Vercel Composition Patterns
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
Rewrite an existing spec so it matches what the codebase does now: drop shipped items, update partially-done ones, fix stale paths and names, remove obsolete scope.
$ npx skills add changkun/wallfacer --skill wf-spec-refine -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install changkun/wallfacer wf-spec-refine --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-refine .claude/skills/wf-spec-refine && 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-refine" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-refine into .claude/skills/wf-spec-refine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-refine", 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-refineType 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-refine -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install changkun/wallfacer wf-spec-refine --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-refine .agents/skills/wf-spec-refine && 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-refine" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-refine into .agents/skills/wf-spec-refine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-refine", 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-refine -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install changkun/wallfacer wf-spec-refine --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-refine .cursor/skills/wf-spec-refine && 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-refine" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-refine into .cursor/skills/wf-spec-refine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-refine", 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-refine--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-refine -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install changkun/wallfacer wf-spec-refine --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-refine .gemini/skills/wf-spec-refine && 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-refine" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-refine into .gemini/skills/wf-spec-refine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-refine", 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-refineInstalls 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-refine -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-refine .github/skills/wf-spec-refine && 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-refine" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-refine into .github/skills/wf-spec-refine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-refine", 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-refine -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-refine --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-refine .opencode/skills/wf-spec-refine && 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-refine" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-refine into .opencode/skills/wf-spec-refine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-refine", 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-refineRewrite an existing spec so it matches what the codebase does now: drop shipped items, update partially-done ones, fix stale paths and names, remove obsolete scope.
Wf Spec Refine is an agent skill from changkun/wallfacer. Rewrite an existing spec so it matches what the codebase does now: drop shipped items, update partially-done ones, fix stale paths and names, remove obsolete scope. Takes optional feedback after the path to steer the rewrite. Use when a spec no longer describes reality; use create when there is no spec yet.
Its SKILL.md is about 1.7k 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.
6 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 these tools, so the agent can use them without asking each time:
ReadGrepGlobEditWriteAgentBash(git log *)Bash(git show *)Bash(git diff *)Bash(ls *)From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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 Refine loads about 1.7k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 951 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). 951 words, ~1,747 tokens.
.claude/skills/wf-spec-refine/SKILL.md (or your agent's skills folder).Update a spec file so it accurately reflects the current state of the project. Remove work that is already done, update partially-done items, and revise descriptions to match what actually exists in the codebase.
$ARGUMENTS has the form: <spec-file.md> [feedback...]
specs/windows-support.md).If feedback is present, apply it in addition to the standard codebase audit below. Feedback takes precedence over the default rules when they conflict (e.g., if feedback says "keep the done items as a checklist", do that instead of removing them per rule 3a).
Read the spec file identified in Step 0. Parse YAML frontmatter to extract
title, status, depends_on, affects, effort, created,
updated, author, dispatched_task_id.
Note the current lifecycle state — this guides the refinement:
vague → focus on fleshing out design, adding detaildrafted → focus on accuracy, removing done items, updating referencesvalidated → focus on keeping the spec in sync with implementation realitycomplete → the spec should not normally need refinement; if it does, it may
need to move to stalestale → the primary goal is to refresh the spec; may transition to drafted
or validated after refinementParse the body into a list of proposed work items, features, or changes. For each item, note:
For every item in the spec, determine its current status by searching the codebase. Use Grep, Glob, and Read to find evidence. Launch Agent subagents in parallel for independent items to speed this up.
Classify each item as one of:
For each classification, record the specific files, functions, tests, or commits that serve as evidence.
Apply these rules:
Delete items that are fully implemented. Do not leave them as "completed" checkboxes — they clutter the spec. If the done work is context for remaining items, mention it briefly in a "Current State" or "Already Implemented" summary section at the top (keep this concise — a few bullet points, not a full recap).
For items that are partially complete:
Retain these, but revise their descriptions if the surrounding code has changed since the spec was written (new function names, moved files, changed APIs).
Delete items that no longer apply. If the reason for obsolescence is non-obvious, add a one-line note explaining why it was removed.
updated → set to today's datestatus → adjust if warranted (e.g., stale → drafted after refresh,
complete → stale if significant drift found)affects → add or remove paths to match what the spec actually describesdepends_on → add or remove entries if dependencies have changedeffort → re-estimate if scope changed significantlyIf feedback was provided in $ARGUMENTS (see Step 0), apply it now. Feedback may include directives such as:
When feedback conflicts with rules 3a–3e (e.g., "keep done items visible"), follow the feedback. When feedback is ambiguous, make a reasonable choice and flag it in the Step 5 summary.
Use Edit (preferred) or Write to update the spec file in place. Preserve the original markdown style (heading levels, list format, code fence style).
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-refine of changkun/wallfacer.
Open the folder on GitHubat commit 5b3cea1
Wf Spec Refine 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 Refine this skillchangkun/wallfacer | 112 | — | ~1.7k | 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 | 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
Rewrite an existing spec so it matches what the codebase does now: drop shipped items, update partially-done ones, fix stale paths and names, remove obsolete scope. Wf Spec Refine is an agent skill from changkun/wallfacer. Rewrite an existing spec so it matches what the codebase does now: drop shipped items, update partially-done ones, fix stale paths and names, remove obsolete scope.
Wf Spec Refine fits situations like: A spec no longer describes reality; use create when there is no spec yet.
Run `npx skills add changkun/wallfacer --skill wf-spec-refine -a claude-code`. Or copy the skill folder (.claude/skills/wf-spec-refine in changkun/wallfacer) into .claude/skills/wf-spec-refine in your project. Claude Code loads it when a task matches its description.
Run `npx skills add changkun/wallfacer --skill wf-spec-refine -a codex`. Or copy the skill folder (.claude/skills/wf-spec-refine in changkun/wallfacer) into .agents/skills/wf-spec-refine 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-refine -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-refine, .gemini/skills/wf-spec-refine, .github/skills/wf-spec-refine and .opencode/skills/wf-spec-refine in your project.
SKILL.md names no scripts, command-line tools or credentials: Wf Spec Refine is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob, Edit, Write, Agent, Bash(git log *), Bash(git show *), Bash(git diff *), Bash(ls *).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. 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 Refine is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.7k tokens (SKILL.md is roughly 7k 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 Refine: 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.
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.