AB huawei-cloud-asm-fuzzy-list
Query the list of Huawei Cloud ASM (Application Service Mesh) meshes belonging to the current tenant / project and fuzzy-match them by mesh name. Returns the mesh name (metadata.name), mesh id (metadata.uid), status phase and creation timestamp for every mesh whose name contains the given keyword (case-insensitive substring match, client-side). Uses the huaweicloudsdkasm Python SDK ListMeshes call (GET /v1/{project_id}/meshes). Read-only — never creates, modifies or deletes any mesh or related resource. Use this skill whenever the user wants to list/inspect the ASM meshes of the tenant or query the ASM name list with fuzzy matching, e.g. for mesh inventory, locating a mesh by name, daily inspection or troubleshooting. Triggers include: "query ASM list", "list ASM", "ASM name list", "ASM mesh list", "模糊查询ASM", "查询ASM列表", "ASM名称", "查询ASM网格列表", "list meshes", "查询服务网格", "服务网格列表", "ASM inventory", "find ASM mesh by name".
Query the list of Huawei Cloud ASM (Application Service Mesh) meshes belonging to the current tenant / project and fuzzy-match them by mesh name.
As a process B 69/100 · Nearly there — weak spots: failures and branches, running it twice, progress reporting
How to improve
- 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: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 69/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 36 steps, 1 vague phrases
- 100Result and completion. Output format and completion criterion are stated
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2147 tokens
- low 11 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 930: 120–800 characters recommended
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 12 example trigger phrases
- +4Structure: 14 headings
- +3Step-by-step instructions: 36 items
- +3Output format is stated explicitly
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.