Vercel Composition Patterns
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
Draft launch or promotion copy for a shipped feature. An agent skill from leo-kuang-ai/spec-first.
$ npx skills add leo-kuang-ai/spec-first --skill spec-promote -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install leo-kuang-ai/spec-first spec-promote --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/leo-kuang-ai/spec-first.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/spec-promote .claude/skills/spec-promote && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "spec-promote" agent skill from https://github.com/leo-kuang-ai/spec-first/tree/master/skills/spec-promote into .claude/skills/spec-promote/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spec-promote", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/leo-kuang-ai/spec-first/tree/master/skills/spec-promoteType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add leo-kuang-ai/spec-first --skill spec-promote -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install leo-kuang-ai/spec-first spec-promote --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/leo-kuang-ai/spec-first.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/spec-promote .agents/skills/spec-promote && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "spec-promote" agent skill from https://github.com/leo-kuang-ai/spec-first/tree/master/skills/spec-promote into .agents/skills/spec-promote/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spec-promote", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add leo-kuang-ai/spec-first --skill spec-promote -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install leo-kuang-ai/spec-first spec-promote --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/leo-kuang-ai/spec-first.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/spec-promote .cursor/skills/spec-promote && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "spec-promote" agent skill from https://github.com/leo-kuang-ai/spec-first/tree/master/skills/spec-promote into .cursor/skills/spec-promote/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spec-promote", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/leo-kuang-ai/spec-first.git --path skills/spec-promote--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add leo-kuang-ai/spec-first --skill spec-promote -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install leo-kuang-ai/spec-first spec-promote --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/leo-kuang-ai/spec-first.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/spec-promote .gemini/skills/spec-promote && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "spec-promote" agent skill from https://github.com/leo-kuang-ai/spec-first/tree/master/skills/spec-promote into .gemini/skills/spec-promote/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spec-promote", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install leo-kuang-ai/spec-first spec-promoteInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add leo-kuang-ai/spec-first --skill spec-promote -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/leo-kuang-ai/spec-first.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/spec-promote .github/skills/spec-promote && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "spec-promote" agent skill from https://github.com/leo-kuang-ai/spec-first/tree/master/skills/spec-promote into .github/skills/spec-promote/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spec-promote", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add leo-kuang-ai/spec-first --skill spec-promote -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install leo-kuang-ai/spec-first spec-promote --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/leo-kuang-ai/spec-first.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/spec-promote .opencode/skills/spec-promote && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "spec-promote" agent skill from https://github.com/leo-kuang-ai/spec-first/tree/master/skills/spec-promote into .opencode/skills/spec-promote/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spec-promote", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
spec-promoteDraft launch or promotion copy for a shipped feature. An agent skill from leo-kuang-ai/spec-first.
Spec Promote is an agent skill from leo-kuang-ai/spec-first. Draft launch or promotion copy for a shipped feature.
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 19 other files, including scripts and reference files (for example `evals/cases/no-publish-side-effects.yaml`, `evals/cases/nothing-shipped-asks.yaml` and `evals/eval.yaml`).
It sits in Development. The repository describes itself as: 仓库原生 AI Coding Harness —— 把一次性 AI 对话变成可治理、可验证、可沉淀的工程闭环 · spec-first.cn. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 74655dc. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (JavaScript and Shell), which the agent can run.
Shell commands in SKILL.md call:
ghgitnodenpmFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use gh, git and npm, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Spec Promote loads about 2.8k tokens when it runs, and up to ~6k if it reads all its reference files. Until then it costs about 17 tokens; SKILL.md has 1,521 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from leo-kuang-ai/spec-first at commit 74655dc, republished under its MIT licence (© leo-kuang-ai). 1,521 words, ~2,782 tokens.
.claude/skills/spec-promote/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.Turn a feature that just shipped into copy-pasteable, user-facing announcement copy — right inside the engineering workflow.
After you ship, the messaging shouldn't wait for a separate marketing pass. spec-promote figures out what shipped, picks the right channels, and drafts the copy. It is spiral-agnostic by default: with nothing installed it draws on a lite layer of editorial and social-media expertise to produce strong channel-specific copy. When the Spiral CLI (see references/spiral-cli.md) is present and authed, it uses Spiral so the drafts are voice-matched to your brand — a subtle enhancement, never a requirement.
The promotion output is draft-only. It never posts, publishes, commits, or opens PRs. Posting is a human action. The only durable local preference exception is the separately disclosed and authorized Spiral opt-out write described in Path 0; it is not promotion output and must remain local-only.
spec-promote # Derive what shipped from context, draft defaults
spec-promote [free-form description] # You describe what shipped
spec-promote a tweet thread and a LinkedIn post # Request specific channels
spec-promote 3 tweet options for the new export featureIf the user gave a free-form description of the feature, use it as the source of truth.
Otherwise, derive it from context (use what's available; don't block on any one source):
gh pr view --json title,body,url 2>/dev/null (and gh pr view for the current branch). The title and body usually state the user-facing value.git diff main...HEAD --stat and skim notable changes to ground the claim in what actually changed.[Unreleased] entry in docs/changelog.md, CHANGELOG.md, or similar.git log --oneline -15 for the arc of the change.Then write a 1–3 sentence summary of the user-facing value — what a user can now do that they couldn't before, and why they'd care. Describe the outcome, not the implementation. ("You can now export any report to CSV in one click" — not "Added a CsvSerializer and an export endpoint.")
If you can't confidently tell what shipped, ask the user one short question rather than guessing.
Default to a small, sensible set:
Scale to what the change warrants and to what the user asked for. If they named channels ("LinkedIn", "email", "a blog intro", "a short demo script"), draft those instead of or in addition to the defaults. A small fix needs one or two short drafts; a flagship feature can justify a cross-channel set. Don't force a fixed template.
First, detect Spiral's state with the Skill-owned bounded probe. Resolve SKILL_DIR from the spec-promote/SKILL.md you loaded; do not run spiral auth status directly because provider stdout/stderr may contain secret-like fields:
SKILL_DIR="<absolute path of the directory containing this SKILL.md>"
node "$SKILL_DIR/scripts/check-spiral-auth.cjs"Classify into one of three states:
status: unavailable → Path 0 (install), then Path A if set up, else Path B.status: ready and authenticated: true → Path A (voice-matched).Never let a Spiral failure, timeout, or odd output block or slow the skill — when in doubt, treat it as not-ready and continue.
When Spiral isn't ready, offer to set it up once — unless the user previously opted out. The point is one proactive nudge, never a recurring one, and never a blocker: a decline always proceeds to Path B. Any dismissal records the opt-out, so a single first-run decline stops the offer for good in this repo — the user is never asked twice.
Read references/spiral-cli.md for the exact setup prompt (built with the platform's blocking-question tool), the connect/install steps, and how the opt-out is recorded so later runs skip this. In short:
spiral login --json (CLI >= 1.8.0; non-blocking, the API key never passes through the agent). On status: already_authenticated → use Path A. On status: pending → surface the auth_url, the user approves in their browser, then re-run the bounded auth probe after the user's confirmation; status: ready → Path A. Never have the user paste a key into chat. (Older CLI without agent login → suggest npm i -g @every-env/spiral-cli@latest, or have the user run spiral login themselves.) Escape hatch: "or the agent can just draft directly, without Spiral's personalization and humanization."Skip Path 0 entirely — straight to Path B — when the opt-out is already recorded, or when running headless / non-interactive (no human to answer). If a human is present but no blocking-question tool is available, do not skip — fall back to a numbered list of the two options in chat and wait for a reply (per the Ask section of references/spiral-cli.md).
Use the Spiral CLI so drafts match the user's brand voice. Read references/spiral-cli.md before composing the prompt — multi-channel vs. single-channel-variations is phrasing-driven (channel keywords / cue words vs. --num-drafts) and getting it wrong silently returns the wrong number or shape of drafts. The exact phrasing rules live there; don't restate them from memory. Essentials:
Before sending feature context or promotion copy to Spiral, record provider_egress_authorization: authorized | missing. Authentication, installation, prior use, requested channels, and general drafting intent do not authorize a run-local content transfer. Display the provider, content categories being sent, persistence behavior, and local Path B alternative; proceed only when the current request or a new confirmation explicitly authorizes this transfer. Missing authority returns provider_egress_authorization_missing and uses Path B with zero spiral write calls.
--instant and --json. Parse drafts[] (each carries its own channel) plus session_id.channel. Spiral decides how many drafts per channel — multi-channel runs often return several per channel — so never assume one-per-channel or drop extras.If the authorized spiral write call errors or returns no usable drafts, fall back to Path B for the affected channels, but do not describe the run as local-only. Return a safe provider receipt with provider_attempt: attempted, delivery_status: unknown, an allowlisted reason_code, persistence_status: possible-or-unknown, and fallback_used: true. Never copy raw Spiral stdout/stderr, exception text, internal commentary, or secret-like fields into chat, logs, or durable artifacts.
No Spiral needed — draft strong copy directly using a compact layer of editorial and social-media fundamentals. (The Spiral path goes further: brand-voice matching, humanization, saved styles, and cross-channel campaign orchestration.)
Editorial fundamentals — every channel:
Social fundamentals — distributed channels:
Per channel:
Drafts per channel: one strong draft by default; produce more only when asked ("3 tweet options"), capped ~3.
Show every draft as a clean, copy-pasteable block, labeled by channel. For each:
### X post
<the copy>session_id and each draft's url so the user can open and tweak them in the Spiral web app.Single-channel variations — "3 tweet options":
User:
spec-promote 3 tweet options for the new one-click CSV export→ Summarize the value. Spiral path:spiral write "3 tweet options for one-click CSV export" --instant --num-drafts 3 --json(no cue words). No-Spiral path: write 3 distinct tweets directly. Present all three.
Multi-channel set — "a campaign across X, LinkedIn, and email":
User:
spec-promote draft a launch across X, LinkedIn, and email→ Spiral path:spiral write "announcing one-click CSV export — a launch across X, LinkedIn, and email" --instant --jsonreturns a set of drafts per channel (Spiral decides the count — often several), each carrying itschannel. (--num-draftsignored here.) No-Spiral path: draft one X post, one LinkedIn post, one email directly. Present every returned draft, grouped by channel.
© leo-kuang-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 10 other files (scripts, references) in skills/spec-promote of leo-kuang-ai/spec-first.
Open the folder on GitHubat commit 74655dc
Spec Promote next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Spec Promote this skillleo-kuang-ai/spec-first | 107 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Vercel Composition Patternssupabase/supabase | 111k | 58 repos | ~726 | Automated safety check: Pass | MIT | |
| Finishing a Development Branchobra/superpowers | 297k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Typescript Advanced Typesrolling-scopes/rsschool-app | 10k | 25 repos | ~4.2k | Automated safety check: Pass | MPL-2.0 | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 4 repos | ~1.1k | Automated safety check: Pass | MIT |
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
rolling-scopes/rsschool-app
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications.
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
onyx-dot-app/onyx
Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments.
leo-kuang-ai/spec-first
Audit mobile App PRD/Figma/local-source consistency across page routes, KMP/Clean Architecture, components, analytics, i18n, engineering quality, and industry lenses before runtime validation; use…
leo-kuang-ai/spec-first
Create a durable cross-session handoff or resume from a user-selected continuity source.
leo-kuang-ai/spec-first
Give a decisive, project-grounded verdict on an external input — judged against the current project, not in the abstract.
leo-kuang-ai/spec-first
Resolve PR review feedback by evaluating validity and fixing issues with conflict-aware resolver dispatch.
leo-kuang-ai/spec-first
Analyze explicit Riffrec product-feedback captures, including riffrec-.zip, the Riffrec session.json + events.json + recording.webm + voice.webm bundle, or media/notes the user identifies as a…
leo-kuang-ai/spec-first
Document a recently solved problem or durable project vocabulary in docs/solutions/ or CONCEPTS.md.
Categories
Draft launch or promotion copy for a shipped feature. An agent skill from leo-kuang-ai/spec-first. Spec Promote is an agent skill from leo-kuang-ai/spec-first. Draft launch or promotion copy for a shipped feature.
Spec Promote fits situations like: development work in your project.
Run `npx skills add leo-kuang-ai/spec-first --skill spec-promote -a claude-code`. Or copy the skill folder (skills/spec-promote in leo-kuang-ai/spec-first) into .claude/skills/spec-promote in your project. Claude Code loads it when a task matches its description.
Run `npx skills add leo-kuang-ai/spec-first --skill spec-promote -a codex`. Or copy the skill folder (skills/spec-promote in leo-kuang-ai/spec-first) into .agents/skills/spec-promote in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add leo-kuang-ai/spec-first --skill spec-promote -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spec-promote, .gemini/skills/spec-promote, .github/skills/spec-promote and .opencode/skills/spec-promote in your project.
Going by SKILL.md and its folder, Spec Promote needs JavaScript and a shell for the scripts in its folder and the command-line tools its instructions call (gh, git, node and npm). Our summary lists: Node.js; A Bash shell.
SKILL.md contains no URLs. Its commands use gh, git and npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Spec Promote is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Spec Promote: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
leo-kuang-ai (a GitHub user) maintains it in leo-kuang-ai/spec-first, which has 107 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on October 8, 2026.
Source: leo-kuang-ai/spec-first on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.