Landing Optimizer
aaron-he-zhu/aaron-marketing-skills
A skill your agent uses when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a…
Privileged applier that LANDS meta-optimize / corpus-audit patches the user approved, with a fresh landing review and human approval.
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep meta-apply --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/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skills-codex/meta-apply .claude/skills/meta-apply && 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 "meta-apply" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/meta-apply into .claude/skills/meta-apply/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-apply", 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/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/meta-applyType 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 wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep meta-apply --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/skills-codex/meta-apply .agents/skills/meta-apply && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "meta-apply" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/meta-apply into .agents/skills/meta-apply/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-apply", 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 wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep meta-apply --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/skills-codex/meta-apply .cursor/skills/meta-apply && 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 "meta-apply" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/meta-apply into .cursor/skills/meta-apply/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-apply", 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/wanshuiyin/Auto-claude-code-research-in-sleep.git --path skills/skills-codex/meta-apply--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 wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep meta-apply --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/skills-codex/meta-apply .gemini/skills/meta-apply && 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 "meta-apply" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/meta-apply into .gemini/skills/meta-apply/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-apply", 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 wanshuiyin/Auto-claude-code-research-in-sleep meta-applyInstalls 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 wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/skills-codex/meta-apply .github/skills/meta-apply && 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 "meta-apply" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/meta-apply into .github/skills/meta-apply/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-apply", 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 wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep meta-apply --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/skills-codex/meta-apply .opencode/skills/meta-apply && 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 "meta-apply" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/meta-apply into .opencode/skills/meta-apply/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-apply", 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.
meta-applyPrivileged applier that LANDS meta-optimize / corpus-audit patches the user approved, with a fresh landing review and human approval.
Meta Apply is an agent skill from wanshuiyin/Auto-claude-code-research-in-sleep. Privileged applier that LANDS meta-optimize / corpus-audit patches the user approved, with a fresh landing review and human approval. Base Codex review is same-family provisional. Use when the user says "meta apply", "/meta-apply", "land the staged patches", "应用优化", after a /meta-optimize run.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework… The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 26b95cf. 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:
Bash(*)ReadWriteEditGrepGlobFrom allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
python3From 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.
Meta Apply loads about 2.1k tokens when it runs. Until then it costs about 76 tokens; SKILL.md has 921 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 noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Bash(*), Read, Write, Edit, Grep, GlobAutomated 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 wanshuiyin/Auto-claude-code-research-in-sleep at commit 26b95cf, republished under its MIT licence (© wanshuiyin). 921 words, ~2,076 tokens.
.claude/skills/meta-apply/SKILL.md (or your agent's skills folder).Codex assurance: a base landing review records
review_independence: same-familyandacceptance_status: provisionalviastamp-provisional; the artifact is not auto-curatable. Only an overlay or deterministic verifier may produce accepted authorization.
This skill exists to enforce a privilege boundary. Producers like
/meta-optimize (and, later, corpus-audit) are
read-only — no Write/Edit, no apply step; they can only stage candidate patches
under .aris/meta/pending/. This skill is the only place a staged patch becomes a real
change to the corpus. Splitting "propose" from "land" across two skills with different
tool grants is what makes "a loop cannot apply its own patch" structural rather than a
sentence the producer is asked to obey.
It is human-invoked only. It runs when the user explicitly types /meta-apply after
reading the producer's REPORT. That invocation IS the landing authorization (the locked
2026-05-30 decision: the human stays at the landing gate).
The earlier design trusted a jury_verdict: pass field in the producer's manifest. That
is forgeable — the producer writes that field, so a buggy/misaligned producer could
stage a killed patch labelled "pass." So this skill does not trust any producer-written
verdict. It runs the fresh landing reviewer itself, at landing time, on the actual staged
diff (fresh reviewer, paths-only). The verdict is produced where it is consumed, by the
privileged human-invoked skill — nothing to forge.
For each staged patch the user asks to land, in order — any failure ⇒ skip & report, never silently apply:
/meta-apply 1,3
or all); default to applying nothing.gpt-6-astra
reviewer via spawn_agent (reasoning_effort: ultra, read-only, paths-only per
reviewer-independence.md) on the
staged .diff + its target. Ask: does this change improve the harness without
regressions; PASS or KILL + one-line reason. Include the scope-limits block from
review-scope-limits.md: this jury
judges ARIS's own mechanism, so an over-defensive KILL permanently blocks a good
patch. The block bans proposing new hash binding — it is not a reason to KILL a
patch that touches the existing provenance stamp. KILL ⇒ refuse. The human cannot
override a KILL — they may only pick among reviewer-PASSED survivors.stamp-provisional; it can complete this explicit
human-invoked operation but does not authorize future auto-curation. A
Claude/Gemini overlay or deterministic verifier uses strict stamp and may
record accepted. See
skill-governance.md.PENDING=".aris/meta/pending"
[ -d "$PENDING" ] || { echo "Nothing staged. Run /meta-optimize first."; exit 0; }
echo "Staged:"; cat "$PENDING/manifest.jsonl"Resolve provenance.py through the Codex manifest:
if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills-codex.txt ]; then
ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills-codex.txt 2>/dev/null) || true
fi
PROVENANCE=""
[ -n "${ARIS_REPO:-}" ] && [ -f "$ARIS_REPO/tools/provenance.py" ] && PROVENANCE="$ARIS_REPO/tools/provenance.py"
[ -z "$PROVENANCE" ] && [ -f tools/provenance.py ] && PROVENANCE="tools/provenance.py"
[ -n "$PROVENANCE" ] || { echo "ERROR: provenance.py unresolved" >&2; exit 1; }For every patch the user asked to land, read its staged .diff and target, then spawn the
fresh reviewer jury (Rule 2) — paths-only, no producer reasoning, no prior-round context.
Record {patch, jury_verdict, jury_review_id, one_line_reason}. Print a one-line result
per patch (PASS → eligible / KILL → refused: <reason>).
The producer may have written an advisory pre-screen into the manifest to help the human read the REPORT — ignore it for the landing decision. Only this fresh verdict counts.
For each patch that PASSED Step 1 and was named by the user:
.aris/meta/backups/<date>/<target> (use the Write tool
to copy contents; corpus paths are not Bash-writable when corpus_write_guard is
active — and the applier should use Write/Edit for corpus mutation anyway).python3 "$PROVENANCE" stamp-provisional "$TARGET" --author "$AUTHOR" \
--reviewer "$JURY_MODEL" --verdict-id "$JURY_REVIEW_ID"review_independence: same-family and
acceptance_status: provisional; is_auto_curatable remains false. If the
active overlay produced a cross-family result, use strict stamp instead..aris/meta/optimizations.jsonl:
{ts, patch, target, author_model, reviewer_model, jury_review_id, applied: true}.Per patch: LANDED <target> (+ backup path + provenance sidecar) or
REFUSED <patch>: <reason>. Remove landed patches from .aris/meta/pending/. Remind the
user a landed patch is revertable from its backup, and to test the changed skill next run.
A stamp records that a change passed a process (fresh landing review + human landing), not that it is correct. To prevent "approved-but-wrong with a stamp that vouches for it" (false-authority laundering — worse than no stamp, because a later auto-curator reads it as evidence):
verdict_id (auditable review) + content_hash (a later hand-edit
invalidates it).stamp-provisional; only an overlay or deterministic verifier may use strict
stamp.corpus_write_guard hook (if installed) additionally denies Bash corpus writes — it
does NOT gate Write/Edit, so it does not by itself stop this skill from editing the
corpus; the jury-at-landing + stamp discipline above is what governs Write/Edit
mutations (that discipline is procedure, not a hook-enforced mechanism)..aris/meta/pending/;
invents nothing of its own.Save each landing-jury reviewer call's trace per
review-tracing.md to
.aris/traces/meta-apply/<date>_run<NN>/ — the acquittal that landed a corpus change must
be forensically recoverable.
© wanshuiyin, 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 skills/skills-codex/meta-apply of wanshuiyin/Auto-claude-code-research-in-sleep.
Open the folder on GitHubat commit 26b95cf
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wanshuiyin/Auto-claude-code-research-in-sleep, which our catalogue first saw on October 7, 2026.
Meta Apply 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 |
|---|---|---|---|---|---|---|
| Meta Apply this skillwanshuiyin/Auto-claude-code-research-in-sleep | 17k | 1 repos | ~2.1k | Automated safety check: Notes | MIT | |
| Landing Optimizeraaron-he-zhu/aaron-marketing-skills | 2.9k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| Landingalirezarezvani/claude-skills | 28k | — | ~3.8k | Automated safety check: Pass | MIT | |
| SQL Optimizationgithub/awesome-copilot | 40k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Landing Optimizeraiskillstore/marketplace | 433 | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Agent Performance Optimizerruvnet/ruflo | 74k | 2 repos | ~3.6k | Automated safety check: Pass | MIT |
aaron-he-zhu/aaron-marketing-skills
A skill your agent uses when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a…
alirezarezvani/claude-skills
Generates a premium single-page HTML landing page with 3D CSS animations, GSAP scroll effects, and mouse-parallax depth.
github/awesome-copilot
Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server…
aiskillstore/marketplace
A skill your agent uses when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a…
ruvnet/ruflo
Agent skill for performance-optimizer - invoke with $agent-performance-optimizer
davila7/claude-code-templates
Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
wanshuiyin/Auto-claude-code-research-in-sleep
Builds an academic conference poster as a single HTML and CSS file with measurement-based gates, real paper figures and a print-ready PDF rendered through headless Chromium.
wanshuiyin/Auto-claude-code-research-in-sleep
Runs a mathematical proof project as a stateful pipeline of run directories: a local attempt first, then a manual GPT Pro handoff package, with an optional DeepSeek audit.
wanshuiyin/Auto-claude-code-research-in-sleep
Render an ARIS Markdown / JSON artifact (IDEAREPORT, AUTOREVIEW, KILLARGUMENT, PAPERPLAN, research-wiki state, etc.) into a single-file HTML view designed for human reading.
wanshuiyin/Auto-claude-code-research-in-sleep
Audit experiment integrity before claiming results. An agent skill from wanshuiyin/Auto-claude-code-research-in-sleep.
wanshuiyin/Auto-claude-code-research-in-sleep
Run the Anti-Autoresearch integrity-forensics DETERMINISTIC slice (numeric core + rules-only reporter) against a paper via a SHA-pinned thin launcher, then convert the verdict into a typed policy…
wanshuiyin/Auto-claude-code-research-in-sleep
Generate a long-form Chinese interview-prep cheat sheet on a specific ML/LLM topic — formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab).
Privileged applier that LANDS meta-optimize / corpus-audit patches the user approved, with a fresh landing review and human approval. Meta Apply is an agent skill from wanshuiyin/Auto-claude-code-research-in-sleep. Privileged applier that LANDS meta-optimize / corpus-audit patches the user approved, with a fresh landing review and human approval.
Meta Apply fits situations like: the user says meta apply; land the staged patches; after a /meta-optimize run.
Run `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a claude-code`. Or copy the skill folder (skills/skills-codex/meta-apply in wanshuiyin/Auto-claude-code-research-in-sleep) into .claude/skills/meta-apply in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a codex`. Or copy the skill folder (skills/skills-codex/meta-apply in wanshuiyin/Auto-claude-code-research-in-sleep) into .agents/skills/meta-apply 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 wanshuiyin/Auto-claude-code-research-in-sleep --skill meta-apply -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meta-apply, .gemini/skills/meta-apply, .github/skills/meta-apply and .opencode/skills/meta-apply in your project.
Going by SKILL.md and its folder, Meta Apply needs the command-line tools its instructions call (python3). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash(*), Read, Write, Edit, Grep, Glob.
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 notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Meta Apply is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.3k 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 Meta Apply: Landing Optimizer (aaron-he-zhu/aaron-marketing-skills, 2.9k stars), Landing (alirezarezvani/claude-skills, 28k stars), SQL Optimization (github/awesome-copilot, 40k stars) and Landing Optimizer (aiskillstore/marketplace, 433 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wanshuiyin (a GitHub user) maintains it in wanshuiyin/Auto-claude-code-research-in-sleep, which has 17,205 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 7, 2026.
Source: wanshuiyin/Auto-claude-code-research-in-sleep on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.