SKILLEMALL.ai

BF alibabacloud-devops

Automate Alibaba Cloud Yunxiao DevOps tasks — create and run pipelines, manage code repositories and merge requests, track work items and sprints, create test cases, manage artifacts, and drive application release workflows across 8 Yunxiao products. Triggers: "Yunxiao", "DevOps", "pipeline", "code repository", "merge request", "work item", "sprint", "test case", "application delivery", "artifact repository", "Codeup", "Flow", "Projex", "AppStack", "Packages", "Testhub"

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.3 MIT-0 17 files body ≈ 6 184 tokens Open the sourceclawhub.ai analyzed 2 d ago

Automate Alibaba Cloud Yunxiao DevOps tasks — create and run pipelines, manage code repositories and merge requests, track work items and sprints, create test…

As a process F 64/100 · Will not run — References files that are not bundled: references/aliyun-cli-install.md, references/mcp-setup.md, references/intent-classification.md

ProcedureDockerSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
F
64/100
Will not run
References files that are not bundled: references/aliyun-cli-install.md, references/mcp-setup.md, references/intent-classification.md
Tools and files w 18
0
Result and completion w 14
40
When it triggers w 12
50
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.
  3. The text references files that are not there: add them or drop the references.
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: 0. 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 ≈ 6184 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/aliyun-cli-install.md
  • warning missing-ref reference to a missing file: references/mcp-setup.md
  • warning missing-ref reference to a missing file: references/intent-classification.md
  • warning missing-ref reference to a missing file: references/acceptance-criteria.md
  • warning missing-ref reference to a missing file: scripts/discover-commands.sh
  • warning missing-ref reference to a missing file: scripts/mcporter-call.sh

Process rating: all ten parameters 64/100

Will not run. References files that are not bundled: references/aliyun-cli-install.md, references/mcp-setup.md, references/intent-classification.md
  • 0Tools and files. 6 referenced file(s) missing: references/aliyun-cli-install.md, references/mcp-setup.md, references/intent-classification.md
  • 40Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 6184 tokens
  • 85Steps. 39 steps, 2 vague phrases
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 15 example trigger phrases
  • +3Description length 474: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 39 items
  • +4Has examples (20 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: suspicious
This appears to be a legitimate Alibaba Cloud Yunxiao DevOps skill, but it needs review because it can automatically install tooling and perform broad live CI/CD, repository, membership, and release changes.
LLM: suspicious (high) · 17 Aug 2026