BB huawei-cloud-lts-log-inspector
Huawei Cloud LTS (Log Tank Service) log traffic statistics, log context query, host group and access config inspection, collection status patrol, and OBS transfer management for batch log export. Covers log histogram query, TOP-N traffic statistics, timeline traffic statistics, single-log context retrieval, host group listing, access config query, host collection status inspection, OBS transfer create/list/delete, and diagnostic workflows for traffic surge, collection break, and log flooding. Triggers include: 日志流量异常排查, 日志采集故障巡检, 故障深度定位, 日志批量导出, LTS流量统计, 日志上下文查询, 采集断流, 日志刷屏, log traffic anomaly, collection inspection, log context, LTS patrol, log flooding diagnose, offline log export, OBS transfer.
Huawei Cloud LTS (Log Tank Service) log traffic statistics, log context query, host group and access config inspection, collection status patrol, and OBS…
As a process B 66/100 · Nearly there — weak spots: result and completion, when it triggers, failures and branches
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Dangerous commands
cmd-pipe-to-shellscripts/test-cli-commands.sh:56Downloads and executes remote code from an unrecognised host (pipe to shell) (detector / deny-list definition; string literal in code, not executed; test fixture / example file)if ! echo "$cmd" | grep -qE '^(hcloud|python3|curl|bash) '; then
detectorcode literalfixture
Files scanned: 10. 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
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 23 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3838 tokens
- 100Progress reporting. Reports progress
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)
- +3Output format is not stated: the model decides each time
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 707: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (21 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.