add-new-entry

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Workflow and tools for adding new entries from temp.md to the section files. Includes legend format, section reference, code tools, and common pitfalls. USE FOR: Adding new resources to the knowledge base. DO NOT USE FOR: Editing existing entries or restructuring sections.

kimtth By kimtth schedule Updated 5/22/2026

name: add-new-entry description: "Workflow and tools for adding new entries from temp.md to the section files. Includes legend format, section reference, code tools, and common pitfalls. USE FOR: Adding new resources to the knowledge base. DO NOT USE FOR: Editing existing entries or restructuring sections."

Workflow: Adding New Entries from temp.md

temp.md is the raw input — an unformatted checklist of URLs and short notes. The goal is to produce temp_entries.md as a properly formatted staging file ready to paste into the target section files.

Steps in order:

  1. Classify each URL → determine which section file (azure.md, applications.md, models_research.md, best_practices.md) and which section heading it belongs to.
  2. Fetch descriptions — use code/fetch_github_description.py for GitHub repos. For arXiv papers and blog/web links, use fetch_webpage to extract a one-sentence description.
  3. Fetch creation dates — use code/get_github_dates.py for GitHub repos. For arXiv, derive the date from the ID prefix (e.g., 2602.xxxxx → Feb 2026). For blog posts, read from the page.
  4. Add star badges — use code/add_github_stars.py for all GitHub links.
  5. Apply legend symbols — see the Legend Format section below. azure.md should not use emoji markers.
  6. Shorten descriptions — keep each description to ≤15 words. One punchy sentence. Do not repeat the link name.

Legend Format

azure.md — dash-bullet, no emojis

- [Name](url) - Description. (Mon YYYY) ![stars](...)
  • Do not use emoji markers in azure.md (no link-prefix emojis and no description-prefix emojis).
  • Date is in (Mon YYYY) parentheses format with no brackets.
  • Star badge goes at the end of the line, after the date.

Examples:

- [Azure ML Prompt Flow](https://learn.microsoft.com/...) - Visual designer for prompt orchestration and evaluation. (Jun 2023)
- [APIM-Sample](https://github.com/Azure-Samples/APIM-Sample) - Single APIM endpoint for multiple models. (Jan 2026) ![**github stars**](...)

applications.md, models_research.md, best_practices.md — numbered list (or dash), symbol appended to link text

1. [Name](url): Description. [Mon YYYY] ![stars](...)

or (for entries that use dash bullets in that section):

- [Name✍️](url): Description. [Mon YYYY]
  • The legend symbol is appended inside the link text, immediately after the name (no space before the symbol).
  • Date is in [Mon YYYY] square-bracket format.
  • Star badge goes at the end of the line, after the date.
  • Use numbered list (1.) when the surrounding section uses numbered lists; dash (-) when not.

Examples:

1. [Auto-Claude](https://github.com/AndyMik90/Auto-Claude): Autonomous multi-session AI coding. [Dec 2025] ![**github stars**](...)
1. [Towards AI Search Paradigm📑](https://arxiv.org/abs/2506.17188): Modular 4-agent system using DAGs for retrieval-intensive search. [Jun 2025]
- [Claude Code Security✍️](https://www.anthropic.com/news/claude-code-security): Claude Code on the web for scanning codebases. [Feb 2026]

Legend Symbols

Symbol Meaning
✍️ Blog post / documentation / web page
📑 Academic paper (arXiv)
📺 Video content
🤗 Hugging Face resource

Section Reference

Use exact heading names when labeling entries in temp_entries.md. Format: ## <filename> - <Section Name>:.

azure.md

  • Developer Tooling
  • Agent Frameworks
  • Agent Development
  • Microsoft Copilot Products
  • Azure OpenAI Samples
  • Azure OpenAI Application
  • Azure OpenAI Accelerator & Samples
  • LLM Frameworks
  • Prompt Tooling
  • Microsoft Copilot Products
  • Copilot Development
  • Azure AI Search / Azure AI Services
  • Microsoft Research
  • Risk & LLMOps

applications.md

  • AI Application → ### **AI Application** (contains #### Agent & Application, #### Skill, #### Coding, #### Deep Research, #### Memory, #### Gateway, #### Caching, #### Data Processing)
  • Agent Protocol → ### **Agent Protocol** (contains #### Model Context Protocol (MCP), #### A2A, #### Computer use)
  • Vector Database & Embedding → ### **Vector Database & Embedding**
  • RAG (Retrieval-Augmented Generation) → ## **RAG ...

Tip: The sub-sections under AI Application (Agent & Application, Skill, Coding, Deep Research) are #### headings. Use the exact name, e.g., applications.md - Skill, applications.md - Coding, applications.md - Agent & Application, applications.md - Deep Research, applications.md - Model Context Protocol (MCP).

models_research.md

  • OpenAI Products → ### **OpenAI Products**
  • Anthropic AI Products → ### **Anthropic AI Products**
  • Google AI Products → ### **Google AI Products**
  • AGI Discussion and Social Impact (no explicit heading — look for related entries near end of file)
  • Large Language Model Collection
  • Reasoning

best_practices.md

  • Agent Research → ### **Agent Research**
  • RAG Research → ### **RAG Research**
  • Agent Design Patterns → ### **Agent Design Patterns**
  • Reflection, Tool Use, Planning and Multi-agent collaboration

Code Tools Reference

All tools are in code/. Run with python code/<script>.py.

Script Purpose
fetch_github_description.py Fetch GitHub repo descriptions; appends after the link colon. Skips lines that already have a description.
get_github_dates.py Fetch GitHub repo creation date; appends [Mon YYYY] or (Mon YYYY). Skips lines already dated.
add_github_stars.py Append star badge to lines with GitHub links. Skips duplicates.
fetch_popular_papers.py Query Semantic Scholar for top-cited papers; writes section/x_popular_papers.md.
update_citation_counts.py Update citation counts for ranked paper sections via Semantic Scholar.
check_unused_files.py Scan markdown for file refs; move unreferenced files to files/_bak/.

For arXiv papers and blog posts, fetch_github_description.py does not apply. Use fetch_webpage (agent tool) to retrieve a description from the URL.

Common CLI pattern:

python code/fetch_github_description.py --input temp.md --output temp_with_desc.md
python code/get_github_dates.py --input temp_with_desc.md --in-place
python code/add_github_stars.py --input temp_with_desc.md --in-place

Common Pitfalls (Lessons Learned)

  1. Wrong legend placement: In azure.md, do not use emoji markers at all. In all other files, the symbol is appended to the link name inside [Name✍️]. Never mix these two formats.

  2. Wrong section names: Section labels in temp_entries.md must match the actual heading text in the target file exactly. Check the file before assigning. Do not invent new section names.

  3. Missing descriptions for non-GitHub links: fetch_github_description.py only works for github.com URLs. For arXiv, blog, and product pages, you must fetch the page and write a description manually.

  4. Verbose descriptions: Keep descriptions to ≤15 words. Do not repeat the name. No trailing "for use with", "that helps you", or similar filler.

  5. Date format mismatch: azure.md uses (Mon YYYY) parentheses. All other section files use [Mon YYYY] square brackets.

  6. emoji stripping via heredoc: Writing file content via PowerShell heredoc strips emoji characters. Use replace_string_in_file or multi_replace_string_in_file to patch emoji symbols back in if they are lost.

  7. Star badges on non-GitHub links: Only add star badges to github.com links. Blog posts, arXiv papers, and product pages must not have a star badge.

Install via CLI
npx skills add https://github.com/kimtth/awesome-azure-openai-llm --skill add-new-entry
Repository Details
star Stars 402
call_split Forks 57
navigation Branch main
article Path SKILL.md
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