SKILLEMALL.ai

CC alibabacloud-mongodb-instances-manage

Alibaba Cloud MongoDB full lifecycle management: create/query/scale/delete standalone, replica set, sharded cluster instances. Covers node management, security (whitelist/security group), public & SRV address, password reset, renewal, billing conversion, cloud disk reconfiguration, maintenance window, backup, version upgrade, HA switchover, account & tag management. Triggers: "MongoDB", "create MongoDB", "dds instance", "list instances", "MongoDB scaling", "add Mongos/Shard node", "MongoDB whitelist", "reset password", "allocate public address", "SRV address", "MongoDB renewal", "billing type conversion", "cloud disk reconfiguration", "delete MongoDB instance", "maintenance window", "restart MongoDB", "MongoDB backup", "upgrade MongoDB version", "HA switchover", "MongoDB tags", "MongoDB account"

ClawHub Agent Skills author: alibabacloud v0.0.2 MIT-0 8 files body ≈ 7 978 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

Alibaba Cloud MongoDB full lifecycle management: create/query/scale/delete standalone, replica set, sharded cluster instances.

As a process C 56/100 · Has gaps — weak spots: steps, result and completion, running it twice

GeneratorMongoDBSecurityCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
C
85/100
safety, quality, tests
Safety 60%
99
Quality 40%
65
Run on models
none yet
Process rating
C
56/100
Has gaps
Steps w 15
0
Running it twice w 4
30
Result and completion w 14
40
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security references/cli-installation-guide.md:35
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    > **Note:** Package manager installation (`dpkg`/`rpm`/`yum`) requires root privileges. Run as root or prepend your preferred privilege escalation method.

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 7978 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 427, 454): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 56/100

  • 0Steps. Prose only: no discrete steps
  • 30Running it twice. 33 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 7978 tokens
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 28 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 806: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 21 example trigger phrases
  • +4Structure: 32 headings
  • +4Has examples (24 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
The skill is mostly coherent for managing Alibaba Cloud MongoDB, but it asks users to run mutable CLI/plugin installation steps and handle powerful cloud credentials and destructive database operations.
LLM: suspicious (high) · VirusTotal: · 16 Sept 2026