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BC openclaw-deploy

Interactive deployment guide for OpenClaw local capabilities. Walks through installing the Memory Stack (qmd + LosslessClaw), vid2md, WeChat plugin, and maintenance cron jobs — with confirmation gates between each phase. Run when setting up a new OpenClaw instance or adding capabilities to an existing one.

ClawHub Agent Skills author: OttoPrua v1.0.0 MIT-0 4 files body ≈ 3 381 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

ProcedureGitHubInfrastructuretype 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
B
89/100
safety, quality, tests
Safety 60%
94
Quality 40%
81
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Consistency w 8
40
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • medium Dangerous commands cmd-shell-rc SKILL.md:346
      Writes to a shell startup file
      echo 'export WECHAT_OCR_BIN=/path/to/wechat-ocr' >> ~/.zshrc
    • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:73
      Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
      - `bun`: `curl -fsSL https://bun.sh/install | bash`
      quoted

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "triggers"

    Process rating: all ten parameters 58/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (openclaw-deploy) differs from the folder (oc-deploy-guide)
    • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 4 branches
    • 100Steps. 6 steps
    • 100Execution cost. Instruction body is 3381 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (3 tags): a typed call is more reliable

    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)
    • +3Output format is not stated: the model decides each time
    • -230 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 307: enough signal without eating the budget
    • +4Structure: 32 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (42 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This is a transparent OpenClaw deployment guide that makes significant local changes only as part of its stated setup purpose and with user confirmation steps.
    LLM: benign (high) · VirusTotal: · 29 May 2026