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gpt-rag-ingestion: Skill for Claude Code

.github/skills/documentation-consistency/SKILL.md

documentation-consistency is a skill for Claude Code, Codex from Azure/gpt-rag-ingestion. It costs 31 tokens per session (208 once invoked), scanned A, original, MIT.

Documentation guidance for keeping a document-ingestion service and its published GPT-RAG guides in agreement. It covers formats, settings, search indexes, deployments, audits, and operator behavior.

In plain words
What is it for?
Use it when code changes affect documented formats, configuration, search fields, endpoints, jobs, deployment modes, or operational procedures.
Why use it?
It prevents documentation from describing old settings, examples, or service behavior. That makes the instructions more reliable for users and operators.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

This is Azure/gpt-rag-ingestion's own configuration. It tells Claude Code and Codex how to work on gpt-rag-ingestion itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything gpt-rag-ingestion configures →

not rated 188repo 1mo ago A scan SkillSpector: pass 31 tokens original MIT
View source ↗ Azure/gpt-rag-ingestion
About the project

GPT-RAG Data Ingestion is a service that processes documents such as PDFs, images, spreadsheets, transcripts, and SharePoint files so they can be searched through Azure AI Search. It prepares data with format-specific chunking and text or image embeddings for multimodal retrieval in agent-based applications.

Azure/gpt-rag-ingestion · 188 stars · on GitHub

Reuse

Borrowing it

Nothing to install: this file belongs to Azure/gpt-rag-ingestion. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Azure/gpt-rag-ingestion/main/.github/skills/documentation-consistency/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Azure/gpt-rag-ingestion

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for documentation-consistency

README.md
[![agentmods](https://agentmods.dev/badge/skills/azure/gpt-rag-ingestion/documentation-consistency/github.svg)](https://agentmods.dev/skills/azure/gpt-rag-ingestion/documentation-consistency)
Your own site
<a href="https://agentmods.dev/skills/azure/gpt-rag-ingestion/documentation-consistency"><img src="https://agentmods.dev/badge/skills/azure/gpt-rag-ingestion/documentation-consistency/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.

agentmods 80×15 button for documentation-consistency

Your own site · 80×15
<a href="https://agentmods.dev/skills/azure/gpt-rag-ingestion/documentation-consistency"><img src="https://agentmods.dev/badge/skills/azure/gpt-rag-ingestion/documentation-consistency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 208 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.00208
Opus 5.5 $0.00012 $0.00083
Sonnet 5.5 $0.00006 $0.00042
Haiku 4.5 $0.00003 $0.00021

Measured 2mo ago against content hash 46cdfdf790e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

documentation-consistency 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 2mo 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.

.github/skills/documentation-consistency/SKILL.md · 21 lines

What it actually says

Ingestion documentation consistency

  1. Identify the user, operator, or cross-component behavior that changed.
  2. Search this repository for the format, configuration key, index field, endpoint, job type, contract, and previous terminology.
  3. Update ingestion-specific service or audit guidance in README.md.
  4. Search the docs branch of Azure/GPT-RAG for cross-component user and operator guidance and update every affected page in the coordinated change.
  5. Register new published pages in that branch's mkdocs.yml.
  6. Ensure examples match current defaults, App Configuration labels, supported deployment modes, and released component behavior.

Keep the service README concise and link to https://azure.github.io/GPT-RAG/ for broad product guidance. Report the documentation branch or pull request in the implementation handoff.

Changes

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.

  1. 2mo ago First seen · 21 lines · 31 tokens per session scan A 46cdfdf790e7

Subscribe to this mod's changes

documentation-consistency is a skill published in the GitHub repository Azure/gpt-rag-ingestion (188 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 208 once invoked, about $0.0001 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 2026-08-30.

Writing and docs
Related

documentation-consistency compared with skills from other repositories

documentation-consistency next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
documentation-consistencyAzure/gpt-rag-ingestionSkill1881mo agoMITA31Claude Code, Codex
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill313k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143ktodayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143ktodayMITA103Claude Code