Agent skill

Azure Search Documents Py

by aiskillstore in aiskillstore/marketplace

Azure AI Search SDK for Python. An agent skill from aiskillstore/marketplace.

No licenceAuto-check passedAI & LLM Engineering

Install Azure Search Documents Py

skills CLI
$ npx skills add aiskillstore/marketplace --skill azure-search-documents-py -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aiskillstore/marketplace azure-search-documents-py --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aiskillstore/marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/sickn33/azure-search-documents-py .claude/skills/azure-search-documents-py && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azure-search-documents-py
GitHub stars
433
Used in
4 other repos
Token cost
~3.6k tokens
SKILL.md length
429 words
Files
2
Skills in repo
1,044
Repo updated
First seen
Licence
None found

At a glance

Azure AI Search SDK for Python. An agent skill from aiskillstore/marketplace.

  • Works in 7 steps: Use hybrid search for best relevance… → Enable semantic ranking for natural… → Index in batches of 100-1000 documents… → …
  • Semantic ranking
  • SKILL.md covers Installation, Environment Variables, Authentication and Client Types, plus 22 more sections
  • Calls pip; needs AZURE_SEARCH_API_KEY

What it does

Azure Search Documents Py is an agent skill from aiskillstore/marketplace. Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill-report.json`).

It sits in AI & LLM Engineering, covering Vector databases and Retrieval-augmented generation. It works with Azure AI Search and Python. The repository describes itself as: Security-audited skills for Claude, Codex & Claude Code. One-click install, quality verified.

When your agent uses it

  • Semantic ranking
  • Tasks that involve Vector databases
  • Tasks that involve Retrieval-augmented generation

Example prompts

  • “/azure-search-documents-py”

Requirements

  • Python 3
  • A credential in AZURE_SEARCH_API_KEY

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Use hybrid search for best relevance combining vector and keyword
  2. Enable semantic ranking for natural language queries
  3. Index in batches of 100-1000 documents for efficiency
  4. Use filters to narrow results before ranking
  5. Configure vector dimensions to match your embedding model
  6. Use HNSW algorithm for large-scale vector search
  7. Create suggesters at index creation time (cannot add later)

What it can do on your machine

Read from SKILL.md and the folder at commit 44923f3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • AZURE_SEARCH_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Azure Search Documents Py loads about 3.6k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 429 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Without a licence we can't republish the file, so here is its outline and opening line. It has 429 words (~3,632 tokens).

“Full-text, vector, and hybrid search with AI enrichment capabilities.”

— opening of SKILL.md by aiskillstore
name
azure-search-documents-py
risk
unknown
source
community
date_added
2026-02-27

Read the full SKILL.md on GitHub

Files

SKILL.md and 1 other file in skills/sickn33/azure-search-documents-py of aiskillstore/marketplace.

  • SKILL.md
  • skill-report.json

Open the folder on GitHubat commit 44923f3

Used in 4 other repositories

We found 17 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in aiskillstore/marketplace, which our catalogue first saw on October 9, 2026.

Compare with similar skills

Azure Search Documents Py next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Azure Search Documents Py compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Azure Search Documents Py this skillaiskillstore/marketplace4334 repos~3.6kAutomated safety check: PassNone
Azure AI Search Python SDKmicrosoft/skills3.1k—~4.4kAutomated safety check: PassMIT
Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs13k7 repos~2.3kAutomated safety check: PassMIT
Postgres Hybrid Text Searchtimescale/pg-aiguide1.9k—~3.1kAutomated safety check: PassApache-2.0
Aliyun Opensearch Searchcinience/alicloud-skills397—~1.1kAutomated safety check: PassMIT
Retail Product Search Agentgoogle/adk-recipes10k—~3kAutomated safety check: PassApache-2.0

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Questions about Azure Search Documents Py

What does Azure Search Documents Py do?

Azure AI Search SDK for Python. An agent skill from aiskillstore/marketplace. Azure Search Documents Py is an agent skill from aiskillstore/marketplace. Azure AI Search SDK for Python.

When should I use Azure Search Documents Py?

Azure Search Documents Py fits situations like: semantic ranking; tasks that involve Vector databases; tasks that involve Retrieval-augmented generation.

How do I install Azure Search Documents Py in Claude Code?

Run `npx skills add aiskillstore/marketplace --skill azure-search-documents-py -a claude-code`. Or copy the skill folder (skills/sickn33/azure-search-documents-py in aiskillstore/marketplace) into .claude/skills/azure-search-documents-py in your project. Claude Code loads it when a task matches its description.

How do I install Azure Search Documents Py in Codex?

Run `npx skills add aiskillstore/marketplace --skill azure-search-documents-py -a codex`. Or copy the skill folder (skills/sickn33/azure-search-documents-py in aiskillstore/marketplace) into .agents/skills/azure-search-documents-py in your project. Codex loads it when a task matches its description.

Can I use Azure Search Documents Py in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aiskillstore/marketplace --skill azure-search-documents-py -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-search-documents-py, .gemini/skills/azure-search-documents-py, .github/skills/azure-search-documents-py and .opencode/skills/azure-search-documents-py in your project.

What does Azure Search Documents Py need to run?

Going by SKILL.md and its folder, Azure Search Documents Py needs the command-line tools its instructions call (pip) and credentials named AZURE_SEARCH_API_KEY. Our summary lists: Python 3; A credential in AZURE_SEARCH_API_KEY.

Does Azure Search Documents Py access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Azure Search Documents Py safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure Search Documents Py use?

No licence was found for Azure Search Documents Py or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Azure Search Documents Py use?

About 3.6k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Azure Search Documents Py?

Skills that share tags, products or a category with Azure Search Documents Py: Azure AI Search Python SDK (microsoft/skills, 3.1k stars), Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars), Postgres Hybrid Text Search (timescale/pg-aiguide, 1.9k stars) and Aliyun Opensearch Search (cinience/alicloud-skills, 397 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure Search Documents Py?

aiskillstore (a GitHub organization) maintains it in aiskillstore/marketplace, which has 433 GitHub stars. The repository holds 1,044 skills in this directory. The repository was last updated on October 10, 2026.

Source: aiskillstore/marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.