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BF alist-cli

AList file management CLI for AI agents including Codex, Claude Code, and OpenClaw. Supports upload, download, list, mkdir, rm, mv, search, url. Auth via environment variables with auto-refresh. Trigger: file management, AList operations, upload/download.

ClawHub Agent Skills author: Kinema. v1.7.0 MIT-0 8 files · 1 script body ≈ 922 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 43/100 · Will not run — References files that are not bundled: references/openapi.json

IntegrationAI and agentsSoftware developmentInfrastructuretype 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
82/100
safety, quality, tests
Safety 60%
84
Quality 40%
79
Run on models
none yet
Process rating
F
43/100
Will not run
References files that are not bundled: references/openapi.json
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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

  1. The text references files that are not there: add them or drop the references.
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-shell-rc references/ONBOARDING.md:108
    Writes to a shell startup file
    echo 'export ALIST_URL="https://..."' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc references/ONBOARDING.md:109
    Writes to a shell startup file
    echo 'export ALIST_USERNAME="xxx"' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc references/ONBOARDING.md:110
    Writes to a shell startup file
    echo 'export ALIST_PASSWORD="xxx"' >> ~/.bashrc
  • low Secrets in code secret-password-literal scripts/alist_cli.py:391
    Hard-coded password / key literal (may be an example)
    password = args.args[1] if len(args.args) > 1 else os.environ.get(ENV_PASSWORD, "")

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/openapi.json
  • note frontmatter-key unknown frontmatter key "displayName"

Process rating: all ten parameters 43/100

Will not run. References files that are not bundled: references/openapi.json
  • 0Tools and files. 1 referenced file(s) missing: references/openapi.json
  • 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. 2 mutating operations with no state check
  • 100Steps. 30 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 922 tokens
  • low The response is described with custom markup (5 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
  • -32 of 2 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 255: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
The skill is a plausible AList file-management CLI, but it includes overbroad admin API references, privileged setup instructions, and plaintext credential persistence guidance that need manual review.
LLM: suspicious (high) · VirusTotal: · 16 Jul 2026