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CC Claude Code CLI for OpenClaw

Install, authenticate, and use Claude Code CLI as a native coding tool for any OpenClaw agent system.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 6 files · 1 script body ≈ 4 274 tokens Open the sourcegithub.com↗ analyzed 34 h ago

Install, authenticate, and use Claude Code CLI as a native coding tool for any OpenClaw agent system.

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

IntegrationSupabaseGitHubPeople and hiringtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
62/100
safety, quality, tests
Safety 60%
53
Quality 40%
75
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 11

    ✓ No critical or high findings

    Medium and low: 11
    • medium Dangerous commands cmd-shell-rc README.md:261
      Writes to a shell startup file
      echo 'export PATH="$PATH:$(npm bin -g)"' >> /root/.bashrc
    • medium Dangerous commands cmd-shell-rc scripts/install.sh:116
      Writes to a shell startup file
      echo -e "  ${GREEN}echo 'export CLAUDE_CODE_OAUTH_TOKEN=YOUR_TOKEN_HERE' >> ~/.bashrc${NC}"
    • medium Dangerous commands cmd-shell-rc scripts/install.sh:117
      Writes to a shell startup file
      echo -e "  ${GREEN}echo 'export CLAUDE_CODE_OAUTH_TOKEN=YOUR_TOKEN_HERE' >> ~/.profile${NC}"
    • medium Dangerous commands cmd-shell-rc scripts/install.sh:118
      Writes to a shell startup file
      echo -e "  ${GREEN}source ~/.bashrc${NC}"
    • medium Dangerous commands cmd-shell-rc scripts/install.sh:173
      Writes to a shell startup file
      echo 'export PATH="$PATH:$(npm bin -g)"' >> "$HOME/.bashrc"
    • medium Dangerous commands cmd-shell-rc scripts/install.sh:181
      Writes to a shell startup file
      echo 'export PATH="$PATH:$(npm bin -g)"' >> "$HOME/.profile"
    • medium Dangerous commands cmd-shell-rc SKILL.md:139
      Writes to a shell startup file
      echo "export CLAUDE_CODE_OAUTH_TOKEN=YOUR_OAUTH_TOKEN_HERE" >> /root/.bashrc
    • medium Dangerous commands cmd-shell-rc SKILL.md:140
      Writes to a shell startup file
      echo "export CLAUDE_CODE_OAUTH_TOKEN=YOUR_OAUTH_TOKEN_HERE" >> /root/.profile
    • medium Dangerous commands cmd-shell-rc SKILL.md:525
      Writes to a shell startup file
      echo 'export PATH="$PATH:$(npm bin -g)"' >> /root/.bashrc
    • low Dangerous commands cmd-privilege scripts/install.sh:121
      Privilege escalation / world-writable permissions (string literal in code, not executed)
      echo -e "  ${GREEN}echo 'CLAUDE_CODE_OAUTH_TOKEN=YOUR_TOKEN_HERE' | sudo tee -a /etc/environment${NC}"
      code literal

    A further 1 matches are quotations in this security skill's documentation and are not counted as findings.

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "openclaw"

    Process rating: all ten parameters 50/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 17 mutating operations with no state check
    • 40Consistency. Frontmatter name (Claude Code CLI for OpenClaw) differs from the folder (claude-code-cli-openclaw)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4274 tokens
    • 100Steps. 79 steps
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 17 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 101: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -218 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +4Structure: 54 headings
    • +3Step-by-step instructions: 79 items
    • +4Has examples (43 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.