AB huawei-cloud-find-skills
Invoke this skill to search, list, query, discover, browse, find and install any Huawei Cloud (华为云) agent skill. Triggers include: "华为云", "华为云有什么skill", "华为云相关skill", "华为云agent skill 市场", "华为云skill类目", "explore Huawei Cloud skills", "show Huawei Cloud skill categories", "does a Huawei Cloud skill exist for...", "which Huawei Cloud skills exist", "搜索华为云技能", "查询华为云skill列表", "有没有管理ECS/OBS/RDS的skill", "帮我找 XX 华为云skill", "介绍 XX Skill 内容", "华为云 XX Skill 具体做什么", "安装华为云Skill".
Invoke this skill to search, list, query, discover, browse, find and install any Huawei Cloud (华为云) agent skill.
As a process B 66/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 66/100
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 39 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3059 tokens
- 100Progress reporting. Reports progress
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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 15 example trigger phrases
- +3Description length 473: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 39 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.