Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add huaweicloud/huaweicloud-skills --skill huawei-cloud-alarm-bind-inspectiongit clone --depth 1 https://github.com/huaweicloud/huaweicloud-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-alarm-bind-inspection)<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-alarm-bind-inspection"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-alarm-bind-inspection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-alarm-bind-inspection"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-alarm-bind-inspection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00179 | $0.05418 |
| Opus 5.5 | $0.00072 | $0.02167 |
| Sonnet 5.5 | $0.00036 | $0.01084 |
| Haiku 4.5 | $0.00018 | $0.00542 |
Grade A, and why
huawei-cloud-alarm-bind-inspection scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alarm Bind Inspection
Overview
Alarm bind inspection: fetches all alarm rules for the current account via CES (Cloud Eye Service) SDK and hcloud AOM CLI, extracts CES and AOM baseline metrics/events from the alarm baseline Excel, and compares and analyzes alarm binding status. Two merged analysis dimensions (CES + AOM data merged into the same tab, distinguished by a "monitoring system" column):
- Metric baseline: analyzes baseline metric binding rate per instance + metric dimension (CES metrics + AOM metrics; AOM services without core instances are skipped)
- Event baseline: analyzes baseline event binding rate per instance (CES events + AOM events; AOM services without core instances are skipped)
Uses AK/SK authentication (current account only, no multi-customer mode). AK/SK are read from environment variables (HW_ACCESS_KEY, HW_SECRET_KEY). Regions are auto-extracted from core_instances.json (multi-region supported). Project ID is auto-fetched via hcloud CLI per target region — no manual configuration needed.
Workflow
Step 1: Check Python Environment and Dependencies
- Check Python: run
python --version, confirm Python exists and version > 3.9 - Install dependencies:
python -m pip install -r requirements.txt
Prerequisites:
- Python version > 3.9
- AK/SK configured in environment variables (
HW_ACCESS_KEY,HW_SECRET_KEY) hcloudCLI available (used to auto-fetch Project ID)- Third-party dependencies: see
requirements.txt(includeshuaweicloudsdkces,huaweicloudsdkcore)
Step 2: Extract Core Instance List from Excel
python scripts/generate_core_instance.py
Extracts the core instance list from the key resource marking Excel (single-customer mode, no per-customer grouping).
Pre-checks (abort if any not met):
assets/关键资源标记表.xlsxmust exist- Must contain sheet
关键资源标记 - Must contain all columns:
region,resource_type,resource_id,是否核心业务 - Must contain at least one data row where
是否核心业务=是with non-emptyresource_typeandresource_id
What ships with it
41 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .gitignore 26 B
- assets/关键资源标记表.xlsx 5.7 KB
- assets/华为云租户面监控告警基线-V26.01-beta.xlsx 246 KB
- references/acceptance-criteria.md 7.1 KB
- references/cli-installation-guide.md 5.5 KB
- references/design.md 9.5 KB
- references/iam-policies.md 6.3 KB
- references/verification-method.md 7.5 KB
- requirements.txt 106 B
- scripts/alarm_api.py 9.7 KB runs code
- scripts/aom_bind_analysis.py 6.3 KB runs code
- scripts/aom_event_bind_analysis.py 5.6 KB runs code
- scripts/bind_analysis.py 22 KB runs code
- scripts/config.py 3.9 KB runs code
- scripts/diagnose_event.py 1.7 KB runs code
- scripts/enrich_metric_dimension.py 16 KB runs code
- scripts/event_bind_analysis.py 17 KB runs code
- scripts/generate_alarm_baseline.py 20 KB runs code
- scripts/generate_core_instance.py 6.7 KB runs code
- scripts/generate_event_excel_report.py 12 KB runs code
- scripts/generate_excel_report.py 24 KB runs code
- scripts/generate_suggestion.py 28 KB runs code
- scripts/main_alarm.py 3.7 KB runs code
- scripts/main_aom_alarm.py 5.5 KB runs code
- scripts/main_event.py 4.2 KB runs code
- scripts/patch_excel.py 8.6 KB runs code
- scripts/regions.py 31 KB runs code
- scripts/resource_type.py 11 KB runs code
- scripts/suggestion_data.py 12 KB runs code
- scripts/suggestion_html.py 13 KB runs code
- scripts/suggestion_template.py 42 KB runs code
- scripts/tool.py 9.6 KB runs code
- scripts/workspace.py 1.4 KB runs code
- tests/__init__.py 0 B runs code
- tests/conftest.py 2.1 KB runs code
- tests/fixtures/core_instances_sample.json 1.3 KB
- tests/fixtures/indicator_baseline_sample.json 1.9 KB
- tests/fixtures/online_alarm_rules_sample.json 3.0 KB
- tests/test_bind_analysis.py 9.4 KB runs code
- tests/test_regression.py 4.2 KB runs code
- tests/test_suggestion_data.py 4.6 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 433 lines · 179 tokens per session scan A 056bfc015648
huawei-cloud-alarm-bind-inspection is a skill published in the GitHub repository huaweicloud/huaweicloud-skills (59 stars, last pushed yesterday), licensed MIT. It adds 179 tokens to every session and 5,418 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-24.
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