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DB alibabacloud-lindorm-agent-skill

Use this Skill for Alibaba Cloud Lindorm work: instance lifecycle and configuration, networking and access control, monitoring, performance, storage, connection diagnosis, backup, migration, permissions (including Lindorm SQL user management with `CREATE USER` and `GRANT`), slow queries, SQL development, and Search, vector, graph, AI, multimodal, or knowledge-base workflows. Trigger on Lindorm product or CLI terms such as LindormTable, LindormTSDB, LindormSearch, Lindorm AI, HBase/AliHBase, lindormcli, Lindorm CLI, `aliyun lindorm`, or Chinese requests mentioning 宽表引擎、时序引擎、搜索引擎、向量检索、图引擎、白名单、实例创建/扩缩容/释放. Use this Skill's references or official Alibaba Cloud documentation; do not invent Lindorm-specific facts from general training knowledge.

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: alibabacloud v0.0.3 MIT-0 33 files body ≈ 8 065 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

Use this Skill for Alibaba Cloud Lindorm work: instance lifecycle and configuration, networking and access control, monitoring, performance, storage…

As a process B 78/100 · Nearly there — weak spots: execution cost, running it twice, progress reporting

ProcedureInfrastructureAI and agentsSoftware developmenttype 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
D
63/100
safety, quality, tests
Safety 60%
58
Quality 40%
70
Run on models
none yet
Process rating
B
78/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Execution cost w 6
40
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 · 9

  • high Dangerous commands cmd-pipe-to-shell references/03-ref/related-commands.md:24
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    > curl -fsSL https://lindorm-open-api-cli.oss-cn-hangzhou.aliyuncs.com/scripts/install.sh | sh
Medium and low: 8
  • medium Dangerous commands cmd-privilege references/03-ref/cli-installation-guide.md:33
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/03-ref/cli-installation-guide.md:48
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/03-ref/cli-installation-guide.md:61
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/03-ref/cli-installation-guide.md:74
    Privilege escalation / world-writable permissions
    sudo mv aliyun /usr/local/bin/
  • low Secrets in code secret-high-entropy-token references/02-ops/network-access-control.md:140
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    | Update | `UpdateInstanceSecurityGroups` | `Modi…ups` | `<arch> instance security-group update <id>` |
    placeholder
  • low Secrets in code secret-password-literal references/02-ops/user-permission.md:392
    Hard-coded password / key literal (may be an example)
    ALTER USER employee_username SET PASSWORD = 'RandomStrongPassword!@#$%123456';
  • low Secrets in code secret-password-literal references/02-ops/user-permission.md:493
    Hard-coded password / key literal (may be an example)
    ALTER USER existing_username SET PASSWORD = 'NewP…123!';
  • low Secrets in code secret-high-entropy-token references/03-ref/related-commands.md:657
    High-entropy token-like string (may be an id, hash or a credential)
    | `instance security-group update` | UpdateInstanceSecurityGroups | Modi…ups |

Files scanned: 33. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 8065 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 282, 298, 299, 302): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 78/100

  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 18 mutating operations with no state check
  • 40Execution cost. Instruction body is 8065 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 60Failures and branches. 2 branches
  • 85Steps. 22 steps, 2 vague phrases
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The skill ranks results itself: that belongs to the system behind the tool, not the model
  • low The response is described with custom markup (8 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)
  • -5TODO / placeholder text left in the skill
  • -217 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 749: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 22 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)

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

External checks

ClawHub: suspicious
The skill is a legitimate Lindorm operations guide, but it needs Review because it mixes real cloud mutation authority with unsafe or contradictory credential, install, and permission-management examples.
LLM: suspicious (high) · 9 Oct 2026