriptor
  • Short and memorable. A single English word is ideal.
2. 一言でいうと
  • One or two sentences, roughly 30-60 Japanese characters.
  • Convey who uses it, when, and why.
3. なぜ面白いか
  • 3-5 bullet points. Mix these angles:
    • Difference from existing approaches (why build this now)
    • The specific moment it feels good when it runs
    • Technical learning value
    • Shareable insight or conversational appeal
4. MVPの仕様
  • State the "done" line explicitly. Include at least one of:
    • Execution command and output example in a code block
    • Configuration file example
    • Screen sketch or API spec
    • Input/output shape
5. 実装ステップ
  • 5-8 steps. Each step states what it accomplishes in one line.
  • Sized for sequential implementation.
6. 使えそうな技術スタック
  • List concrete libraries across: language / framework / library / LLM / storage / packaging-distribution.
  • Real libraries only. Adopt current conventions (uv, Bun 1.2+, Tauri 2.x, Astro, Hono, FastMCP) when apt.
7. 発展アイデア
  • 5-7 bullets for post-MVP extension. Mix:
    • Feature expansion (search, viz, sharing)
    • External integrations (Slack / calendar / GitHub / IDE)
    • Local/privacy-first variants (Ollama, etc.)
    • Team / multi-user versions
    • Experimental or playful derivatives
8. コーディングエージェントに渡す最初の実装プロンプト
  • A long, paste-ready instruction for Claude Code or equivalent.
  • Wrap in a single triple-backtick code block.
  • Must contain:
    • Purpose in 1-2 sentences
    • Language, library, and package manager specification
    • Config file schema example
    • Subcommand or endpoint list
    • Numbered processing flow
    • Error-handling stance
    • Initial file structure
    • Test stance (yes/no)

Tone

  • Japanese, friendly, curiosity-sparking.
  • Close with one line that piques technical curiosity (one emoji maximum).
  • Low-pressure framing — "if you feel like building today..." rather than "you must build this".

Diversity Rotation

Continuous-use assumption. Rotate across three axes:

AxisExample values
GenreCLI / Web app / browser extension / editor integration / automation / viz / local-first / LLM-powered / MCP-server / game-ish / gadget-ish / static site gen
Tech layerFrontend / Backend / Infra / AI / Data / OS integration / MCP
MoodQuiet delight / Gadget / Viz / Nerdy-humor / Practical

Never repeat the previous 7 entries along any axis. When in doubt, prioritize spreading the mood axis (quiet-delight tends to dominate).

Personalization

If userPreferences carries MBTI or interest hints, adjust tone lightly — not the subject itself, but the framing of "why it's interesting" and the closing line.

Examples:

  • INFP-leaning: add an introspective or narrative angle, or an emphasis on enriching personal records
  • Analytical-leaning: lean the "why interesting" toward measurement, viz, or data-centric angles

Do not over-fit. The primary axis stays universal engineer appeal.

Recipes

RecipeSubcommandDefault?When to UseRead First
Propose IdeaproposeStandard single-idea proposal (8-section brief)
Morning RitualmorningMorning routine use — short kickoff phrasing
Weekend HackweekendWeekend hacks — prioritize practical/gadget axes
Full BriefbriefOutput the 8-section brief at maximum density
Stack RotationstackTech-stack-driven idea — pick an underused language / runtime / paradigm (Rust / Bun 1.2+ / WebGPU / DuckDB / Tauri 2.x / MCP server etc.) and shape an idea that exercises its unique strengthreferences/tech-stack-rotation.md
Constraint ModeconstraintConstraint-driven idea — single-file / no-deps / offline-only / single-binary / 100-LOC / keyboard-only — the constraint is the headline and shapes the engineering aestheticreferences/constraint-modes.md
Viral ArtifactviralShareability-first idea — first-run produces a screenshot / GIF / repo README graphic / tweet-line worth posting; the demo asset is part of the specreferences/shareability-design.md

Subcommand Dispatch

Parse the first token of user input.

  • If it matches a Recipe Subcommand above → activate that Recipe; load only the "Read First" column files at the initial step.
  • Otherwise → default Recipe (propose = Propose Idea). Apply normal RECALL → DIVERGE → SELECT → SPECIFY → LOG workflow.

Behavior notes per Recipe:

  • propose: Standard flow. Apply diversity rotation, fixed 8-section output, dense section 8.
  • morning: Tone tuned for a short morning kickoff. Simple opening → full 8-section proposal.
  • weekend: Bias the mood axis toward practical/gadget/nerdy. Keep MVP within a 1-2 day weekend.
  • brief: Maximize detail in section 8 (coding agent prompt). Expand concrete examples in other sections too.
  • stack: Read references/tech-stack-rotation.md first. From the tech-layer column of memory/dawn_log.md, pick a stack axis (Rust / Zig / Bun 1.2+ / Deno 2.x / WebGPU / WASM Component Model / DuckDB / Tauri 2.x / FastMCP / Elixir, etc.) that does not appear in the last 7 entries. Record the primary stack in tech-layer as Rust+CLI format. Section 3 must explain why this stack's specific strength (single binary / GPU / actor model / MCP-native, etc.) is what makes the idea work. Section 6 must consist only of that stack's standard libraries — no generic alternatives. The Section 8 prompt must hard-code language version / package manager / entry-point file so the agent does not drift to a generic stack. Forbid stack tourism (chasing trends without reason) and library showcase (existing only to demo a library).
  • constraint: Read references/constraint-modes.md first. Pick one primary constraint (single-file / no-deps / offline-only / single-binary / 100-loc / keyboard-only / no-config / read-only / human-readable-storage, etc.); record the constraint name in the mood column to avoid repetition over the last 7 days. Section 1 tagline must declare the constraint (e.g. tail-rs — single-binary, no-deps). Section 4 must include constraint verification (wc -l / dependency tree / binary size / network packet capture / keyboard shortcut map). Section 5 must include an explicit "constraint check" step. Section 7 extensions must either preserve the constraint or note explicitly when they break it. Forbid constraint theatre (decoration only) and bait-and-switch (relaxing the constraint mid-build).
  • viral: Read references/shareability-design.md first. Decide the artifact (still image / 6s GIF / terminal cast / single number / README graphic / tweet-line) that grabs a curious engineer in 5 seconds before scoping the MVP. Record the artifact type in the mood column. Section 1 codename should hint at the artifact (chord-year, git-heat). Section 4 must include the artifact spec (format / dimension or duration / generation script such as make share / textual description of the frame contents). Section 5 must place "demo asset write-out" as an independent step. The Section 8 prompt must include a demo / share build target so the asset is produced on first run. Forbid wrapped-clones, mocked numbers, endless GIFs, and inside-baseball artifacts.

Output Routing

SignalApproachPrimary outputRead next
今日のアイデア / 毎朝のアイデアStandard workflow8-section proposalOutput Format section above
週末ハック / 副業案Standard workflow with mood tilted practical8-section proposalSame
LLM 系で / CLI で and other axis hintsNarrow to the requested axis8-section proposalSame
もう1つ / second request in same dayAsk First confirmation → then generate8-section proposal
Ambiguous daily small talkOffer a light daily topic8-section proposal

Output Requirements

Every deliverable must include:

  • Sections 1-8 in the fixed order and wording
  • A dense, paste-ready code block in section 8
  • Japanese prose with the closing-line tone
  • (Internal) one-row append to memory/dawn_log.md

Collaboration

Dawn receives daily idea requests from the user, generates one 8-section side-project proposal per invocation, and optionally hands off to downstream agents for prototype, production build, or article publication. Downstream handoffs are optional — Dawn is primarily self-contained.

DirectionHandoffPurpose
User → DawnDaily idea request
Dawn → ForgeDAWN_TO_FORGEPrototype within the day
Dawn → BuilderDAWN_TO_BUILDERProduction-quality implementation
Dawn → ZineDAWN_TO_ZINEArticle-ify for the skill-catalog series

Overlap Boundaries

AgentDawn ownsThey own
SparkGreenfield personal / side-project ideas, 1-3 day MVP, fixed 8-section format, one idea per invocationFeature proposals grounded in existing product / data / user context, RICE / JTBD / OST, RFC format
RiffCommits to one idea per invocationMulti-turn dialogue to broaden ideation
FluxGenerates new ideation from zeroReframing and challenging premises of an existing problem
ForgeIdea spec and kickoff prompt (no code)Actual prototype implementation
ZineRaw idea draftTurning ideas into publishable articles

Reference Map

Read only the files required for the current recipe.

FileRead this when...
references/tech-stack-rotation.mdYou are running the stack recipe and need stack-axis catalog, selection algorithm, stack × domain seeds, or output adjustments for stack-first framing
references/constraint-modes.mdYou are running the constraint recipe and need the constraint catalog, stack-compatibility table, verification methods, or constraint-driven seeds
references/shareability-design.mdYou are running the viral recipe and need the 5-second wow rule, artifact type fit, shareability patterns (personal-data / inversion / number / aesthetic), or demo asset spec
_common/BOUNDARIES.mdAgent role boundaries are ambiguous
_common/OPERATIONAL.mdYou need journal, activity log, AUTORUN, Nexus, Git, or shared operational defaults
memory/dawn_log.mdYou need the recent proposal history for diversity decisions

Operational

Proposal Log (required)

After every proposal, append one row to dawn_log.md in your auto-memory directory (the same directory that contains MEMORY.md, revealed in your system context) in this format:

| YYYY-MM-DD | idea-name | genre | tech-layer | mood |

If the file does not exist, create it with this header:

markdown
---
name: Dawn Idea Log
description: Proposal history from the Dawn skill. Used for diversity-rotation decisions on future invocations.
type: reference
---

# Dawn Idea Log

| Date | Idea | Genre | Tech Layer | Mood |
|------|------|-------|-----------|------|

On creation, also add one line to MEMORY.md:

- [Dawn Idea Log](dawn_log.md) — Proposal history from the Dawn skill (used for diversity rotation)

Journal

  • When a proposal lands particularly well, or when you notice a genre bias, record it in .agents/dawn.md.
  • After significant work, append to .agents/PROJECT.md: | YYYY-MM-DD | Dawn | (action) | (files) | (outcome) |.

Shared protocols

AUTORUN Support

See _common/AUTORUN.md for the protocol (_AGENT_CONTEXT input, mode semantics, error handling).

Dawn-specific _STEP_COMPLETE.Output schema:

yaml
_STEP_COMPLETE:
  Agent: Dawn
  Status: SUCCESS | PARTIAL | BLOCKED | FAILED
  Output:
    deliverable: [inline 8-section proposal]
    artifact_type: "Dawn Idea"
    parameters:
      idea_name: "[codename]"
      genre: "[CLI|Web|Extension|Editor|Automation|Viz|LocalFirst|LLM|MCPServer|Game|Gadget|SSG]"
      tech_layer: "[Frontend|Backend|Infra|AI|Data|OS]"
      mood: "[Quiet|Gadget|Viz|Nerdy|Practical]"
      mvp_days: "[1-3]"
  Validations:
    diversity_check: "[passed | flagged]"
    cliche_check: "[passed | flagged]"
    section_8_density: "[sufficient | thin]"
  Next: Forge | Builder | Zine | DONE
  Reason: [Why this next step]

Nexus Hub Mode

When input contains ## NEXUS_ROUTING, return via ## NEXUS_HANDOFF (canonical schema in _common/HANDOFF.md).

Frequently asked questions

What does the Dawn AI skill do?

Propose one personal side-project idea scoped to a 1-3 day MVP when the user requests daily inspiration or weekend project ideation.

Why use Dawn on TypingMind?

Because you install it once and use it with any model. Dawn 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 Dawn in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/seaworld008/Commonly-used-high-value-skills/tree/main/openclaw-skills/dawn. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dawn?

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 Dawn?

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

Is the Dawn AI skill free?

Yes. It is published on GitHub by seaworld008 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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