SKILLEMALL.ai

DC alibabacloud-pai-rec-diagnosis

Alibaba Cloud PAI-Rec Engine Diagnostic and Configuration Validation Skill. Use for diagnosing PAI-Rec engine interface issues and validating engine configurations. Triggers: "PAI-Rec", "engine diagnosis", "engine config validation", "pairec", "recommendation engine".

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: alibabacloud-skills-team v0.0.3 MIT-0 13 files body ≈ 6 063 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
D
56/100
safety, quality, tests
Safety 60%
36
Quality 40%
86
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
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. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 10

  • high Dangerous commands cmd-pipe-to-shell references/troubleshooting-guide.md:52
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash
  • high Dangerous commands cmd-pipe-to-shell references/troubleshooting-guide.md:80
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash
Medium and low: 8
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:30
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:45
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:58
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:71
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-pipe-to-shell SKILL.md:35
    Downloads and executes remote code from an unrecognised host (pipe to shell) (quoted — discussed, not commanded)
    > run `curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash` to install/update,
    quoted
  • low Secrets in code secret-high-entropy-token references/config-validation.md:116
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | `FilterConfs[*].FilterType` | `User…ter`, `User…ter`, `AdjustCountFilter`, `PriorityAdjustCountFilter`, `Prio…rV2`, `ItemStateFilter`, `ItemCustomFilte
    table
  • low Secrets in code secret-high-entropy-token references/schema.json:394
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "User…ter",
    quoted
  • low Secrets in code secret-high-entropy-token scripts/validate.py:82
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "User…ter",
    quoted

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6063 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 57/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 7 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6063 tokens
  • 100Steps. 80 steps
  • 100Failures and branches. 7 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 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

  • +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
  • +5Description quotes 5 example trigger phrases
  • +3Description length 268: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 80 items
  • +4Has examples (19 code blocks)
  • +4Reference files are cited in the instructions (7 of 8)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

External checks

ClawHub: clean
This skill appears purpose-built for Alibaba Cloud PAI-Rec troubleshooting, but users should grant narrow read-only access and redact diagnostic data before sharing it.
LLM: benign (high) · VirusTotal: · 17 Jun 2026