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AD quantinuumclaw

Enables building and deploying quantum computing applications with Quantinuum, Guppy, Selene, and Fly.io. Use for the OpenClaw Clinical Hackathon, clinical or healthcare projects (drug discovery, treatment optimization, patient stratification, trial randomization), quantum-powered web apps, deploying quantum algorithms to the cloud, or integrating quantum results into user-facing interfaces.

ClawHub Agent Skills author: Arun Nadarasa v0.1.0 27 files body ≈ 1 822 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructuretype 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
A
92/100
safety, quality, tests
Safety 60%
92
Quality 40%
91
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
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 references/flyio_config.md:21
      Pipe-to-shell installer from a well-known host (still executes remote code)
      curl -L https://fly.io/install.sh | sh
    • low Exfiltration read-dotenv assets/selene-template/README.md:14
      Reads a .env file
      cp .env.example .env
    • low Secrets in code secret-high-entropy-token scripts/lovable_integrate.py:383
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      (public_dir / "vite.svg").write_text('<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" heig
      detector
    • low Exfiltration read-dotenv scripts/setup_selene_service.py:321
      Reads a .env file (quoted — discussed, not commanded)
      cp .env.example .env
      quoted

    Files scanned: 27. 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 46/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 13 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
    • 85Steps. 35 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1822 tokens
    • low 11 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 394: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This skill is not clearly malicious, but it needs review because it can deploy public healthcare-oriented cloud services and handle secrets with weak default safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026