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-ces-aom-capacity-assessmentgit 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-ces-aom-capacity-assessment)<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-ces-aom-capacity-assessment"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-ces-aom-capacity-assessment/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-ces-aom-capacity-assessment"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-ces-aom-capacity-assessment.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 | $0.00212 | $0.04474 |
| Opus 5.5 | $0.00085 | $0.01790 |
| Sonnet 5.5 | $0.00042 | $0.00895 |
| Haiku 4.5 | $0.00021 | $0.00447 |
Grade A, and why
huawei-cloud-ces-aom-capacity-assessment 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 29d 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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Huawei Cloud Capacity Assessment
Assesses instances in the Excel capacity template: collects monitoring data (hcloud CES; CCE and other cloud-native metrics via hcloud AOM), computes peak/valley multiples, pressure coefficients, and expected festival ceilings, decides whether business peaks (festival events) need scale-out, and writes results back to Excel.
Core division of labor (must follow)
- The script does all computation, data collection, and Excel read/write; the model only orchestrates the flow, selects modes, and reports results.
- The model must not manually compute peak/valley or pressure coefficients, and must not make logic decisions beyond writing Excel cells.
- The model must not investigate root causes of collection failures (§9.3); report failure details to the user as-is.
Script locations and dependencies
<SKILL_DIR>/scripts/capacity_cli.py # Unified CLI entry point
<SKILL_DIR>/scripts/requirements.txt # Dependency: openpyxl
<SKILL_DIR>/references/metrics.json # 238-metric registry (Chinese name → CES/AOM metric_name + namespace + dimensions + ceiling + unit)
<SKILL_DIR>/references/troubleshooting-dns.md # DNS troubleshooting when hcloud cannot connect
<SKILL_DIR>/references/region-map.md # Chinese region name ↔ region code mapping
<SKILL_DIR>/references/cli-installation-guide.md # hcloud installation/config (required for review)
<SKILL_DIR>/references/iam-policies.md # IAM permissions (CES/AOM read-only, required for review)
<SKILL_DIR>/references/verification-method.md # Verification method (required for review)
<SKILL_DIR>/references/acceptance-criteria.md # Acceptance criteria (required for review)
<SKILL_DIR>/templates/capacity_assessment_template.xlsx # Template (the Excel template users take and fill in)
First-time setup: pip install -r <SKILL_DIR>/scripts/requirements.txt
Four assessment modes
| Mode | Command | Time range |
|---|---|---|
| Single-instance historical | assess-row --mode historical --start ... --end ... |
user-specified |
| Full historical | assess-all --mode historical |
user-specified |
| Single-instance T-24 | assess-row --mode t24 |
last 24h (automatic) |
| Full T-24 | assess-all --mode t24 |
last 24h (automatic) |
What ships with it
16 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.
- references/acceptance-criteria.md 2.8 KB
- references/cli-installation-guide.md 1.6 KB
- references/iam-policies.md 2.1 KB
- references/metrics.json 105 KB
- references/region-map.md 1.8 KB
- references/troubleshooting-dns.md 4.0 KB
- references/verification-method.md 3.1 KB
- scripts/capacity_cli.py 18 KB runs code
- scripts/capacity/assessor.py 21 KB runs code
- scripts/capacity/calculator.py 6.3 KB runs code
- scripts/capacity/collector.py 18 KB runs code
- scripts/capacity/config.py 8.4 KB runs code
- scripts/capacity/excel_io.py 10 KB runs code
- scripts/capacity/registry.py 4.3 KB runs code
- scripts/requirements.txt 13 B
- templates/capacity_assessment_template.xlsx 12 KB
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.
- 29d ago First seen · 244 lines · 212 tokens per session scan A 54b84a265927
huawei-cloud-ces-aom-capacity-assessment is a skill published in the GitHub repository huaweicloud/huaweicloud-skills (59 stars, last pushed yesterday), licensed MIT. It adds 212 tokens to every session and 4,474 once invoked, about $0.0008 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 2026-09-29.
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