SKILLEMALL.ai

AD agent-init

Initialize and configure OpenClaw agent workspace MD files (AGENTS.md, SOUL.md, IDENTITY.md, USER.md, TOOLS.md, BOOTSTRAP.md, HEARTBEAT.md). Use when: setting up a new agent, customizing agent personality/behavior, configuring agent workspace, or checking/fixing agent environment (Python/uv). Provides interactive interview workflow before generating files. Supports both container and external (host) OpenClaw instances.

ClawHub Agent Skills author: teamclaw v1.0.0 MIT-0 6 files · 1 script body ≈ 1 145 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
92
Quality 40%
87
Run on models
none yet
Process rating
D
45/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Dangerous commands cmd-pipe-to-shell-known-host scripts/check-env.sh:45
      Pipe-to-shell installer from a well-known host (still executes remote code)
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • low Dangerous commands cmd-pipe-to-shell-known-host references/openclaw-workspace.md:48
      Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
      - If `uv` is missing, install: `curl -LsSf https://astral.sh/uv/install.sh | sh`
      quoted
    • low Dangerous commands cmd-pipe-to-shell-known-host scripts/check-env.sh:81
      Pipe-to-shell installer from a well-known host (still executes remote code) (string literal in code, not executed)
      echo "⚠️  uv is missing. Run: curl -LsSf https://astral.sh/uv/install.sh | sh"
      code literal
    • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:87
      Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
      - If uv missing: `curl -LsSf https://astral.sh/uv/install.sh | sh`
      quoted

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 45/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 40Consistency. Frontmatter name (agent-init) differs from the folder (whois)
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 100Steps. 35 steps
    • 100Execution cost. Instruction body is 1145 tokens
    • 100Running it twice. Mutating operations check current state

    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
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +3Description length 422: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a user-directed OpenClaw workspace initializer with one disclosed setup risk: an optional command that installs uv by running a remote script.
    LLM: benign (high) · VirusTotal: · 29 May 2026