SKILLEMALL.ai

BB huawei-cloud-cloudrobo-dataset

Manage CloudRobo data processing (proc-tasks) and data evaluation (eval-tasks) — query algorithms, create/list/show/update/delete/restart tasks; poll task status until terminal; retrieve system and job logs; download logs; preview output data and frames; discover available algorithms from the asset marketplace; orchestrate processing→evaluation pipelines; batch-manage tasks across workspaces; diagnose failures via log analysis. Triggers include: data processing task management, data evaluation task management, task status polling, log retrieval for troubleshooting, output data preview, algorithm discovery, task pipeline orchestration, batch task management, failure diagnosis, dataset, proc-tasks, eval-tasks.

ClawHub Agent Skills author: huaweicloud-skills-team v1.0.1 MIT-0 11 files · 1 script body ≈ 5 164 tokens Open the sourceclawhub.ai analyzed 3 d ago

Manage CloudRobo data processing (proc-tasks) and data evaluation (eval-tasks) — query algorithms, create/list/show/update/delete/restart tasks; poll task…

As a process B 73/100 · Nearly there — weak spots: when it triggers

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
B
73/100
Nearly there
When it triggers w 12
20
Failures and branches w 10
50
Tools and files w 18
60
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 · 0

✓ No critical or high findings

Files scanned: 11. 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 ≈ 5164 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 73/100

  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5164 tokens
  • 100Steps. 87 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 717: enough signal without eating the budget
  • +4Structure: 45 headings
  • +3Step-by-step instructions: 87 items
  • +3Output format is stated explicitly
  • +4Has examples (20 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill mostly matches its CloudRobo task-management purpose, but it includes insecure TLS and credential-handling guidance that users should review before installing.
LLM: suspicious (high) · 11 Sept 2026