Aliyun Platform Docs Benchmark

Community

cinience

aliyun-platform-docs-benchmark

Use when benchmarking similar product documentation and API documentation across Alibaba Cloud, AWS, Azure, GCP, Tencent Cloud, Volcano Engine, and Huawei Cloud. Given one product keyword, auto-discover latest official docs/API links, score quality consistently, and output detailed prioritized improvement recommendations.

Overview

Publisher	cinience
Repository	`alicloud-skills`
Skill name	`aliyun-platform-docs-benchmark`
Stars	397
Forks	34
Bundled files	5
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by cinience on GitHub. Read the source before you install it.

Installation

Install the Aliyun Platform Docs Benchmark AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/cinience/alicloud-skills/tree/main/skills/platform/docs/aliyun-platform-docs-benchmark
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/cinience/alicloud-skills/tree/main/skills/platform/docs/aliyun-platform-docs-benchmark

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/cinience/alicloud-skills.git /tmp/alicloud-skills
mkdir -p .claude/skills
cp -r /tmp/alicloud-skills/skills/platform/docs/aliyun-platform-docs-benchmark .claude/skills/aliyun-platform-docs-benchmark

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aliyun Platform Docs Benchmark in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aliyun Platform Docs Benchmark on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aliyun Platform Docs Benchmark is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Multi-Cloud Product Docs/API Benchmark

Use this skill when the user wants cross-cloud documentation/API comparison for similar products.

Supported clouds

Alibaba Cloud
AWS
Azure
GCP
Tencent Cloud
Volcano Engine
Huawei Cloud

Data source policy

L0 (highest): user-pinned official links via --<provider>-links
L1: machine-readable official metadata/source
- GCP: Discovery API
- AWS: API Models repository
- Azure: REST API Specs repository
L2: official-domain constrained web discovery fallback
L3: insufficient discovery (low confidence)

Workflow

Run the benchmark script:

bash
python skills/platform/docs/aliyun-platform-docs-benchmark/scripts/benchmark_multicloud_docs_api.py --product "<product keyword>"

Example:

bash
python skills/platform/docs/aliyun-platform-docs-benchmark/scripts/benchmark_multicloud_docs_api.py --product "serverless"

LLM platform benchmark example (Bailian/Bedrock/Azure OpenAI/Vertex AI/Hunyuan/Ark/Pangu):

bash
python skills/platform/docs/aliyun-platform-docs-benchmark/scripts/benchmark_multicloud_docs_api.py --product "Bailian" --preset "llm-platform"

If --preset is omitted, script attempts to auto-match preset based on keyword.

Scoring weights can be switched by profile (see references/scoring.json):

bash
python skills/platform/docs/aliyun-platform-docs-benchmark/scripts/benchmark_multicloud_docs_api.py --product "Bailian" --preset "llm-platform" --scoring-profile "llm-platform"

Optional: pin authoritative links

Auto-discovery may miss pages. For stricter comparison, pass official links manually:

bash
python skills/platform/docs/aliyun-platform-docs-benchmark/scripts/benchmark_multicloud_docs_api.py \
  --product "object storage" \
  --aws-links "https://docs.aws.amazon.com/AmazonS3/latest/userguide/Welcome.html" \
  --azure-links "https://learn.microsoft.com/azure/storage/blobs/"

Available manual flags:

--alicloud-links
--aws-links
--azure-links
--gcp-links
--tencent-links
--volcengine-links
--huawei-links

Each flag accepts comma-separated URLs.

Output policy

All artifacts must be written under:

output/aliyun-platform-docs-benchmark/

Per run:

benchmark_evidence.json
benchmark_report.md

Reporting guidance

When answering the user:

Show score ranking across all providers.
Highlight top gaps (P0/P1/P2) and concrete fix actions.
If discovery confidence is low, ask user to provide pinned links and rerun.

Validation

bash
mkdir -p output/aliyun-platform-docs-benchmark
for f in skills/platform/docs/aliyun-platform-docs-benchmark/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/aliyun-platform-docs-benchmark/validate.txt

Pass criteria: command exits 0 and output/aliyun-platform-docs-benchmark/validate.txt is generated.

Output And Evidence

Save artifacts, command outputs, and API response summaries under output/aliyun-platform-docs-benchmark/.
Include key parameters (region/resource id/time range) in evidence files for reproducibility.

Prerequisites

Configure least-privilege Alibaba Cloud credentials before execution.
Prefer environment variables: ALIBABACLOUD_ACCESS_KEY_ID, ALIBABACLOUD_ACCESS_KEY_SECRET, optional ALIBABACLOUD_REGION_ID.
If region is unclear, ask the user before running mutating operations.

References

Rubric: references/review-rubric.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB
references/presets.json1 KB
references/review-rubric.md1 KB
references/scoring.json1 KB
scripts/benchmark_multicloud_docs_api.py23 KB

Frequently asked questions

What does the Aliyun Platform Docs Benchmark AI skill do?

Why use Aliyun Platform Docs Benchmark on TypingMind?

Because you install it once and use it with any model. Aliyun Platform Docs Benchmark is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aliyun Platform Docs Benchmark in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cinience/alicloud-skills/tree/main/skills/platform/docs/aliyun-platform-docs-benchmark. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aliyun Platform Docs Benchmark?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aliyun Platform Docs Benchmark?

As many as you like. As long as a model supports skills, you can use Aliyun Platform Docs Benchmark with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aliyun Platform Docs Benchmark AI skill free?

Yes. It is published on GitHub by cinience under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Multi-Cloud Product Docs/API Benchmark

Supported clouds

Data source policy

Workflow

Optional: pin authoritative links

Output policy

Reporting guidance

Validation

Output And Evidence

Prerequisites

References

Bundled files

Frequently asked questions

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