Agent skill

Claude Skill

by LeoYeAI in LeoYeAI/openclaw-master-skills

A skill your agent uses when user asks to leverage claude or claude code to do something (e.g.

MITAuto-check passedDevelopment

Install Claude Skill

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill claude-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills claude-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/claude-skill .claude/skills/claude-skill && rm -rf skills-src

Use ~/.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/

Facts

Skill name
claude-skill
GitHub stars
2.2k
Token cost
~5.2k tokens
SKILL.md length
968 words
Files
3 (incl. references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when user asks to leverage claude or claude code to do something (e.g.

  • Works in 8 steps: Create Worktree → Launch Agent in tmux → Register Task → …
  • User asks to leverage claude
  • SKILL.md covers Prerequisites, CLI Quick Reference, Execution Modes and Full Workflow: Task → Merged PR, plus 5 more sections
  • Calls claude, jq and git

What it does

Claude Skill is an agent skill from LeoYeAI/openclaw-master-skills. Use when user asks to leverage claude or claude code to do something (e.g. implement a feature design or review codes, etc). Provides non-interactive automation mode for hands-off task execution without approval prompts.

Its SKILL.md is about 5.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `_meta.json` and `references/examples.md`).

It sits in Development, covering Code review. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • User asks to leverage claude
  • Claude code to do something (e.g

Example prompts

  • “/claude-skill”

Requirements

  • Python 3
  • Node.js

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Create Worktree
  2. Launch Agent in tmux
  3. Register Task
  4. Monitor & Steer
  5. Definition of Done
  6. Multi-Model Code Review
  7. Notify
  8. Cleanup

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • claude
    • jq
    • git
    • gh
    • pnpm
    • codex

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, gh and pnpm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Claude Skill loads about 5.2k tokens when it runs, and up to ~6k if it reads all its reference files. Until then it costs about 58 tokens; SKILL.md has 968 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~5.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 968 words, ~5,193 tokens.

Download SKILL.mdSave it as .claude/skills/claude-skill/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
claude-skill
description
Use when user asks to leverage claude or claude code to do something (e.g. implement a feature design or review codes, etc). Provides non-interactive automation mode for hands-off task execution without approval prompts.

Claude Code Agent Skill

Operate Claude Code as a managed coding agent — from worktree setup through PR merge.

Prerequisites

bash
claude --version  # Verify installed
# Install: npm install -g @anthropic-ai/claude-code
tmux -V             # tmux required for full workflow

CLI Quick Reference

FlagEffect
-p "prompt"Non-interactive one-shot, exits when done
--dangerously-skip-permissionsSkip all permission prompts (safe in containers/VMs)
--permission-mode acceptEditsAuto-accept file edits, still prompt for shell commands
--permission-mode planRead-only analysis, no modifications
--model <model>Model selection (e.g. claude-sonnet-4-6)
--allowedTools "Bash,Read,Write,Edit"Restrict available tools
--disallowedTools "Bash,Write"Block specific tools
--append-system-prompt "..."Add custom instructions to system prompt
--output-format jsonStructured JSON output with cost/duration metadata
--output-format stream-jsonStreaming JSON (each message as it arrives)
--continue / -cContinue most recent conversation
--resume <id> / -r <id>Resume specific session by ID
--mcp-config <file>Load MCP server configuration
--verboseEnable verbose debug logging

Execution Modes

Quick Mode — Small Tasks

For trivial fixes, one-file changes, or analysis. Use -p (non-interactive).

Output capture: Always redirect output to a log file so it's readable regardless of PTY availability. Use --output-format stream-json for structured, parseable progress events (each message arrives as a separate JSON line).

bash
LOG_FILE="/tmp/claude-quick-${TASK_ID:-$$}.log"

# Via OpenClaw exec — use background=true + pty=true, NO hard timeout
# pty=true ensures claude CLI flushes output properly (no buffering issues)
# (hard timeout kills the process; instead we poll and extend)
# Redirect both stdout and stderr to log file via tee so output is always captured.
# In -p mode (non-interactive), | tee is safe — no TTY detection issues.
exec(command="claude -p 'fix the typo in README.md' --dangerously-skip-permissions --output-format stream-json 2>&1 | tee -a $LOG_FILE",
     workdir="/path/to/project", background=true, pty=true)

PTY fallback: If pty=true is unavailable (some containers, CI runners), the command still works because -p mode is non-interactive — it doesn't rely on isatty(stdout). The 2>&1 | tee ensures both stdout and stderr are captured to the log file regardless of PTY status. Without PTY, you lose color output but all content is preserved.

Adaptive Timeout (Poll-and-Extend)

Do NOT use timeout= for claude tasks. Instead, use background execution with periodic polling. This prevents premature kills on long-running tasks:

  1. Launch with background=true (no timeout)
  2. Poll every ~5 min with process(action="poll", sessionId=<id>, timeout=300000)
  3. If process is still running → check log file for new output
  4. If process exited → check exit code and log file, done
  5. Safety net: if no new output for 12 hours, ask user before killing
  6. Safety net: if output is repeating (loop detection), ask user

Persistent polling state: Store polling metadata in the task registry so a restarted orchestrator agent can resume monitoring without losing state:

Registry fields for Quick Mode tasks:
  "lastOutputHash": "<sha256 of last 20 lines>",
  "lastCheckedAt": <unix timestamp>,
  "silentRounds": <int>,
  "repeatingRounds": <int>
Poll loop (agent behavior, not a script):

  poll_interval = 5 min (300000 ms)
  max_silent_rounds = 144  (= 12 hours with no new output → ask user)
  max_repeating_rounds = 12 (= 1 hour of identical output → likely stuck)

  # Restore state from registry if resuming after agent restart
  silent_rounds = registry[task_id].silentRounds ?? 0
  repeating_rounds = registry[task_id].repeatingRounds ?? 0
  last_output_hash = registry[task_id].lastOutputHash ?? ""

  repeat:
    result = process(action="poll", sessionId=<id>, timeout=300000)
    if result.completed:
      → check exit code, read $LOG_FILE, report result
      → break
    else:
      # Read latest output directly from the log file
      new_output = tail -20 "$LOG_FILE"
      new_hash = sha256(new_output)

      if new_hash != last_output_hash and new_output != "":
        if last_output_hash != "" and output_looks_similar(new_output, last_output):
          repeating_rounds += 1   # output changing but repetitive (loop)
          silent_rounds = 0
        else:
          silent_rounds = 0       # genuinely new output, keep going
          repeating_rounds = 0
        last_output_hash = new_hash
      else:
        silent_rounds += 1

      # Persist state to registry (survives agent restart)
      update_registry(task_id, {
        lastOutputHash: new_hash,
        lastCheckedAt: now(),
        silentRounds: silent_rounds,
        repeatingRounds: repeating_rounds
      })

      if silent_rounds >= max_silent_rounds:
        → notify user: "Claude has been silent for 12 hours, kill or keep waiting?"
        → wait for user decision
      if repeating_rounds >= max_repeating_rounds:
        → notify user: "Claude appears stuck in a loop (1h of repeated output), kill or keep waiting?"
        → wait for user decision

This way tasks that need 5 min or several hours both work without premature kills.

Full Mode — Features, Bugfixes, Refactors

For non-trivial tasks, use the full workflow below. This gives you:

  • Isolated worktree — no conflicts with other work
  • tmux session — mid-task steering without killing the agent
  • Task tracking — know what's running at all times
  • Quality gates — Definition of Done checklist
  • Smart retries — don't waste tokens on repeated failures

Full Workflow: Task → Merged PR

Step 1: Create Worktree

Isolate each task in its own worktree and branch:

bash
TASK_ID="feat-custom-templates"
BRANCH="feat/$TASK_ID"
REPO_ROOT=$(git rev-parse --show-toplevel)
WORKTREE="/tmp/worktrees/$TASK_ID"

git worktree add -b "$BRANCH" "$WORKTREE" origin/main
cd "$WORKTREE"

# Install dependencies (adapt to your stack)
pnpm install   # or: npm install / go mod tidy / pip install -r requirements.txt
Step 2: Launch Agent in tmux

Start Claude Code in interactive mode (no -p) so you can steer mid-task. Important: Use tmux pipe-pane to log output — do NOT use | tee because it turns stdout into a pipe, which breaks interactive mode (claude detects !isatty(stdout) and may disable interactive features, breaking send-keys steering).

Critical: Set up pipe-pane BEFORE sending the command. Otherwise early output (startup messages, fast crashes) is lost.

bash
LOG_FILE="/tmp/worktrees/$TASK_ID/claude-output.log"
MAX_LOG_SIZE=$((100 * 1024 * 1024))  # 100 MB safety cap

# 1. Create session with an idle shell first
tmux new-session -d -s "$TASK_ID" -c "$WORKTREE"

# 2. Start pipe-pane BEFORE the command runs — captures ALL output from the start
#    Strip ANSI escape codes so log files are clean and grep-parseable
tmux pipe-pane -t "$TASK_ID" -o "sed 's/\x1b\[[0-9;]*[a-zA-Z]//g' >> $LOG_FILE"

# 3. NOW send the command — all output is captured
tmux send-keys -t "$TASK_ID" "claude --dangerously-skip-permissions \
  'Your detailed prompt here.

When completely finished:
1. Commit all changes with descriptive messages
2. Push the branch: git push -u origin $BRANCH
3. Create PR: gh pr create --fill
4. Notify: openclaw system event --text \"Done: $TASK_ID\" --mode now'" Enter

Log file management: For very long-running tasks, the log file can grow large. Monitor its size and rotate if needed:

bash
LOG_SIZE=$(stat -c%s "$LOG_FILE" 2>/dev/null || echo 0)
if [ "$LOG_SIZE" -gt "$MAX_LOG_SIZE" ]; then
  mv "$LOG_FILE" "${LOG_FILE}.old"
  # pipe-pane will create a new file on next write
fi

Why interactive mode (no -p)?

  • Allows mid-task steering via tmux send-keys
  • Agent can be redirected without killing and restarting
  • --dangerously-skip-permissions is safe in container/sandbox environments

Note on stdout/stderr: In tmux, both stdout and stderr from the process flow through the PTY and are captured by pipe-pane. They are mixed together — you cannot separate them after capture. For error diagnosis, grep for keywords like error, fail, panic in the clean (ANSI-stripped) log file.

Show full SKILL.md (391 more words)Show less
Step 3: Register Task

Track all active tasks in a JSON registry. Use flock for atomic updates to prevent race conditions when multiple agents run in parallel.

bash
mkdir -p "$REPO_ROOT/.clawd"
TASKS_FILE="$REPO_ROOT/.clawd/active-tasks.json"

# Initialize if not exists
[ -f "$TASKS_FILE" ] || echo '{"tasks":[]}' > "$TASKS_FILE"

# Get the PID of the claude process inside tmux for reliable status checks
PANE_PID=$(tmux display-message -t "$TASK_ID" -p '#{pane_pid}')

# Register — use flock to prevent concurrent write races
(
  flock -x 200
  jq --arg id "$TASK_ID" --arg branch "$BRANCH" --arg wt "$WORKTREE" \
    --arg pane_pid "$PANE_PID" \
    '.tasks += [{
      "id": $id,
      "agent": "claude",
      "branch": $branch,
      "worktree": $wt,
      "tmuxSession": $id,
      "panePid": ($pane_pid | tonumber),
      "status": "running",
      "startedAt": (now|floor),
      "pr": null,
      "retries": 0,
      "checks": {},
      "lastOutputHash": "",
      "lastCheckedAt": (now|floor),
      "silentRounds": 0,
      "repeatingRounds": 0
    }]' "$TASKS_FILE" > /tmp/tasks.$$.json && mv /tmp/tasks.$$.json "$TASKS_FILE"
) 200>"$TASKS_FILE.lock"
Step 4: Monitor & Steer
bash
# --- Process status check (reliable — checks actual process, not just tmux session) ---

# Method 1: Check if the claude process inside the pane is alive
PANE_PID=$(tmux display-message -t "$TASK_ID" -p '#{pane_pid}' 2>/dev/null)
if [ -z "$PANE_PID" ]; then
  echo "tmux session gone"
elif pgrep -P "$PANE_PID" > /dev/null 2>&1; then
  echo "running"
else
  echo "process exited (tmux session still open)"
  # Get exit code from the shell inside tmux
  tmux send-keys -t "$TASK_ID" 'echo "EXIT_CODE=$?"' Enter
fi

# Method 2: Use tmux's pane_dead flag (if remain-on-exit is set)
# tmux display-message -t "$TASK_ID" -p '#{pane_dead}'  # 1 = process exited

# --- View output ---

# Full output history from log file (ANSI-stripped, grep-friendly)
tail -100 "/tmp/worktrees/$TASK_ID/claude-output.log"

# Search for errors in clean log
grep -i "error\|fail\|panic" "/tmp/worktrees/$TASK_ID/claude-output.log"

# Live view (raw tmux pane, may contain ANSI codes — use for quick glance only)
tmux capture-pane -t "$TASK_ID" -p -S -50

# --- Mid-task steering (DON'T kill — redirect!) ---

# Agent going the wrong direction?
tmux send-keys -t "$TASK_ID" "Stop. Focus on the API layer first, not the UI." Enter

# Agent missing context?
tmux send-keys -t "$TASK_ID" "The schema is in src/types/template.ts. Use that." Enter

# Agent's context window filling up?
tmux send-keys -t "$TASK_ID" "Focus only on these 3 files: api.ts, handler.ts, types.ts" Enter

# Agent needs test guidance?
tmux send-keys -t "$TASK_ID" "Run 'npm test -- --grep auth' to verify your changes." Enter

Monitoring cadence: Check every 5-10 minutes, not every 30 seconds. Agents need time to work.

Step 5: Definition of Done

A PR is NOT ready for review until all checks pass:

✅ PR created              → gh pr list --head "$BRANCH"
✅ No merge conflicts       → gh pr view $PR_NUM --json mergeable -q '.mergeable'
✅ CI passing               → gh pr checks $PR_NUM
✅ AI code review passed    → at least one cross-model review (see Step 6)
✅ UI screenshots included  → (if applicable) screenshot in PR description

Quick inline check:

bash
PR_NUM=$(gh pr list --head "$BRANCH" --json number -q '.[0].number')
echo "PR: #$PR_NUM"
gh pr checks "$PR_NUM"
gh pr view "$PR_NUM" --json mergeable -q '.mergeable'
Step 6: Multi-Model Code Review

Review with a different model than the one that wrote the code. Different models catch different issues:

bash
DIFF=$(gh pr diff "$PR_NUM")

# Option A: Codex reviews Claude's code (best for edge cases & logic errors)
echo "$DIFF" | codex exec -s read-only \
  "Review this PR diff. Focus on: bugs, edge cases, missing error handling, 
   race conditions, security issues. Be specific — cite file and line numbers.
   Output format: list of issues with severity (critical/warning/info)."

# Option B: Claude reviews with security focus
echo "$DIFF" | claude -p \
  --append-system-prompt "You are a security-focused code reviewer. Flag only critical issues." \
  "Review this diff for security vulnerabilities, injection risks, and logic errors."

Post review results to PR:

bash
gh pr comment "$PR_NUM" --body "## AI Code Review

$REVIEW_OUTPUT"

Update task registry:

bash
(
  flock -x 200
  jq --arg id "$TASK_ID" \
    '(.tasks[] | select(.id == $id)).checks.codeReviewPassed = true' \
    "$TASKS_FILE" > /tmp/tasks.$$.json && mv /tmp/tasks.$$.json "$TASKS_FILE"
) 200>"$TASKS_FILE.lock"
Step 7: Notify

If you included the notify command in the agent prompt (Step 2), the agent self-notifies on completion.

Otherwise, notify after DoD passes:

bash
openclaw system event --text "✅ PR #$PR_NUM ready for review: $TASK_ID — all checks passed" --mode now

Update task status:

bash
(
  flock -x 200
  jq --arg id "$TASK_ID" --argjson pr "$PR_NUM" \
    '(.tasks[] | select(.id == $id)) |= (.status = "done" | .pr = $pr | .completedAt = (now|floor))' \
    "$TASKS_FILE" > /tmp/tasks.$$.json && mv /tmp/tasks.$$.json "$TASKS_FILE"
) 200>"$TASKS_FILE.lock"
Step 8: Cleanup

After PR is merged:

bash
git worktree remove "$WORKTREE" 2>/dev/null
git branch -d "$BRANCH" 2>/dev/null

# Remove from registry
(
  flock -x 200
  jq --arg id "$TASK_ID" '.tasks = [.tasks[] | select(.id != $id)]' \
    "$TASKS_FILE" > /tmp/tasks.$$.json && mv /tmp/tasks.$$.json "$TASKS_FILE"
) 200>"$TASKS_FILE.lock"

Smart Retry Strategy

When an agent fails, analyze the failure and adapt the prompt — don't just re-run blindly.

Failure TypeSymptomRetry Strategy
Context overflowAgent loops, produces garbage, or stops mid-taskNarrow scope: "Focus only on files X, Y, Z"
Wrong directionAgent implements something unrelated to intentCorrect intent: "Stop. Customer wanted X, not Y. Spec: ..."
Missing infoAgent makes wrong assumptions about architectureAdd context: "Auth uses JWT, see src/auth/jwt.ts"
CI failureTests, lint, or typecheck fail after PRAttach CI log: "Fix these test failures: ..."
Build failureDependencies missing or incompatiblePre-install deps before retry

Max 3 retries. After that, escalate to human.

bash
RETRY=$((RETRY + 1))
if [ "$RETRY" -gt 3 ]; then
  openclaw system event --text "BLOCKED: $TASK_ID failed after 3 retries — needs human help" --mode now
  (
    flock -x 200
    jq --arg id "$TASK_ID" '(.tasks[] | select(.id == $id)).status = "blocked"' \
      "$TASKS_FILE" > /tmp/tasks.$$.json && mv /tmp/tasks.$$.json "$TASKS_FILE"
  ) 200>"$TASKS_FILE.lock"
  exit 1
fi

# Capture what went wrong — prefer log file over tmux scrollback
LOG_FILE="/tmp/worktrees/$TASK_ID/claude-output.log"
if [ -f "$LOG_FILE" ]; then
  # Log file is ANSI-stripped (clean text) — extract error-relevant lines
  # Take last 500 lines, but also grep for error context
  FAILURE_LOG=$(tail -500 "$LOG_FILE")
  ERROR_LINES=$(grep -n -i "error\|fail\|panic\|exception\|traceback" "$LOG_FILE" | tail -50)
  if [ -n "$ERROR_LINES" ]; then
    FAILURE_LOG="=== Error lines ===
$ERROR_LINES

=== Last 500 lines ===
$FAILURE_LOG"
  fi
else
  FAILURE_LOG=$(tmux capture-pane -t "$TASK_ID" -p -S -200)
fi
CI_LOG=$(gh pr checks "$PR_NUM" 2>/dev/null || echo "no PR yet")
tmux kill-session -t "$TASK_ID" 2>/dev/null

# Archive old log, start fresh for retry
[ -f "$LOG_FILE" ] && mv "$LOG_FILE" "${LOG_FILE}.retry$((RETRY - 1))"

# Respawn — set up pipe-pane BEFORE sending command (captures all output)
tmux new-session -d -s "$TASK_ID" -c "$WORKTREE"
tmux pipe-pane -t "$TASK_ID" -o "sed 's/\x1b\[[0-9;]*[a-zA-Z]//g' >> $LOG_FILE"
tmux send-keys -t "$TASK_ID" "claude --dangerously-skip-permissions \
  'Previous attempt failed. Error output:
$FAILURE_LOG

CI status: $CI_LOG

Fix the issues above and complete the original task.
[...your enriched instructions here...]

When done: commit, push, gh pr create --fill, then run:
openclaw system event --text \"Done: $TASK_ID (retry $RETRY)\" --mode now'" Enter

# Update registry with flock
PANE_PID=$(tmux display-message -t "$TASK_ID" -p '#{pane_pid}')
(
  flock -x 200
  jq --arg id "$TASK_ID" --argjson r "$RETRY" --arg pane_pid "$PANE_PID" \
    '(.tasks[] | select(.id == $id)) |= (.retries = $r | .status = "running" | .panePid = ($pane_pid | tonumber) | .silentRounds = 0 | .repeatingRounds = 0 | .lastOutputHash = "")' \
    "$TASKS_FILE" > /tmp/tasks.$$.json && mv /tmp/tasks.$$.json "$TASKS_FILE"
) 200>"$TASKS_FILE.lock"

Parallel Execution

Run multiple agents simultaneously on different tasks. Important: Always set up pipe-pane before sending the command to avoid losing early output. Use ANSI stripping for clean logs.

bash
# Helper: launch an agent in tmux with proper output capture
launch_agent() {
  local TASK_ID="$1" WORKTREE="$2" PROMPT="$3"
  local LOG_FILE="$WORKTREE/claude-output.log"

  # 1. Create session with idle shell
  tmux new-session -d -s "$TASK_ID" -c "$WORKTREE"
  # 2. Start pipe-pane BEFORE command (captures everything, ANSI-stripped)
  tmux pipe-pane -t "$TASK_ID" -o "sed 's/\x1b\[[0-9;]*[a-zA-Z]//g' >> $LOG_FILE"
  # 3. Send command
  tmux send-keys -t "$TASK_ID" "$PROMPT" Enter
}

# Task 1: Feature
git worktree add -b feat/auth /tmp/worktrees/feat-auth origin/main
launch_agent "feat-auth" "/tmp/worktrees/feat-auth" \
  "cd /tmp/worktrees/feat-auth && pnpm install && claude --dangerously-skip-permissions 'Implement JWT auth...'"

# Task 2: Bugfix
git worktree add -b fix/payments /tmp/worktrees/fix-payments origin/main
launch_agent "fix-payments" "/tmp/worktrees/fix-payments" \
  "cd /tmp/worktrees/fix-payments && pnpm install && claude --dangerously-skip-permissions 'Fix payment webhook...'"

# Dashboard: check all agents (uses process check, not just has-session)
echo "=== Agent Status ==="
for s in $(tmux ls -F '#{session_name}' 2>/dev/null); do
  PANE_PID=$(tmux display-message -t "$s" -p '#{pane_pid}' 2>/dev/null)
  if [ -z "$PANE_PID" ]; then
    STATUS="(session gone)"
  elif pgrep -P "$PANE_PID" > /dev/null 2>&1; then
    STATUS="running"
  else
    STATUS="process exited"
  fi
  LOG="/tmp/worktrees/$s/claude-output.log"
  LAST_LINE=$(tail -1 "$LOG" 2>/dev/null || echo "(no log)")
  echo "  $s: $STATUS | last: $LAST_LINE"
done

Multi-Turn Conversations

For complex tasks that need iterative refinement:

bash
# Start session, capture ID
session_id=$(claude -p "analyze the codebase architecture" \
  --output-format json | jq -r '.session_id')

# Continue with context from previous turn
claude -r "$session_id" -p "now implement the changes we discussed" \
  --dangerously-skip-permissions

# Resume in non-interactive mode
claude -r "$session_id" -p "fix the remaining test failures" \
  --dangerously-skip-permissions

Best Practices

Prompt Quality
  • Include file paths: "The entry point is src/index.ts, config in src/config/"
  • Include schemas/types: Paste relevant type definitions into the prompt
  • Include test commands: "Verify with: npm test -- --grep auth"
  • Include commit convention: "Use conventional commits: feat:, fix:, chore:"
  • Include error logs: When retrying, always attach the failure output
Scope Management
  • One task per agent — don't ask for "refactor everything"
  • Pre-install dependencies before launching the agent
  • Be specific — "Add rate limiting to POST /api/users" not "improve the API"
When to Interrupt (Ask Human)
  • Destructive operations (drop tables, force push main)
  • Security decisions (expose credentials, change auth)
  • Ambiguous requirements with significant trade-offs
  • All other decisions: proceed autonomously

Examples

See references/examples.md for additional usage scenarios.

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/claude-skill of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • references/examples.md

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Claude Skill 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.

Claude Skill compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Claude Skill this skillLeoYeAI/openclaw-master-skills2.2k—~5.2kAutomated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
Backend Code Reviewlangflow-ai/langflow155k—~3.5kAutomated safety check: NotesMIT
Mole Bug Patternstw93/Mole70k—~2kAutomated safety check: PassGPL-3.0
Backend Code Reviewlanggenius/dify158k—~676Automated safety check: PassCustom licence

Similar skills

  • PR Babysitter

    openinterpreter/openinterpreter

    Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.

    69k GitHub starsUsed in 3 repos~4.2k tokens
    DevelopmentAuto-check passed
  • Code Review Checklist

    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.

    78k GitHub starsUsed in 5 repos~1.1k tokens
    DevelopmentAuto-check passed
  • Backend Code Review

    langflow-ai/langflow

    Review backend code for quality, security, maintainability, and best practices based on established checklist rules.

    155k GitHub stars~3.5k tokensUpdated yesterday
    DevelopmentAuto-check: notes
  • A catalog of recurring bug shapes in the Mole Mac cleaner, used to review safety-sensitive diffs for deletion safety, unbounded commands, shell traps and weak tests.

    70k GitHub stars~2k tokensUpdated yesterday
    DevelopmentAuto-check passed
  • Backend Code Review

    langgenius/dify

    Reviews backend code under api/ for concrete, reproducible defects, routes to rule packs for architecture, schema, repositories and SQLAlchemy, and ranks findings from P0 to P3.

    158k GitHub stars~676 tokensUpdated today
    DevelopmentAuto-check passed
  • WooCommerce Code Review

    woocommerce/woocommerce

    Reviews WooCommerce code changes against the project's standards, flagging backend PHP architecture, naming, documentation, data integrity and testing violations.

    11k GitHub starsUsed in 3 repos~1.1k tokens
    DevelopmentAuto-check passed

More from LeoYeAI/openclaw-master-skills

All 1,235 skills in this repo
  • DevOps Pipeline Management

    LeoYeAI/openclaw-master-skills

    Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.

    2.2k GitHub stars~4.2k tokensUpdated 2 mo ago
    Auto-check: notes
  • Feishu Document Collaboration

    LeoYeAI/openclaw-master-skills

    Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.

    2.2k GitHub stars~2k tokensUpdated 2 mo ago
    Auto-check passed
  • Files Memory System

    LeoYeAI/openclaw-master-skills

    Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.

    2.2k GitHub stars~3.8k tokensUpdated 2 mo ago
    Auto-check passed
  • GEO-Claw AI Visibility Agent

    LeoYeAI/openclaw-master-skills

    Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.

    2.2k GitHub stars~4.7k tokensUpdated 2 mo ago
    Auto-check passed
  • Google Workspace CLI

    LeoYeAI/openclaw-master-skills

    Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.

    2.2k GitHub stars~2.6k tokensUpdated 2 mo ago
    Auto-check: notes
  • HealthFit Health Advisors

    LeoYeAI/openclaw-master-skills

    Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.

    2.2k GitHub stars~4.4k tokensUpdated 2 mo ago
    Auto-check passed

Categories

Questions about Claude Skill

What does Claude Skill do?

A skill your agent uses when user asks to leverage claude or claude code to do something (e.g. Claude Skill is an agent skill from LeoYeAI/openclaw-master-skills.g.

When should I use Claude Skill?

Claude Skill fits situations like: user asks to leverage claude; Claude code to do something (e.g.

How do I install Claude Skill in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill claude-skill -a claude-code`. Or copy the skill folder (skills/claude-skill in LeoYeAI/openclaw-master-skills) into .claude/skills/claude-skill in your project. Claude Code loads it when a task matches its description.

How do I install Claude Skill in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill claude-skill -a codex`. Or copy the skill folder (skills/claude-skill in LeoYeAI/openclaw-master-skills) into .agents/skills/claude-skill in your project. Codex loads it when a task matches its description.

Can I use Claude Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill claude-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/claude-skill, .gemini/skills/claude-skill, .github/skills/claude-skill and .opencode/skills/claude-skill in your project.

What does Claude Skill need to run?

Going by SKILL.md and its folder, Claude Skill needs the command-line tools its instructions call (claude, jq, git, gh, pnpm and codex). Our summary lists: Python 3; Node.js.

Does Claude Skill access the network?

SKILL.md contains no URLs. Its commands use git and gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Claude Skill safe to install?

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.

What licence does Claude Skill use?

Claude Skill is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Claude Skill use?

About 5.2k tokens (SKILL.md is roughly 21k 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 807 tokens, read only when the agent opens those files.

What are the alternatives to Claude Skill?

Skills that share tags, products or a category with Claude Skill: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Backend Code Review (langflow-ai/langflow, 155k stars) and Mole Bug Patterns (tw93/Mole, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Claude Skill?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,160 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.