Vercel Composition Patterns
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
Build a spec: plan the work, implement each item with tests and docs, commit, then finalize.
$ npx skills add changkun/wallfacer --skill wf-spec-implement -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install changkun/wallfacer wf-spec-implement --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/changkun/wallfacer.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/wf-spec-implement .claude/skills/wf-spec-implement && 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 "wf-spec-implement" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-implement into .claude/skills/wf-spec-implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-implement", 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/changkun/wallfacer/tree/main/.claude/skills/wf-spec-implementType 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 changkun/wallfacer --skill wf-spec-implement -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install changkun/wallfacer wf-spec-implement --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/wf-spec-implement .agents/skills/wf-spec-implement && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "wf-spec-implement" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-implement into .agents/skills/wf-spec-implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-implement", 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 changkun/wallfacer --skill wf-spec-implement -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install changkun/wallfacer wf-spec-implement --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/wf-spec-implement .cursor/skills/wf-spec-implement && 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 "wf-spec-implement" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-implement into .cursor/skills/wf-spec-implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-implement", 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/changkun/wallfacer.git --path .claude/skills/wf-spec-implement--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 changkun/wallfacer --skill wf-spec-implement -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install changkun/wallfacer wf-spec-implement --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/wf-spec-implement .gemini/skills/wf-spec-implement && 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 "wf-spec-implement" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-implement into .gemini/skills/wf-spec-implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-implement", 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 changkun/wallfacer wf-spec-implementInstalls 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 changkun/wallfacer --skill wf-spec-implement -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/wf-spec-implement .github/skills/wf-spec-implement && 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 "wf-spec-implement" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-implement into .github/skills/wf-spec-implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-implement", 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 changkun/wallfacer --skill wf-spec-implement -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install changkun/wallfacer wf-spec-implement --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/wf-spec-implement .opencode/skills/wf-spec-implement && 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 "wf-spec-implement" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-implement into .opencode/skills/wf-spec-implement/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-implement", 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.
wf-spec-implementBuild a spec: plan the work, implement each item with tests and docs, commit, then finalize.
Wf Spec Implement is an agent skill from changkun/wallfacer. Build a spec: plan the work, implement each item with tests and docs, commit, then finalize. The only skill here that writes production code. Use when the user says "implement spec" or "build spec", or names a spec file to build.
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development. The repository describes itself as: Chat, specs, tasks, and code. An autonomous engineering platform. Full autonomy when you trust it. Full control when you don't. The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 5b3cea1. 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.
Shell commands in SKILL.md call:
gitFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git, 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.
Wf Spec Implement loads about 2.7k tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 1,500 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); files beside SKILL.md are not scanned.
The full file from changkun/wallfacer at commit 5b3cea1, republished under its MIT licence (© changkun). 1,500 words, ~2,694 tokens.
.claude/skills/wf-spec-implement/SKILL.md (or your agent's skills folder).Implement the design spec at $ARGUMENTS. The first token is the spec file path
(e.g., specs/04-file-explorer.md). Remaining tokens are optional focus
instructions — if provided, implement only the specified items/sections instead
of the full spec.
$ARGUMENTS).specs/ for a
matching filename.--- fences:
title, status, depends_on, affects, effort, created,
updated, author, dispatched_task_id. These drive readiness checks and
completion updates below.specs/README.md to understand where this spec sits in the track
organization and dependency graph.Before writing any code, verify:
status field:validated → ready to implement. Proceed.drafted → warn the user that the spec has not been reviewed/validated.
Ask whether to proceed anyway.vague → stop. The spec is not ready for implementation.testing → the implementation already landed and the drift verdict is
pending. Do not re-implement; run /wf-spec-wrapup to render the verdict.complete → already done. Confirm with the user before re-implementing.stale → warn the user the spec may not match reality. Suggest /wf-spec-refine
first.depends_on list from frontmatter.
For each dependency path, read that spec's frontmatter and confirm its
status is complete. If any dependency is not complete, report which
ones block this spec and ask the user how to proceed.affects list from frontmatter to locate the
relevant code files. Skim the spec for file paths, function names, and API
references. If any look stale, update them (or flag to the user) before
proceeding.git status to confirm the working tree is clean.
If dirty, ask the user how to proceed.Break the spec into an ordered list of implementation tasks. For each task:
Present this plan to the user for approval (in Claude Code, through plan mode). Group tasks into logical commits (small, focused). Order tasks so each commit leaves the project in a working state.
Wait for user approval before proceeding. The user may adjust scope, reorder items, or skip sections.
Autonomous mode (goal-driven / driven by /wf-spec-drive): plan-mode approval
is an interactive gate — it hangs an unattended /goal loop. So when this skill
is invoked by /wf-spec-drive under a goal, or with an explicit auto token in
the arguments, the goal itself is the standing approval: skip plan mode
and the approval wait, and go straight to Step 3. Stay conservative — keep
commits small, and if the plan turns out ambiguous, risky, or larger than a
single focused leaf, stop and report (surfacing it to the goal loop / user)
rather than guessing. Reserve autonomous mode for leaf specs you can build in one
pass; anything needing real design judgment should still pause for a human.
For each task in the approved plan:
AGENTS.md, CLAUDE.md, CONTRIBUTING.md, README.md, package manifests,
build files, and CI workflows. Treat the live repository as authoritative.After implementing each task, run the repository's documented gates in this order where they exist:
If the task adds, removes, or modifies any API route, CLI flag, env variable, data model field, or user-visible behavior:
api: add file content endpoint).After each commit, mark the completed task done and show the user a brief status update: what was done, what's next.
After all tasks are implemented, run the full verification set required by the repository, including its test suite and build or type-check command where they exist. If any gate fails, diagnose and fix it before finishing.
How you finalize depends on whether the whole spec shipped or only a subset (focus instructions, deferred/blocked items).
If every item in the spec was implemented, do not hand-roll the completion
write-up here — invoke /wf-spec-wrapup <spec-file>. It owns the canonical
finalization: driving the spec through the testing gate to complete (or
stale on significant drift) — never a raw validated → complete jump — writing
the ## Outcome section (What Shipped + Design Evolution + the
decisions/surprises/follow-ups detail), updating specs/README.md, the
reverse-dependency scan, and the single spec commit. This keeps direct-implement and dispatch converging on one finalizer and
one section convention, instead of two skills writing divergent sections.
Hand wrap-up the knowledge you accumulated this session as the Outcome source — the commit SHAs, the judgment calls, the deviations from the spec, the gotchas — so it documents what actually happened rather than reconstructing it from git. If a deviation made the spec body itself wrong, fix the body inline (wrap-up's Outcome explains the change; the body must read as current reality).
If only a subset shipped, do NOT mark the spec complete (that would let wrap-up close it). Instead:
status at validated (the lifecycle has no in_progress /
implemented state — a spec stays validated until it goes through testing
to complete, which only the full-completion wrap-up does); set updated to
today; record dispatched_task_id if this is a dispatched leaf.## Implementation notes section capturing the running state, with
tight bullets (omit a subsection only if genuinely empty):specs/README.md status column to the in-progress state and run
the reverse-depends_on scan for factual corrections to dependents only.specs: record partial progress on <spec-name>).Run /wf-spec-wrapup later, once the remaining items land, to do the full
completion write-up.
Report to the user:
© changkun, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/wf-spec-implement of changkun/wallfacer.
Open the folder on GitHubat commit 5b3cea1
Wf Spec Implement 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 |
|---|---|---|---|---|---|---|
| Wf Spec Implement this skillchangkun/wallfacer | 112 | — | ~2.7k | Automated safety check: Pass | MIT | |
| Vercel Composition Patternssupabase/supabase | 111k | 59 repos | ~726 | Automated safety check: Pass | MIT | |
| Finishing a Development Branchobra/superpowers | 296k | 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 | 5 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.
changkun/wallfacer
Split one spec into children — sub-design specs when questions are still open, or implementation-ready leaves when the plan is clear.
changkun/wallfacer
Write a new spec from scratch when none exists for the idea yet.
changkun/wallfacer
Mark a validated spec ready to build and resolve its dependency wiring; where a task board with a transition API is present, create the linked task atomically.
changkun/wallfacer
Run the whole lifecycle for one spec, calling the other skills in order and advancing one legal transition at a time until it reaches a target state (default complete), stopping to ask at…
changkun/wallfacer
Survey the whole spec tree: what is complete, in progress, blocked, and actionable next.
changkun/wallfacer
Read-only verdict on whether an implementation meets its spec: each acceptance criterion classified, unintended changes flagged, test coverage checked.
Categories
Build a spec: plan the work, implement each item with tests and docs, commit, then finalize. Wf Spec Implement is an agent skill from changkun/wallfacer. Build a spec: plan the work, implement each item with tests and docs, commit, then finalize.
Wf Spec Implement fits situations like: the user says implement spec; names a spec file to build.
Run `npx skills add changkun/wallfacer --skill wf-spec-implement -a claude-code`. Or copy the skill folder (.claude/skills/wf-spec-implement in changkun/wallfacer) into .claude/skills/wf-spec-implement in your project. Claude Code loads it when a task matches its description.
Run `npx skills add changkun/wallfacer --skill wf-spec-implement -a codex`. Or copy the skill folder (.claude/skills/wf-spec-implement in changkun/wallfacer) into .agents/skills/wf-spec-implement 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 changkun/wallfacer --skill wf-spec-implement -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wf-spec-implement, .gemini/skills/wf-spec-implement, .github/skills/wf-spec-implement and .opencode/skills/wf-spec-implement in your project.
Going by SKILL.md and its folder, Wf Spec Implement needs the command-line tools its instructions call (git).
SKILL.md contains no URLs. Its commands use git, 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. Review the folder before installing.
Wf Spec Implement is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k 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.
Skills that share tags, products or a category with Wf Spec Implement: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 296k 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.
changkun (a GitHub user) maintains it in changkun/wallfacer, which has 112 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 4, 2026.
Source: changkun/wallfacer on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.