SKILLEMALL.ai

BD AndonQ

腾讯云 AndonQ 工单与智能客服助手 — 不切窗口、不排队,即刻获得腾讯云全产品线专业解答。支持工单查询(列表/详情/流水)、集团工单与需求单管理,以及腾讯云全产品线智能问答。当用户查询工单、查看工单详情、咨询腾讯云产品问题(如 CVM、轻量应用服务器、COS 等)、查询集团工单/需求单,或要求找人工客服时使用。

ClawHub Agent Skills author: AutoClaw v1.0.1 MIT-0 16 files body ≈ 2 968 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
90
Quality 40%
68
Run on models
none yet
Process rating
D
41/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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:43
    Writes to a shell startup file
    echo 'export TENCENTCLOUD_SECRET_ID="your-secret-id"' >> ~/.zshrc
  • medium Dangerous commands cmd-shell-rc SKILL.md:44
    Writes to a shell startup file
    echo 'export TENCENTCLOUD_SECRET_KEY="your-secret-key"' >> ~/.zshrc

Files scanned: 16. 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)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 41/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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
  • 40Consistency. Frontmatter name (AndonQ) differs from the folder (tencent-andon)
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 100Steps. 57 steps
  • 100Execution cost. Instruction body is 2968 tokens
  • 100Running it twice. No mutating operations

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
  • -33 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 159: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 57 items
  • +4Has examples (23 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This skill is a disclosed Tencent Cloud support assistant that uses user-provided Tencent credentials to read ticket data and send SmartQA questions to Tencent Cloud, with no artifact-backed evidence of hidden exfiltration or destructive behavior.
LLM: benign (high) · VirusTotal: · 12 Aug 2026